International Journal of Modelling, Identification and Control (42 papers in press)
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
Adaptive neural networks for AC voltage sensorless control of three-phase PWM rectifiers
by Adel Rahoui, Hamid Sediki, Ali Bechouche, Djaffar Ould Abdeslam
Abstract: In this paper, a new adaptive grid voltages estimator for AC voltage sensorless control of three-phase pulse-width modulation (PWM) rectifier is proposed. The proposed method is based on a simple adaptive neural network (ANN) to estimate online the grid voltages. The main advantage of this method is its simplicity and it requires low computational cost. The ANN estimator is inserted in voltage-oriented control (VOC) to perform an AC voltage sensorless control scheme. During the startup process, the proposed ANN estimator is also used for estimating initial values of the grid voltages. For accurate estimation, adaptive neural filters (ANFs)-based pre-filtering stage of the input voltages and AC-line currents is added. Experimental tests are carried out to verify the feasibility and robustness of the proposed ANN estimator. Experimental results show good performances of the proposed AC voltage sensorless control scheme in normal and severe grid voltage conditions.
Keywords: adaptive neural network; adaptive neural filter; pulse-width modulation rectifier; diode rectifier; grid voltages estimation; voltage-oriented control; sensorless control; startup process; experimental verification; stability.
Complete synchronisation of supply chain system using adaptive integral sliding mode control method
by Hamed Tirandaz
Abstract: In this paper, the synchronisation problem of supply chain chaotic system is carried out 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; integral sliding mode control; active control; adaptive control.
D-stability of parameter-dependent linear systems including discretization by Taylor series expansion and search in a scalar parameter.
by Marco Aurelio Leandro, Karl Kienitz
Abstract: This work addresses the allocation of the 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 to 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.
Feedback control of bilinear distributed parameter system by input-output linearization
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 balanced 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.
A non-linear coupled-variables model for mass transfer modes in MIG-MAG processes with experimental validation
by Paulo Evald, Jusoan Mór, Rodrigo Azzolin, Silvia 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 MIG-MAG (Metal Inert Gas - Metal Active Gas) processes using 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 comprehend 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: non-linear systems; time-varying systems; coupled-parameters systems; uncertain systems; gas metal arc welding process.
Robust adaptive sliding mode control technique for combination synchronisation of non-identical time-delay chaotic systems
by Shikha , Ayub Khan
Abstract: This manuscript presents the methodology in which a robust adaptive sliding mode control technique is used for implementing combination synchronisation of non-identical time-delay chaotic systems. To justify this methodology, a modified Lorenz chaotic time-delay system and a Genesio time-delay system are used. The stability condition for the error dynamics is analysed using Lyapunov stability theory and detailed mathematical theory. Numerical simulations are carried out to demonstrate the efficiency of the proposed approach that supports the analytical results.
Keywords: time-delay chaotic system; combination synchronisation; robust adaptive sliding mode control; Lyapunov stability theory.
Towards a unified stability analysis of continuous-time T-S model based fuzzy control systems
by Weicun Zhang
Abstract: This paper is intended to develop a unified stability analysis framework for a general closed-loop continuous-time T-S model based fuzzy control (TSFC) system, which consists of the parallel distributed compensation (PDC) controller and the real plant instead of the T-S fuzzy model. The plant to be controlled may be a linear time-invariant, linear parameter jump, or nonlinear time-varying system. As an alternative to Lyapunov function based approach, virtual equivalent system (VES) approach is introduced. The stability of a TSFC system is identical to that of the corresponding VES.
Keywords: T-S model based fuzzy control; stability; virtual equivalent system.
Robust mixed performance for uncertain Takagi-Sugeno fuzzy time-delay systems with linear fractional perturbations
by Chang-Hua Lien, Sundarapandian Vaidyanathan, Ker-Wei Yu, Hao-Chin Chang
Abstract: The robust mixed H2/Hinf. performance for Takagi-Sugeno (T-S) fuzzy systems with time delay and linear fractional perturbations is considered in this paper. Some delay-dependent conditions have been proposed to guarantee the mixed performance of uncertain fuzzy time-delay systems. The LMI optimisation approach is used to find the minimisation of performance measure. Some numerical simulations are illustrated to show the significant improvement over some previous results.
