Forthcoming articles

International Journal of Modelling, Identification and Control

International Journal of Modelling, Identification and Control (IJMIC)

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International Journal of Modelling, Identification and Control (54 papers in press)

Regular Issues

  • Designing Route Guidance Strategy with Travellers Stochastic Compliance: A Bi-level Optimal Control Procedure
    by Wei-li Sun, Ling-long Hu, Ping Li, Hui Wang 
    Keywords: .

  • Comparision of hybrid path planning approaches for vehicles in 3D non-deterministic environments   Order a copy of this article
    by Denis Beloglazov, Valery Finaev, Mikhail Medvedev, Igor Shapovalov, Viktor Soloviev 
    Abstract: The article presents the development and analysis of hybrid path planning systems for vehicles. Two types of planner structure are defined. In the first type of system, several basic path planning methods operate together. In the systems of the second type, parameters and initial data of one basic method are modified by additional algorithms. We developed the controller that solves positioning and path-following problems with a high accuracy. Hybrid path-planning systems are developed for a hexacopter based on the virtual fields method and fuzzy logic. In the first synthesised system, the special algorithm of sensor data analysis modifies an initial data to use the virtual fields method.
    Keywords: hybrid planner; virtual fields; fuzzy logic; obstacle points cloud analysis; hexacopter control; position-path controller.

  • Survey and tutorial on multiple model methodologies in modelling, identification and control   Order a copy of this article
    by Weicun Zhang, Li Zhao 
    Abstract: Multiple model methodology is an important approach in modelling, identification and control of complicated systems with large uncertainties (parameter uncertainty or even model structure uncertainties). It agrees with the idea of 'divide and conquer' in solving engineering problems. There are two representative strategies with scheduling the multiple models, i.e., switching strategy and weighting strategy. Theses two strategies can be alternatively viewed as identification of the correct model/controller. Consequently, any reasonable control system design method can be incorporated with switching or weighting methodology to formulate robust and adaptive control schemes. This survey paper gives a brief hostorical review of the development of Multiple Model Adaptive Estimation (MMAE) and Multiple Model Adaptive Control (MMAC), then moves focus on the new progress of weighted MMAC (WMMAC) that has emerged in recent years, including the weighting algorithm and stability analysis of WMMAC systems, based on virtual equivalent system (VES) theory.
    Keywords: MMAE; MMAC; stability; convergence; weighting algorithm; VES.

  • Robust active steering control for vehicle rollover prevention   Order a copy of this article
    by Ke Shao, Jinchuan Zheng, Kang Huang 
    Abstract: This paper presents a dynamic vehicle rollover model and robust controller for rollover prevention by using a steer-by-wire (SbW) system. Firstly, a linear vehicle dynamic model is derived whose behaviour varies as a function of the time-varying vehicle speed. Next, a load transfer ratio (LTR) model is proposed for measuring the rollover conditions in a vehicle. In particular, the LTR model is generalised based on the conventional one by explicitly considering the rolling motion of the sprung mass. Moreover, the relationship of LTR between steering angle and vehicle speed is analysed. To prevent the undesired rollovers, a sliding mode control (SMC) approach is then used to design the robust controller for rollover prevention. Finally, simulation results are shown to verify the efficiency of rollover prevention under the proposed controller and its robustness against the vehicle speed and vehicle parameter variations.
    Keywords: Load transfer ratio; rollover prevention; sliding mode control; steer-by-wire system; robustness.

  • Biotechnical measurement and Monitoring system controlled features for determining the level of a state of environment and health of the person in ecologically adverse regions on the basis of collectives of hybrid decisive rules   Order a copy of this article
    by Riad Taha Al-kasasbeh, Nikolay Korenevskiy, Sergey Filist, Olga Vladimirovna Shatalova, Mahdi Alshamasin, Ashraf Shaqadan 
    Abstract: Setting exposure criteria to environmental pollutants is dependent on a range of interrelated variables, therefore it is complicated to understand and model exposure levels. Fuzzy logic is a convenient approach to integrate expert judgement and mathematical modelling in one prediction model. Monitoring the health state of a population is useful tool to develop and calibrate parameters of a fuzzy logic model. Analysis of the indistinct decisive rules making a basis of creation of knowledge bases of expert systems, solving problems of monitoring of a state of environment and the health of people on the basis of collectives of the hybrid mathematical models working with diverse structure of data in the absence of their exact analytical description are considered. Disease risk was analysed for populations living in two environmental conditions, one polluted mining community (Zheleznogorsk city) and one cleaner environment community (Kursk city). A fuzzy classification model was developed for the sampled communities using real health data. The occurrences of respiration and digestion diseases and psycho-emotional stress were used as indicators. The disease risk classification accuracy was measured using diagnostic sensitivity and predictive importance. The accuracy of disease occurrence exceeded 0.9 for three diseases intoxication, pneumoconiosis, and bronchitis.
    Keywords: ecology; health of the person; decisive rules; fuzzy logic; prospecting analysis; monitoring; expert systems.

  • High-order sliding mode control for variable speed PMSG wind turbine based disturbance observer   Order a copy of this article
    by Marwa Ayadi 
    Abstract: This paper introduces a model-based control system for Variable Speed Wind Energy Conversion System (VSWECS) based Permanent Magnet Synchronous Generator (PMSG). Compared with traditional wind turbines operating methods, these variable speed systems have the advantages of increasing the energy capture and reducing the mechanical stress. In order to exploit this latest advantage, a High Order Sliding Mode (HOSM) control strategy has been developed to enhance system performances, ensure the maximum power point tracking (MPPT) and track the generator reference speed. Moreover, for the WT system, the turbine torque is considered as an unmeasurable disturbance. Therefore, using a modified disturbance observer will allow directly tracking of the maximum power point. The stability analysis of the system has been proved using the Lyapunov theory. Finally, simulation results have been presented to verify the proposed approach efficiency.
    Keywords: wind turbine; high order sliding mode control; permanent magnet synchronous generator; disturbance observer.

  • A new five-dimensional four-wing hyperchaotic system with hidden attractor, its electronic circuit realisation and synchronisation via integral sliding mode control   Order a copy of this article
    by Sundarapandian Vaidyanathan, Leutcho Gervais Dolvis, Kengne Jacques, Chang-Hua Lien, Aceng Sambas 
    Abstract: This paper reports a new five-dimensional four-wing hyperchaotic system with hidden attractor. First, this paper discusses the dynamic properties of the new four-wing system with a detailed bifurcation analysis, coexistence of attractors and multistability, offset boosting, Lyapunov exponents, etc. It is shown that the new four-wing system has no rest point and thus it exhibits hidden attractor. The new four-wing system exhibits two positive Lyapunov characteristic exponents and a large value of Kaplan-Yorke dimension indicating high complexity of the system. We realise the dynamic equations of the new four-wing system with an electronic circuit and simulations via MultiSIM. As a control application, we derive new results for the complete synchronisation of the new four-wing systems via integral sliding mode control. MATLAB simulations are adequately provided to illustrate modelling and applications of the new four-wing system with hyperchaotic four-wing attractor.
    Keywords: hyperchaos; hyperchaotic systems; four-wing system; integral sliding mode control; circuit design.

  • Identification scheme for switched linear systems in presence of bounded noise   Order a copy of this article
    by Abdelhak Goudjil, Mathieu Pouliquen, Eric Pigeon, Olivier Gehan 
    Abstract: This paper discusses an online switched linear systems identification algorithm based on a modified Outer Bounding Ellipsoid (OBE) algorithm. It alternates between estimating discrete states and system parameters updating. Theoretical analysis show the convergence result given that certain persistent excitation condition are met. This algorithm can be adapted to solve offline identification as well as MIMO system identification. Simulation results show the algorithm has improvement in both estimation error and computation time over existing methods.
    Keywords: identification; switched linear systems; bounded noise.

  • A novel chattering-free PI sliding mode control for a class of nonlinear underactuated systems   Order a copy of this article
    by Shuang Liu, Pengwei Li 
    Abstract: For the tracking and stabilisation control problem of nonlinear underactuated systems, a novel chattering-free sliding mode control approach is proposed in this paper. According to Lyapunov theorem of stability, sliding mode can be around the sliding surface in a finite time by the control law. Moreover, the chattering phenomenon created in the discontinuous control law can be eliminated by the proposed approach. Simulation results for a bipedal walking robot system demonstrate the feasibility and efficiency of the introduced design. Furthermore, it is noteworthy that the developed approach can be widely applied to many kinds of underactuated nonlinear control problem.
    Keywords: nonlinear underactuated systems; PI sliding surfaces; finite time stable; bipedal walking robots; chattering phenomenon.

  • Intelligent perturb and observe control based on support vector machine for photovoltaic pumping system   Order a copy of this article
    by Omar Dahhani, Ismail Boumhidi 
    Abstract: In this paper, an intelligent maximum power point tracking control is proposed for a photovoltaic (PV) water pumping system. This strategy combines the least squares support vector machines (LS-SVM) technique with the exponential adaptive perturb and observe (EAP&O) control. The reason in combining these two techniques is to overcome the steady states oscillations, low convergence rate as well as failure problems in standard P&O. The main purpose of the LS-SVM in this work, is to design an accurate off-line MPP model, which gives back the optimal value of duty cycle at present illumination intensity. These former values serve to initialise the proposed EAP&O in online implementation. To validate and to show the effectiveness of the proposed control, both strategies, EAP&O based on LS-SVM and standard P&O, are applied on the PV pumping system, and finally some important simulation results are presented.
    Keywords: adaptive perturb and observe ; MPPT ; support vector machine ; photovoltaic power system control.

  • Feature selection for detection of stroke risk using relief and classification method   Order a copy of this article
    by Yonglai Zhang, Yaojian Zhou, Wenai Song 
    Abstract: The morbidity of stroke presents an evident growing trend in the world. Stroke also features high disability rate and high recurrence rate. Therefore, the key of risk detection locates in preventing the stroke. This study mainly aims to find the way of selecting the most important influence factor in many features because of numerous risk factors of stroke. A new hybrid feature selection model is proposed based on a wrapper algrorithm. The most important features are extracted from the data. Afterwards, a classification model aiming at the ischemic stroke is established with the support vector machine and GSO (glow-worm swarm optimisation) algorithm for the risk detection of diseases. The result of the classification shows that our method displayed good performance in the detection of ischemic stroke. The new method can provide the technical support for the stroke screening of mass population, and establish a referable application framework for the prevention of cardiovascular disease.
    Keywords: machine learning; stroke; feature selection; relief; SVM.

  • Research on limited buffer scheduling problems in flexible flow shops with setup times   Order a copy of this article
    by Zhonghua Han, Quan Zhang, Haibo Shi, Yuanwei Qi, Liangliang Sun 
    Abstract: In order to solve the limited buffer scheduling problems in flexible flow shops with setup times, this paper proposes an improved whale optimisation algorithm (IWOA) as a global optimisation algorithm. Firstly, this paper presents a mathematical programming model for limited buffer in flexible flow shops with setup times, and applies the IWOA algorithm as the global optimisation algorithm. Based on the whale optimisation algorithm (WOA), the improved algorithm uses Levy flight, opposition-based learning strategy and simulated annealing to expand the search range, enhance the ability for jumping out of local extremum, and improve the continuous evolution of the algorithm. To verify the improvement of the proposed algorithm on the optimisation ability of the standard WOA, the IWOA is tested by verification examples of small-scale and large-scale flexible flow shop scheduling problems, and the imperialist competitive algorithm (ICA), bat algorithm (BA), and WOA are used for comparision. Based on the instance data of a bus manufacturer, simulation tests are made on the four algorithms under various practical evalucation scenarios. The simulation results show that the IWOA can better solve this type of limited buffer scheduling problem in flexible flow shops with setup times compared with the state-of-the-art algorithms.
    Keywords: limited buffer; improved whale optimisation algorithm; Levy flight; opposition-based learning strategy; simulated annealing; flexible flow shop.

  • A novel maximum likelihood based stochastic gradient algorithm for Hammerstein nonlinear systems with colored noise   Order a copy of this article
    by Yan Pu, Jing Chen 
    Abstract: This paper proposes a novel maximum likelihood based stochastic gradient algorithm for Hammerstein nonlinear systems with colored noise. The unknown noises in the information vector are replaced by their estimates, and then the parameters can be obtained by using the proposed algorithm through the noise estimates. Compared with the maximum likelihood based recursive least squares algorithm, the proposed algorithm has less computation burden. Furthermore, the performance of the proposed algorithm is analyzed and compared using a simulation example.
    Keywords: parameter estimation; stochastic gradient algorithm; recursive least squares algorithm; maximum likelihood; Hammerstein system.