Keywords: mixed H2/Hinf. performance; Takagi-Sugeno fuzzy systems; time delay; linear fractional perturbations.
Iterative linear quadratic regulator control for quadrotors leader-follower formation flight
by Wesam Jasim, Dongbing Gu
Abstract: This paper presents an iterative linear quadratic regulator optimal control technique to solve the problem of quadrotor leader-follower formation. The dynamic motion equations are represented based on unit quaternion representation and include some modelled aerodynamical effects as a nonlinear part. Simulation results prove the ability and effectiveness of iLQR controller to successfully track different paths by the leader and maintain the relative distance between the leader and the follower by the follower. It also shows that iLQR controller outperforms LQR controller in terms of fast convergence and tracking errors.
Keywords: iLQR controller; LQR controller; optimal control; leader-follower formation; unit quaternion; UAV quadrotors.
Adaptive backstepping control of multi-mobile manipulators handling a rigid object in coordination
by Abdelkrim Brahmi, Maarouf Saad, Guy Gauthier, Wen-Hong Zhu, Jawhar Ghommam
Abstract: This paper presents an adaptive backstepping control scheme applied to a group of mobile manipulator robots transporting a rigid object in coordination. All the dynamic parameters of the robotic system, including the handled object and the mobile manipulators, are assumed to be unknown but constant. The problem of uncertain parameters is resolved by using the virtual decomposition approach (VDC). This approach was originally applied to multiple manipulator robot systems. In this paper, the VDC approach is combined with backstepping control to ensure a good position tracking. The controller developed in this work ensures that the position error in the workspace converges to zero, and that the internal force error is bounded. The global stability of the entire system is proven based on the appropriate choice of Lyapunov function using virtual stability of each subsystem, based on the principle of the virtual work. An experimental validation is carried out for two mobile manipulators moving a rigid object in order to show the effectiveness of the proposed approach.
Keywords: backstepping control; adaptive control; virtual decomposition approach; multiple mobile manipulator robots.
Accuracy control in Monte Carlo simulations of particle breakage
by Jherna Devi, Gregor Kotalczyk, Einar Kruis
Abstract: Monte Carlo (MC) methods are an important tool for the numerical solution of the population balance equation, allowing the optimisation and control of particulate processes on laboratory or plant scales. We investigate in this work a family of MC methods for particle breakage proposed by Kotalczyk et al., Powder Technology (2017), 317, pp. 417-429. The authors reported that specific breakage schemes (defined by a combination factor R) allow to render the full particle size distribution. They also showed that specific ranges of the combination factor R might lead to severe systematic errors, but did not investigate measures of control or prevention. In this paper, a strategy which allows to estimate the magnitude of the systematic error from the simulation data is presented. It is also shown how the simulation parameters can be set in order to keep the systematic error at an acceptable level.
Keywords: Monte Carlo; population balance; weighted particles; simulation; GPU; breakage; optimisation; control.
H performance of continuous switched time-delay systems with sector and norm bounded nonlinearities
by Chang-Hua Lien, Sundarapandian Vaidyanathan, Ker-Wei Yu, Hao-Chin Chang
Abstract: In this paper, the exponential stabilisation and H∞ performance analysis for switched systems with time-varying interval delay and multiple nonlinearities by switching rule design are considered. H∞ performance is guaranteed by the proposed LMI delay-dependent criteria via the selection of the switching rule. The selected scheme of switching rule is developed to improve the difficulty for the generalisation of the proposed main results. Finally, some examples are presented to show the reduced conservativeness of our developed results.
Keywords: H∞ performance; Park inequality; switched system; selection of switching rule; time-varying interval delay; sector bounded nonlinearities; norm bounded nonlinearities.
Comparision of Hybrid Path Planning Approaches for Vehicles in 3D Non-Deterministic Environments
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 structures have been defined. In the first type of systems, 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 synthesized 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
NARMAX model identification using a randomised approach
by Pedro Retes
Abstract: Structure selection is one of the most critical steps in nonlinear system identification. A large family of methods, based on model prediction error, uses concepts and tools from linear algebra. Other methods, based on model simulation error, have to deal with non-convex optimisation problems. More recently a family of methods has ben put forward that has probabilistic setting. The Randomized algorithm for Model Structure Selection (RaMSS) belongs to this family and it has been shown to be effective to select regressors for NARX models. In the present paper, such a method is extended to cope with NARMAX models. The performance of the proposed method is illustrated using simulated and experimental data. It is shown that the proposed method is capable of correctly selecting model structures from simulation data. The method was also applied to experimental data with successful results.