  • A fast background model using kernel density estimation and distance transform   Order a copy of this article
    by Jian Zhao Cao, Ru Wei Ma, Oloro Michael Opeyemi 
    Abstract: Background modelling is a key factor for foreground detection, which is imperative for people-counting in a dynamic environment. In this paper, a background model with improved fast kernel density estimation technique while adopting distance transform is proposed for people-counting. The kernel density estimation background model is improved by an early-break method and LUT. Distance transform adopted is used to separate people who are close together as one blob. It has been tested in a 2.6 GHz Intel Core computer with 25 fps on 432
    Keywords: image processing; background model; kernel density estimation; distance transform; people counting.

  • Planing avoidance H-inf design for supercavitating vehicles   Order a copy of this article
    by Pang Aiping, He Zhen, Liu Minglei, Yang Jing 
    Abstract: For the planing forces generated when the aft end of an underwater high speed vehicle pierces the bubble which lead to oscillatory motion, planing avoidance control is designed based on observer and compensation in this paper. The effect of this compensation is related to the performance of the controller, and we consider controllers designed via the H-inf feedback control. The H-inf performance requirement which leads to the weight selection problem is analysed. Through the design of the H-inf weighted matrix, the controller that satisfies various performance requirements is obtained. Simulation results show that this H-inf state feedback controller, which inserts the compensating observer, can avoid the planing force generated. This method of H-inf weighting coefficients and the compensation method of the disturbance observer can also be a reference for other system designs as well.
    Keywords: supercavitating vehicles; planing avoidance; H-inf control; disturbance observer; compensation.

  • Analysis of estimator and energy consumption with multiple faults over a distributed integrated wireless sensor network   Order a copy of this article
    by Rui Wang, Xianyu Wang, Hui Sun, Yongtao Huang, Zengqiang Chen 
    Abstract: In this paper, based on an event-triggered mechanism, a new state estimation algorithm is proposed. According to the actual environment of the cabin, the algorithm considers the influence of path loss and packet loss on the algorithm, and can effectively monitor the pollutant concentration and save energy. The sufficient conditions for the stability of the algorithm are proved, and the influence of the triggered threshold on the energy consumption of the algorithm is analysed. Finally, the simulation proves that compared with the existing Kalman-Consensus filter, the proposed algorithm has stronger fault tolerance and lower energy consumption, and energy consumption and accuracy of the algorithm can be controlled by adjusting the triggered threshold according to actual needs.
    Keywords: estimation; packet loss; event-triggered ; stability analysis; energy consumption.

  • Fault monitoring and diagnosis of aerostat actuators based on PCA and state observer   Order a copy of this article
    by Guochang Zhang, Li Chen, Kuankuan Liang 
    Abstract: In order to solve the problem of actuator fault diagnosis for multi-propeller aerostats, this paper adopts the fault monitoring and diagnostic method that combines principal component analysis (PCA) and state observer. When the aerostat is running, the fault is detected in real time through the PCA method; once the fault occurs, the linearisation model of the system is obtained by the method of small disturbance linearisation, and the failure factor of the fault is further calculated by the state observer. Therefore, the location and severity of the fault are obtained. The simulation results show that the fault diagnosis method based on the combination of PCA and state observer can monitor and diagnose the failure of the aerostat actuator in real time.
    Keywords: aerostat; actuator; fault monitoring; fault diagnosis; PCA; state observer.

  • Design of set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers for quadcopter UAVs   Order a copy of this article
    by Ahmad Riyad Firdaus, M.O. Tokhi 
    Abstract: This research is to develop set-point weighting-based dynamic integral sliding mode control with nonlinear full-order state observers to deal with nonlinear and underactuated coupled systems, and unforeseen circumstances of quadcopter UAV systems. A comparative assessment through numerical simulations of sliding mode-based nonlinear observer approaches and Kalman filter is presented. These include quasi method, interval type-2 fuzzy logic system, super-twisting algorithm, higher order sliding mode observer, and extended Kalman filter. Chattering, noise rejection, estimation error and time required to track true states are evaluated to demonstrate the performance of each observer. In addition, to assess the proposed controller performance, maximum overshoot, rise time, chattering, and steady-state error are evaluated in relation to the use of each observer.
    Keywords: nonlinear systems; underactuated and coupled systems; integral dynamic sliding mode control; set-point weighting function; nonlinear full-order state observers.

  • An analytical study of the Vaidyanathan chaotic dynamics in Lorentzian metric that has no similar dynamics in Riemannian metric   Order a copy of this article
    by Najmeh Khajoei, MohammadReza Molaei 
    Abstract: In this paper, we investigate the behaviour at infinity of a physical $3$-dimensional chaotic system via the Poincare compactification method. This system has been introduced in Vaidyanathan et al. (2017). We plot the phase portrait of the system for parameters a and b, which appear in the nonlinear part of the system. We see that a set of non-isolated singular points at infinity is a hyperbolic set by considering a Lorentzian metric g on $mathbb{R}^2$, and it is not a hyperbolic set in the sense of Riemannian metrics. We compute a first integral for the resulting system and we prove there is at most a generalised rational first integral when one of its parameters is equal to zero.
    Keywords: Poincare compactification; hyperbolic set; Lorentzian metric; first integral; electronic systems.

  • Over-parameterisation and optimisation approaches for identification of nonlinear stochastic systems described by Hammerstein-Wiener models   Order a copy of this article
    by Saif Eddine Abouda, Mourad Elloumi, Yassine Koubaa, Abdessattar Chaari 
    Abstract: This paper proposes two iterative procedures based on over-parameterisation and optimisation approaches for identification of nonlinear systems that can be described by Hammerstein-Wiener stochastic models. In this case, the dynamic linear part of the considered system is described by the ARMAX mathematical model. The static nonlinear block is approximated by polynomial functions. The first procedure is based on a combination of the prediction error method by using the Recursive Approximated Maximum Likelihood (RAML) estimator, the Singular Value Decomposition (SVD) approach and the fuzzy techniques, in order to estimate the parameters of the considered process. As for the second procedure, it includes an appropriate representation named as Generalized Orthonormal Basis Filters (GOBF) in order to reduce the complexity of the considered system. The parametric estimation problem is formulated using the Recursive Extended Least Squares (RELS) algorithm incorporated with the SVD and fuzzy techniques, in order to segregate the coupled parameters and improve the estimation quality. The validity of the developed approaches is proved by considering a nonlinear hydraulic process simulation.
    Keywords: nonlinear stochastic systems; Hammerstein-Wiener models; ARMAX model; GOBF representation; parametric estimation; prediction error method, SVD approach; fuzzy technique; hydraulic process simulation.

  • Intelligent detection method for tapping omission of internal thread based on computer vision   Order a copy of this article
    by Wei Ding, Qingguo Wang, Yanfang Zhao 
    Abstract: Tapping
    Keywords: computer vision; tapping omission; interior thread; semantic recognition.

  • Thick restarted adaptive weighted block simpler GMRES algorithm   Order a copy of this article
    by Hongxiu Zhong, Guoliang Chen 
    Abstract: In this paper, an adaptive weighted block simpler GMRES algorithm is proposed for linear system with multiple right-hand sides, which can overcome the ill-conditioning difficulty of the basis generated by weighted block simpler GMRES algorithm. Moreover, a thick restarted adaptive weighted block simpler GMRES algorithm is presented to significantly reduce the products number of the matrix-vector and the consumed CPU time. Numerical examples illustrates the performance of our new algorithms.
    Keywords: linear system; Block GMRES; adaptive simpler GMRES; thick restarting.

  • A target classification method for unmanned surface vehicle based on extreme learning machines   Order a copy of this article
    by Defeng Wu, Kexin Yuan, Jiadong Gu, Honggui Lin 
    Abstract: In the process of autonomous navigation and obstacle avoidance of unmanned surface vehicles (USV), it is important for USVs to classify maritime targets correctly and effectively. In this paper, aiming at the recognition of surface targets for autonomous navigation of USVs, three kinds of targets are mainly considered, namely ships, buoys and islands. Visual sensors are installed on the USV to acquire visual images of maritime targets, and then the images are sent to the computer for automatic recognition. The invariant moments of three kinds of target images are extracted firstly, and target feature library will be built through image invariant moments, then an Extreme Learning Machine (ELM) based neural network is trained and then used to classify and recognize the sea targets. In addition, the sea targets are classified and analyzed by Adaboost-BP. The simulation results show that the ELM based classification method proposed in this paper has a better performance for maritime targets.
    Keywords: unmanned surface vehicles; visual system; extreme learning machine; target classification.

  • Using Self-constructing Recurrent Fuzzy Neural Networks for Identification of Nonlinear Dynamic Systems
    by Qinghai Li, Ye Lin, Rui-Chang Lin 
    Abstract: In this paper, the self-constructing recurrent fuzzy neural network (SCRFNN) is applied for nonlinear dynamical system identification (NDSI). The SCRFNN is a novel fuzzy neural network (FNN) by adding a recurrent path in each node of the hidden layer of self-constructing fuzzy neural network, which contains two learning phases. Specifically, the structure learning is based on partition of the input space and the parameter learning is based on the supervised gradient descent method using a delta adaptation law. This simple and efficient FNN can decreases the minimum firing strength in each learning cycle and the number of hidden neurons and is able to generate a FNN with high accuracy and compact structure compared with several other neural network. The performance of SCRFNN in NDSI is further verified in simulation.
    Keywords: Self-Constructing Recurrent Fuzzy Neural Network; Nonlinear Dynamic System Identification; Supervised Gradient Descent Method

  • An analytical approach for generating balanced gaits of a biped robot on stairs and sloping surfaces   Order a copy of this article
    by Ravi Kumar Mandava, Pandu R. Vundavilli 
    Abstract: The present paper deals with the generation of dynamically balanced walking gaits of a biped robot while moving on different terrain conditions, such as staircase and sloping surface. Here, an attempt is made to eliminate the complex inverse dynamics approach used to generate the gaits for the upper body by defining the trajectory for the movement of the hands and restricting the motion of the trunk. However, the restricted movement of the trunk is compensated by the movement of hands in the sagittal plane. The lower limbs gait has been generated by using the concept of inverse kinematics in both the sagittal and frontal planes. A provision is given in the algorithm to accommodate the variations in the dimension of the staircase and angle of slope of the terrain. Further, a study has also been conducted to investigate the influence of swing foot trajectory (that is, quadratic, cubic and fifth-order polynomial) on the balance of the robot. Once the model is developed, its performance has been benchmarked while ascending and descending the staircase and sloping surface after considering both the single and double support phases. Finally, the developed algorithms are tested on a real two-legged robot.
    Keywords: biped robot; staircase; sloping surface; zero moment point.

  • Vision-based leader follower approach for uncertain quadrotor dynamics using feedback linearisation sliding mode control   Order a copy of this article
    by Walid Kh. Alqaisi, Brahim Brahimi, Jawhar Ghommam, Maarouf Saad, Vahe Nerguizian 
    Abstract: In this paper, a leader-follower quadrotor based on a visual system is presented. It is assumed that the follower quadrotor is equipped with a single onboard camera for determining the position of the leader. In the following quadrotor, feedback linearisation based on sliding mode control is designed. The latter reduces complex nonlinear control solutions and highly coupled dynamic behaviour of the quadrotor. Uncertain dynamics and unexpected disturbances, such as the change of payload and wind variation, are overcome by designing a time delay estimation which helps in reducing chattering. The proposed controller uses a second order sliding mode exact differentiator to estimate the leader's velocity and acceleration. The effectiveness of the proposed system is analysed by Lyapunov function and studied by Matlab simulation.
    Keywords: leader-follower; feedback linearisation sliding mode control; quadrotor; second order sliding mode estimator; time delay estimation.

  • A biotech measurement scheme and software application for the level determination of person’s functional reserve based fuzzy logic rules
    by Riad Taha Al-kasasbeh, Nikolay Korenevskiy, Adnan Mukattash, Altin Aikeeva, Dmitry Titov, Maksim Jurievich Ilyash  
    Abstract: The level of person’s functional reserve is determined by number of different indicators such as power imbalance of meridian structures, psycho emotional tension, intellectual and physical exhaustion, parameters of pulse and arterial pressure at the impact of the dosed intellectual and physical activities on the base of heterogeneous fuzzy models usage. The functional reserve helps to diagnosis a lot of diseases. The theoretical results obtained in the form of fuzzy models are recommended in medical practice with cofficient of confidence at least 95%.
    Keywords: level of functional reserve, psycho emotional pressure, intellectual exhaustion, physical exhaustion, heterogeneous fuzzy models.