Keywords: NARMAX; non-linear models; ELS; OLS; RaMSS; NARX; system identification; parameter estimation.
Modelling of gene signal attribute reduction based on neighbourhood granulation and rough approximation
by Jian Xue, Fu Liu, Jing Bai, Tao Hou
Abstract: The update of high-throughput sequencing technology has led to the dramatic increase in the number of sequenced meta-genomic DNA sequences. However, extracting a nearly 10,000-dimensional digital signature as a species tag will inevitably bring about tremendous computational load. Therefore, how to reduce the macro features of macro-genomic DNA and how to extract and select the subset with the best characteristics as a species tag has become a research direction of bio-informatics. In this paper, we use neighbourhood granulation and rough approximation theory modelling to study the method of attribute reduction of meta-genomic DNA fragments and to deduce the digital features of meta-genome at the 'genus' classification. The results show that this method can effectively screen out representative species tags and improve classification efficiency.
Keywords: meta genomics; attribute reduction; neighborhood rough set; species classification; K-mer frequency.
On Peng's type maximum principle for optimal control of mean-field stochastic differential equations with jump processes
by Shahlar Meherrem, Mokhtar Hafayed, Syed Abbas
Abstract: In this paper, we investigate the Peng's type optimal control problems for stochastic differential equations of mean-field type with jump processes. The coefficients of the system contains not only the state process but also its marginal distribution through their expected values. We assume that the control set is a general open set that is not necessary convex. The control variable is allowed to enter into both diffusion and jump terms. We extend the maximum principle of Buckdahn et al. (Appl Math. Optim. 64(2), 197-216, 2011) to jump case.
Keywords: mean-field jump systems; stochastic optimal control; Peng's maximum principle; spike variation method; second-order adjoint equation; Poisson martingale measure.
Optimal torque vectoring control for distributed drive electric vehicle
by Wei Xu, Zhijun Fu, Weidong Xie, Anqing He, Yong Xiao, Bin Li
Abstract: A novel optimal torque vectoring control (TVC) strategy is proposed in this paper to enhance the lateral stability of a dual-motor rear-wheel drive electric vehicle. The structure of the optimal TVC consists of three parts, i.e. pre-processor, model-following controller and post-processor. Unlike the commonly used linear single track vehicle model, an accurate nonlinear vehicle model is built in the pre-processor based on the Magic Formula tyre model. The model-following controller is responsible for producing the corrective yaw moment by a two-dimensional gain scheduling method related to the vehicle longitudinal velocity and lateral acceleration. This optimal yaw moment controller, consisting of the steady-state control law and the optimal feedback control law, is developed to compensate the nonlinear property induced by time-varying tyre cornering stiffness. In the post processor, torque vectoring allocation strategies are presented considering the constraints of motor peak torque and tyre friction. Co-simulation results of the CarSim and LabVIEW under two driving manoeuvres (step steering and skid pad track) illustrate that the lateral and longitudinal performance of the vehicle is greatly improved and experimental results of hardware-in-the-loop (HIL) proves that the control system can be well used in real-time.
Keywords: optimal control; torque vectoring; lateral stability; Magic Formula; co-simulation; HIL.
An improved energy-aware and self-adaptive deployment method for autonomous underwater vehicles
by Chunlai Peng, Tao Wang
Abstract: Autonomous underwater vehicles (AUVs) are special mobile robots travelling underwater and perform dangerous tasks for humans in unknown mission areas. However, there are two critical issues when deploying AUVs. First, these algorithms do not optimise the travelling distances of AUVs and hence will lead to excessive energy depletion. Second, these deployment models rarely consider the available energy variations among AUVs in the task execution process. For this reason, an energy-aware and self-adaptive deployment method is presented for a group of AUVs taking collaborative tasks. First, the movement priority of AUVs is considered according to their positions during the deployment process. Second, an improved virtual force algorithm is proposed to obtain the initial deployment scheme. In addition, a self-adaptive deployment strategy is presented for redeploying the AUVs when the available energy of some AUVs has fallen below a certain threshold. Simulation results with 10 AUVs demonstrate that the proposed method greatly decreases energy consumption (evaluated by the movement distances of AUVs) by about 30% than its traditional counterpart and it can redeploy AUVs adaptively and rapidly.