  • Front vehicle detection based on parallel BLOB detection using quad-pipeline on FPGAs   Order a copy of this article
    by Lin Meng 
    Abstract: Binary large object (BLOB) detection technology is widely used for front vehicle detection in intelligent transport systems, so achieving real-time detection is very important. This paper describes real-time BLOB and front vehicle detection using quad-pipeline image processing on FPGAs. The image processing consists of reading image data from BRAM, Gaussian filtering, binarization, labelling, and BLOB analysis. We propose simplified labeling to detect BLOBs in parallel. The image is divided into four parts, and two lines are temporarily labelled at first in parallel. Then, the four pipelines temporarily label each corresponding line in parallel. Connected information of temporarily labels between two neighbouring lines is kept in four look up tables (LUTs), and they are integrated into one. In simplified labelling, temporary labels are not revised, and connected labels are kept in a BLOB table. A system for front vehicle detection is implemented based on parallel BLOB detection using quad-pipeline. Tail lights are detected using two pipelines, and white lines are detected using the other two pipelines. If two red BLOBs of tail lights are detected between the two white line BLOBs, we can determine a vehicle is up ahead. The experimental results showed that the quad-pipeline system can detect BLOBs in 31.6 us on Virtex-5, which is 3.55 times and 1.83 times faster than the single-pipeline system and the dual-pipeline one, respectively. The quad-pipeline system can detect a vehicle up ahead in 124.8 us on Artix7, which is 1.91 times faster than the dual-pipeline one. Thus, parallel BLOB detection and front vehicle detection have a nearly linear speedup in the quad-pipeline system.
    Keywords: BLOB detection; front vehicle detection; quad-pipeline; simplified labeling; Scalability.

  • Identification of Nonlinear Systems Having Discontinuous Nonlinearity
    by Adil Brouri 
    Abstract: This paper deals with the identification of nonlinear systems. Presently, the nonlinear system is described by Wiener model. The linear element is nonparametric and may be of unknown structure. The nonlinear part is allowed to be discontinuous or of hard type and, noninvertible. A two-stage identification method is developed to get a set of points of the nonlinear part and estimates of the linear dynamic element. This method is based on simple geometric analysis and involves easily generated excitation signals.
    Keywords: Nonlinear systems; Nonlinear systems identification; Discontinuous nonlinearity; Nonparametric linear block; Hard nonlinearity; Wiener systems.

  • U-model enhanced MIMO decoupling control of thickness and plate type of cold rolling temper mill
    by Pengwei Li, Weicun Zhang 
    Abstract: This paper presents a new design procedure for control of thickness and plate type of cold rolling temper mill. A novel concept for control system design —U-model based design methodology with expanded Multi-Input and Multi-Output (MIMO) formulation for this application makes separation of specifying closed loop performance-controller from process models. Contrast to classical and methodologies, this takes two parallel formations, 1) designs an invariant virtual controller with specified closed loop transfer function in a feedback control loop, 2) determines real controller output by resolving the inverse of the plant U-model. Further, this study analyses some of the associated properties for assurance and guidance for ongoing theoretical development and applications. To validate the design procedure, it takes several computational experiments to generate simulation results, the bench tests show off efficiency and effectiveness of the proposed MIMO U-model based control system design.
    Keywords: cold rolling temper mill; plate type, plate thickness; U-model; U-control; model independent control system design

  • Thermal stress deformation prediction for rotary air-preheater rotor using deep learning approach   Order a copy of this article
    by Jing Xin, Rong Yu, Ding Liu, Youmin Zhang 
    Abstract: Failures often occur in the seal clearance measuring sensor due to the harsh operating conditions of the rotary air-preheater in power plant boilers. Therefore, it is necessary to predict the rotor deformation to eliminate the effects of failures on the gap control system. An air-preheater rotor thermal stress deformation prediction method is proposed in this paper based on deep learning. Firstly, a stacked auto-encoder (SAE) is constructed and trained to learn the feature information which is hidden within the input data (the temperature of flue gas side inlet, air side outlet, flue gas side outlet, air side inlet); then, an Elman neural network is constructed and trained using the output of the encoder part of the well trained stacked auto-encoder to predict rotor deformation. Simulation and experimental results show that the proposed SAE-Elman prediction method can obtain the effective feature representation and has better prediction precision compared with other traditional prediction methods.
    Keywords: deep learning; stacked auto-encoder; SAE; Yadvendra SAE-Elman; rotary air-preheater; thermal stress deformation prediction.
    DOI: 10.1504/IJMIC.2019.10021206
     
  • D-stability of parameter-dependent linear systems including discretisation by Taylor series expansion and search in a scalar parameter   Order a copy of this article
    by Marco Aurélio Carvalho Leandro, Karl Heinz Kienitz 
    Abstract: This work addresses the allocation of closed-loop poles of a discretised system from a continuous-time one with varying parameters, aiming at its control through a computer. It proposes a sufficient condition for an allocating state feedback with parameter-dependent gain. The condition is verified through a feasibility test of a set of linear matrix inequalities (LMIs), based on the existence of a homogeneous polynomially parameter-dependent Lyapunov function of arbitrary degree. The main contribution of this work is the guarantee of the continuous-time system's stability and simultaneously the allocation of the closed-loop poles of the discretised system in a D-stable region. In order to allow this, the discretised model is formed by homogeneous polynomial matrices of arbitrary degree, augmented by an additive norm-bounded term, which represents the discretisation residual error. Numerical examples show a larger number of feasible cases associated with the proposed condition in comparison with the condition based on a parameter-independent gain.
    Keywords: Robust control; D-stability; discrete-time linear systems; parameter-dependent state feedback; linear matrix inequalities.
    DOI: 10.1504/IJMIC.2019.10021186
     
  • Complete synchronisation of supply chain system using adaptive integral sliding mode control method   Order a copy of this article
    by Hamed Tirandaz 
    Abstract: In this paper, the synchronisation problem of supply chain system (SCS) is addressed with active and adaptive integral sliding mode controlling method. Active integral sliding mode synchronisation is performed for two identical supply chain systems by assuming that all parameters of the systems are known. When the internal and external distortion parameters of the system are considered unknown, an appropriate feedback controller is developed based on the adaptive integral sliding mode control mechanism to synchronise two identical supply chain chaotic systems and to estimate the unknown parameters of the systems. The stability evaluation of the synchronisation methods is performed by the Lyapunov stability theorem. In addition, the performance evaluation of the designed controllers and the theoretical analysis are verified by some illustrative numerical simulations. Simulation results indicate excellent convergence from both speed and accuracy points of view.
    Keywords: supply chain system; SCS; integral sliding mode control; active control; adaptive control.
    DOI: 10.1504/IJMIC.2019.10021185
     
  • Feedback control of bilinear distributed parameter system by input-output linearisation   Order a copy of this article
    by Nouara Habrache, Ahmed Maidi, Jean-Pierre Corriou 
    Abstract: In this paper, a control law that enforces the tracking of a boundary controlled output for a bilinear distributed parameter system is developed in the framework of geometric control. The dynamic behaviour of the system is described by two weakly coupled linear hyperbolic partial differential equations. The stability of the resulting closed-loop system is investigated based on eigenvalues of the spatial operator of a weakly coupled system of balance equations. It is shown that, under some reasonable assumptions, the stability condition is related to the choice of the tuning parameter of the control law. The performance of the developed control law is demonstrated, through numerical simulation, in the case of a co-current heat exchanger. The control objective is to control the outlet cold fluid temperature by manipulating its velocity. Both tracking and disturbance rejection problems are considered.
    Keywords: partial differential equation; bilinear distributed parameter system; geometric control; characteristic index; exponential stability; co-current heat exchanger; input-output linearisation.
    DOI: 10.1504/IJMIC.2019.10021187
     
  • Stochastic gradient-based particle filtering method for ARX models with nonlinear communication output submodel   Order a copy of this article
    by Jianxia Feng, Donglei Lu 
    Abstract: This paper develops a stochastic gradient-based modified particle filter algorithm for an auto regressivee xogenous (ARX) model with nonlinear communication output submodel. The outputs of the ARX model are transmitted over a nonlinear communication network, while the outputs of the communication network are available. Based on the modified particle filter and the available outputs, the outputs of the ARX model can be computed, and then the unknown parameters can be estimated by the stochastic gradient algorithm. The simulation results demonstrate that the stochastic gradient-based particle filter algorithm is effective.
    Keywords: system identification; stochastic gradient; particle filter; missing outputs; auto regressivee xogenous; ARX model.
    DOI: 10.1504/IJMIC.2019.10021205
     
  • Output feedback nonlinear control of power system under large penetration of renewable energy sources   Order a copy of this article
    by Hassan El Fadil, Abdelhafid Yahya, Mustapha Oulcaid, Leila Ammeh, Fouad Giri 
    Abstract: This paper deals with the problem of stability analysis and controlling a power system in which a synchronous generator and renewable energy sources supply the power to an infinite bus. Firstly the investigation of the existence of the equilibrium points of the system and their stability is presented. For this problem, we derive a sufficient condition on the renewable energy current for the existence of the equilibrium points. In addition, we analyse the stability of the equilibrium points, and show that there is only one equilibrium points which is stable. These results clarify the impact of the penetration of renewable energy sources on the existence of the stable equilibrium points of the system. Secondly, the focus is made on elaborating an output feedback controller, combining a state observer and a nonlinear control law that stabilises the closed loop system whatever the current of renewable energy sources. Numerical simulations are given in order to show the effectiveness of all theoretical results.
    Keywords: power system; renewable energy; stability analysis; nonlinear control; nonlinear observer; output feedback control.
    DOI: 10.1504/IJMIC.2019.10021207
     
  • Research on the control algorithms of human-thinking simulated control   Order a copy of this article
    by Peijin Wang 
    Abstract: Human-thinking simulated control according to the human cognition and human control thinking mechanism was first proposed many years ago. Human control thinking includes image intuitive reasoning control thinking, abstract logical inference control thinking and inspiration inference control thinking. The methods of simulating the image intuitive reasoning control thinking and the abstract logical inference control thinking are discussed in this paper. Some cases studies prove that the methods are better for simulating human control thinking and the test results are better than that of traditional control methods.
    Keywords: human-thinking; intelligent control; control thinking; human-thinking simulated control.
    DOI: 10.1504/IJMIC.2019.10021210
     
  • A nonlinear coupled-variables model for mass transfer modes in MIG-MAG processes with experimental validation   Order a copy of this article
    by Paulo Jefferson Dias De Oliveira Evald, Jusoan Lang Mór, Rodrigo Zelir Azzolin, Silvia Silva Da Costa Botelho 
    Abstract: Welding processes have relevant importance in many areas of industry, especially in the manufacturing area. The choice of mass transfer mode, to weld metal plates, depends on workpiece structure and its sensibility to the heat input and necessity for material deposition rate. Then, aiming at the mass transfer modes in metal inert gas-metal active gas (MIG-MAG) processes utilising pure CO2 as shielding gas, the objective of this paper is to present a detailed mathematical modelling for globular and short-circuit transfer modes. The proposed models cover a large set of process dynamics, approximating the simulated dynamics very closely to the physical process, which give a high level of credibility for the models. Furthermore, simulations and experimental data are presented to corroborate the validation of both models.
    Keywords: nonlinear systems; time-varying systems; coupled-parameters systems; uncertain systems; gas metal arc welding process; GMAW.
    DOI: 10.1504/IJMIC.2019.10021188
     
  • On the renovation and analysis of high order sliding mode approaches with application to robotic systems   Order a copy of this article
    by Fatma Abdelhedi, Nabil Derbel 
    Abstract: Variable structure control (VSC) approaches have been widely used to study nonlinear or ill-defined systems. While sliding mode methods can enhance the system robustness, a chattering phenomenon degrades system performances. In order to reduce this phenomenon appearing on the control law, several concepts have been proposed, particularly those called high order sliding mode (HOSM) approaches. In this paper, a renovated theorem of HOSM based on high order procedures has been presented, aiming to improve and to simplify the implementation of HOSM controllers. As the stability of dynamical systems is a fundamental requirement for its practical value, an original proposal for developing general forms of the Lyapunov equation matrices has been demonstrated for high orders of sliding modes, which are essential for the HOSM stability analysis-based Lyapunov theory. Simulation results present control comparisons between motion control behaviours of a robotic system controlled by the proposed HOSM approaches.
    Keywords: variable structure systems; sliding mode control; high order sliding mode control; HOSM; chattering phenomenon; disturbances; robotic systems.
    DOI: 10.1504/IJMIC.2019.10021212
     

Special Issue on: ICEE2015 Signals and System Modelling, Design and Simulation

  • Protection of 25 kV electrified railway system   Order a copy of this article
    by Farid Achouri, Imed Eddine Achouri, Mabrouk Khemliche 
    Abstract: Improving a reliability of electrified railway operation system requires protection against overvoltage, particularly those of atmospheric origin. The most serious threat to the traction system is lightning when it strike the mast or conductors. The ZnO arresters are used to protect a system from this phenomenon. In the present investigation the system under study is developed and each element is represented by a model corresponding in EMTP program and some elements are modelled using the Models section in ATP EMTP. The protective effect of the surge arrester and discharge current that passes through it is analysed and discussed in case lightning strikes a mast. The simulation results have shown that the surge arrester reduces overvoltage in primary power transformer traction below the basic insulation level under critical conditions.
    Keywords: railway traction network; overvoltage; lightning; surge arrester ZnO.

Special Issue on: ISMIC 2018 Data-driven Modelling and Intelligent Computation

  • Parameter estimation algorithm for d-step time delay systems   Order a copy of this article
    by Ya Gu, Peiyi Zhu, Xiangli Li, Jianfei Gu 
    Abstract: This article proposes the methods of parameter estimation and state estimation to calculate state space systems with delay. Associating the properties of linear conversion and shift operators, the state space model can be equal to the standard state space model, which can then be converted into the recognition model. The proposed stochastic gradient method is brought to calculate the system and converge to the recursive least squares estimates for state space models. Finally, one example is proposed to certify the theorems of this paper.
    Keywords: state estimation; stochastic gradient algorithm; time delay.

  • The investigation of an improved ultrasonic tomography reconstruction method for bubble particle identification   Order a copy of this article
    by Jianfei Gu, Jicheng Liu, Yongxin Chou 
    Abstract: To improve the accuracy of particle image reconstruction, a new image reconstruction method, Improved Binary Back Projection Algorithm using Triangular-criteria (IBBPAT) for in-line Ultrasound Processing Tomography (UPT), is presented. An ultrasonic transducer array consisting of eight transducers working as both transmitters and receivers, and 16 ultrasonic transducers working only as receivers, is adopted in the simulation. The transducers that also function as transmitters emit fan-shaped ultrasonic waves. Based on Multiphysics software (COMSOL Inc., Palo Alto, CA), signals scattering a cylindrical wave by different distribution of bubble particles are simulated. The results are entered in to IBBPAT for bubble reconstruction, and then the position and size of each bubble particle are accurately reconstructed. As indicated by the final results, Spatial Image Error (SIE) of IBBPAT is clearly less than that of Binary Back Projection Algorithm (BBPA).
    Keywords: particle image reconstruction; ultrasound processing tomography; binary back projection algorithm; numerical simulation.

  • Human behaviour recognition algorithm based on improved DMM and Fisher coding   Order a copy of this article
    by Feng Wei, Zhang Jiliang, Peng Li 
    Abstract: Human behaviour recognition has become a key technology in intelligent sensing, location and tracking tasks. In view of the different speed of action execution and DMM loss of time dimension information, this paper proposes a human action recognition method based on improved DMM and Fisher coding. First, in consideration of the different action speeds of long and short video, this paper adopts two different video segmentation strategies. Second, in order to make video-based DMM contain more time dimension information, this paper proposes an improved DMM; then, in order to better express the texture information of the image, this paper improves the extraction of LBP features by DMM. Finally, owing to the different feature lengths and high dimensions obtained by the long and short video, this paper adopts the Fisher vector for feature encoding and combines SVM to complete the action recognition. In the public action recognition database MSRAction3D and gesture recognition database MSRGesture3D, the accuracy rate of the algorithm is 96.25% and 96.00%, respectively, and it has higher recognition rate than many existing algorithms.
    Keywords: human behavior recognition; depth motion map; video segmentation; Fisher coding.

  • Online soft sensing method based on improved weighted Gaussian model   Order a copy of this article
    by Che Xiaoqing, Xiong Weili 
    Abstract: Aiming at the problems of delay, nonlinearity and multi-mode and noise pollution in chemical processes, a novel soft-sensor modelling method based on improved weighted Gaussian model is proposed. The moving gray relational analysis method is used to extract the process delay information, and the modelling dataset is reconstructed to improve the accuracy of the model. The cumulative similarity factor is introduced into the selection rules of the model training set to improve the real-time performance of the model. When the new query sample arrives, an adaptive similarity threshold is used to determine criteria of updating local model of the current operating point, so as to reduce the model update frequency. The improved modelling method is applied to the debutaniser column process. The simulation results show that the model has high precision and real-time performance.
    Keywords: variable time delay; moving gray relational analysis; weighted Gaussian model; cumulative similarity factor.

  • Multi-mode process monitoring based on multi-block information extraction PCA method with Local neighborhood standardisation   Order a copy of this article
    by Bingbin Gu, Weili Xiong 
    Abstract: In order to solve the problem of multi-mode process data in complex industrial processes, a multi-mode industrial process fault monitoring method based on multi-block information extraction PCA with local neighborhood standardisation is proposed. Firstly, define the cumulative observation information and rate of change information of the process variable. Then extract the two kinds of information from the existing observation information, and obtain the data sub-blocks of the three kinds of information. Secondly, the three data sets are separately standardised by the local neighborhood standardisation method. Next the Puata criteria are employed to eliminate singular points. Accordingly, three PCA models were built based on the three information datasets obtained, and each PCA model will get a monitoring result. Finally, the Bayesian inference method is used to fuse the results of the three models to obtain a final BIC monitoring index. The effectiveness and feasibility of the proposed method are proved by a numerical example and applications in Tennessee-Eastman (TE) process monitoring.
    Keywords: principal component analysis; information extraction; multi-block modelling; multi-mode process; local neighborhood standardization.

  • Research on reconfigurable control for a hovering PVTOL aircraft   Order a copy of this article
    by Xinli Xu, Chunwei Zhang, Huosheng Hu 
    Abstract: This paper presents a novel reconfigurable control method for the planar vertical take-off and landing (PVTOL) aircraft when actuator faults occur. According to the position subsystem within the multivariable coupling, and the series between subsystems of position and attitude, a active disturbance rejection controller (ADRC) is used to counteract the adverse effects when actuator faults occur. The controller is cascade and ensures the input value of the controlled system can be tracked accurately. The coordinate transformation method is used for model decoupling due to the severe coupling. In addition, the Taylor differentiator is designed to improve the control precision based on the detailed research for tracking differentiator. The stability and safety of the aircraft is much improved in the event of actuator faults. Finally, the simulation results are given to show the effectiveness and performance of the developed method.
    Keywords: reconfigurable control; PVTOL; ADRC; coordinate transformation; actuator faults; Taylor differentiator.

  • Multi-innovation parameter and state estimation for multivariable state space systems   Order a copy of this article
    by Xuehai Wang, Fang Zhu, Fenglin Huang 
    Abstract: This work considers the modelling and estimation problem of multivariable state space systems. Based on the observer canonical form, the identification model is derived and a combined state and multi-innovation estimation algorithm is presented by means of the Kalman filter principle. The efficacy of the algorithm is verified by a simulation example.
    Keywords: multi-innovation; multivariable system; Kalman filter.

  • Research on passivity-based control strategy of three-phase current source inverter based on interconnection and damping assignment   Order a copy of this article
    by Shuo Zhan, Jing Bai, Chao Chao Li, Lin Yue 
    Abstract: In view of the facts that switching frequency of the high power current source inverter (CSI) is limited and the load parameter of the system is variable, and moreover the performance of output is affected, an interconnection and damping assignment of passivity-based control (IDA-PBC) for a three-phase CSI is proposed. The lumped-parameter model of the three-phase CSI with independent storage unit is established, and its port-controlled Hamilton (PCH) model in Park coordinate is proposed. The control rate of the closed-loop system is obtained by solving the parametric partial differential equation based on interconnection and damping assignment. The controller is designed, and the stability of system is analysed by Lyapunov function. The simulation and experiment results show that the inverter can output a good sinusoidal voltage, which has strong anti-interference ability to the load disturbance. The stability and robustness of the system are also improved.
    Keywords: current source inverter; port-controlled Hamiltonian system; interconnection and damping assignment; passivity-based control.

  • The gradient and the Newton iterative modelling methods for an operational amplifier circuit   Order a copy of this article
    by Ling Xu 
    Abstract: In order to provide a new method to identify the mathematical model of circuit systems, this paper studies modelling methods by combining the iterative strategy with the nonlinear optimisation. When we analyse a complicated circuit, we only need to find the relationship between the input and the output and do not need to concern the specific components, which can be solved by system identification. With this purpose, this paper develops iterative modelling methods to construct the transfer function for an amplifier circuit system that can be described by the transfer function model of a first-order inertial system. For obtaining the transfer function model, the impulse response observed data are employed to design the objective function regarding the time constant and the gain of the first-order inertial system. In light of the nonlinear characteristic of the system output, the gradient optimisation and the Newton optimisation are adopted to minimise the objective function. Finally, the simulation experiment is carried out to test the performance of the developed modelling methods.
    Keywords: parameter estimation; iterative identification; gradient optimisation; Newton optimisation; transfer function.

  • A modified model decomposition identification for bilinear-in-parameter systems   Order a copy of this article
    by Huibo Chen, Jiangbo Fan, Jing Li 
    Abstract: The so-called bilinear-in-parameter models are usually derived from the block-oriented nonlinear models and identified by different methods. Inspired by the model decomposition-based identification technique, this paper develops a recursive least squares algorithm to estimate the model parameters and obtain a global convergence, as shown by a simulation example.
    Keywords: identification; bilinear model; least squares.

  • Steady flight of miniature fixed-wing unmanned aerial vehicle flocking by using biological algorithm   Order a copy of this article
    by Yongnan Jia, Qing Li, Weicun Zhang 
    Abstract: This paper focuses on solving the cohesive flocking problem from the biological point of view. Twelve variables are adopted to draw the kinematic characteristics of the fixed-wing UAV. A weighted and undirected graph is applied to describe the time-variant and distance-related interaction relationship among the UAVs. Based on the proposed model and the communication mechanism, a distributed cooperation approach is designed to force groups of miniature fixed-wing UAVs to be capable of collaboratively accomplishing a predefined task like a flock of birds. During the evolutionary process, there are three constraint conditions to be considered. The first one is that each UAV flies under a small roll angle and a small pitch angle. Second, one forward speed is necessary for the flight of each fixed-wing UAV. The last constraint condition is that the shorter the adjustment time, the better within the error margin of steady-state value. Three constraint conditions are skillfully taken as evaluation criteria to determine the communication network's coupling strength. Numerical simulations are provided to validate the feasibility of the proposed approach.
    Keywords: steady flight; fixed-wing unmanned aerial vehicle; cohesive flocking; biological algorithm.

  • Sensor fault signal reconstruction based on sliding mode observer for flight control systems   Order a copy of this article
    by Rui Wang, Chengjie Wang, Hui Sun, Zengqiang Chen, Yigang Sun 
    Abstract: The sensor-fault detection for linear systems with bounded unknown input disturbance is investigated in this paper. By non-singular linear transformation, the sensor-faults are converted equivalently into actuator failures. The residual generation is proposed, which is robust to disturbance and sensitive to sensor faults. A sliding mode observer is further designed to give the estimation of residuals. The sensor faults can be detected and reconstructed by using the estimation of residuals. For typical sensor failure modes, the simulation results about the longitudinal model of the aircraft show the effectiveness of the proposed method.
    Keywords: sensor fault; sliding mode observer; fault detection; signal reconstruction.

  • Recursive least squares algorithm and stochastic gradient algorithm for feedback nonlinear equation-error systems   Order a copy of this article
    by Guanglei Song, Ling Xu, Feng Ding 
    Abstract: Many industrial systems exhibit nonlinear characteristics. Generally, the structure of the system is taken by feedback closed-loop for the purpose of realising the automatic control of industrial process. Therefore, industrial systems are closed-loop feedback nonlinear systems with complicated structures. The mathematical models of systems provide the support and basis for the design of the control system and the better control performance. However, it is hard to determine the models of closed-loop feedback nonlinear systems owing to the complex structures. The goal of this study is to develop an identification way for a feedback nonlinear system including a forward channel and a feedback channel, where the forward channel is described by a controlled autoregressive model and the feedback channel takes the form of a static nonlinear function. By taking advantage of the least squares optimisation, a recursive least squares algorithm is established and shows its good performance to solve the identification problem for the feedback nonlinear system.
    Keywords: parameter estimation; recursive identification; least squares; stochastic gradient; nonlinear system; feedback system.

  • Modelling arterial blood pressure waveforms for extreme bradycardia and tachycardia by curve fitting with Gaussian functions   Order a copy of this article
    by Yongxin Chou, Ya Gu, Jicheng Liu, Xufeng Huang, Jiajun Lin 
    Abstract: Arterial blood pressure (ABP) signal contains abundant information about heart beat rhythm and hemodynamic changes which can be employed to predict bradycardia and tachycardia. Thus, a waveforms modelling method based on curve fitting is proposed to extract some significant difference between bradycardia and tachycardia. First, the ABP signal is pre-processed and is split into a series of single-period waveforms. Then, a single-period ABP waveform model is proposed to describe the change of linear trend and waveform, and a nonlinear least squares method is employed to compute the parameters of the model. The bradycardia and tachycardia data from 2015 PhysioNet/CinC Challenge are engaged as experimental data. The results show that there are significant differences for many of the model parameters between bradycardia and tachycardia.
    Keywords: arterial blood pressure; curve fitting; modelling; bradycardia; tachycardia.