Keywords: autonomous underwater vehicles; Voronoi diagram; energy-awareness; self-adaptive deployment; unknown environment.
Stabilisation of time delay systems with nonlinear disturbances using sliding mode control
by Adrian E. Onyeka, Xing-Gang Yan, Zehui Mao, Jianqiu Mu
Abstract: This paper focuses on a class of control systems with time delay states and time delay nonlinear disturbances using sliding mode techniques. Both matched and mismatched uncertainties are considered, which are assumed to be bounded by known nonlinear functions. The bounds are used in the control design and analysis to enhance robustness. A sliding function is designed and a set of sufficient conditions is derived to guarantee the asymptotic stability of the corresponding sliding motion by using the Lyapunov-Razumikhin approach, which allows large time-varying delay with fast changing rate. A delay-dependent sliding mode control is synthesised to drive the system to the sliding surface in finite time and maintain a sliding motion thereafter. Effectiveness of the proposed method is demonstrated via a case study on a continuous stirred tank reactor system.
Keywords: stabilisation; sliding mode control; time delay; uncertain systems; Lyapunov-Razumikhin approach.
Coupling vibration analysis of the elastics structure with liquid
by Jin Yan
Abstract: The equations of the structure motions are accomplished in terms of the displacement form, and the liquid formulations are expressed by pressure, with or without considering the effect of sloshing. The unknown coefficients in the two domains are expanded into velocity potential and vibration functions by the Galerkins method. The coupled vibration of the elastics baffle with two sides fluid, in a rigid tank, is also carried out by finite element method (FEM), which regards the structure and fluid element global degrees of freedoms as row index and column index, and the coupled matrix is assembled to the global matrix. Finally, the coupled frequencies of simple supported beam and liquid are computed, which are in good agreement with the FEM results. The effects of the liquid filling height and beam flexibility on the slosh response are also investigated. The baffles with two sides fluid vibration numerical results by the proposed FEM, are compared with the test example, which agree well.
Keywords: elastics structure; liquid; coupling vibration; Galerkins method; free surface; FEM.
Stochastic gradient-based particle filtering method for ARX models with nonlinear communication output submodel
by Jianxia Feng, Donglei Lu
Abstract: This paper develops a stochastic gradient-based modified particle filter algorithm for a AutoRegressive eXogenous (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; ARX model.
Thermal stress deformation prediction for rotary air-preheater rotor using deep learning approach
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 that 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; rotary air-preheater; thermal stress deformation predicti.
Output feedback nonlinear control of power system under large penetration of renewable energy sources
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 are 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 point that 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 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.
Research on the control algorithms of human-thinking simulated control
by Peijin Wang
Abstract: Human-thinking simulated control was first proposed according to the human cognition and human control thinking mechanism 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 case studies prove that the methods are better for simulating human control thinking and the test results are better than those of traditional control methods.
Keywords: human thinking; intelligent control; control thinking; human-thinking simulated control.
On the renovation and analysis of high order sliding mode approaches with application to robotic systems
by Fatma Abdelhedi
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 is 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 is 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 approach; high order sliding mode approach;
chattering phenomenon; disturbances; robotic systems.
Survey and tutorial on multiple model methodologies in modelling, identification and control
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
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
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
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
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
by Abdelhak GOUDJIL, Mathieu Pouliquen, Eric pigeon, Olivier Gehan
Abstract: This paper discusses an online switched linear systems identification algorithm\r\nbased 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 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
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
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
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
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 optimization algorithm (IWOA) as a global optimization algorithm. Firstly, this paper presents a mathematic programming model for limited buffer in flexible flow shops with setup times, and applies the IWOA algorithm as the global optimization algorithm. Based on the whale optimization 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 optimization ability of the standard WOA algorithm, the IWOA algorithm 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 whale optimization algorithm (WOA) are used for comparision. Based on the instance data of bus manufacturer, simulation tests are made on the four algorithms under variouis of practical evalucation scenarios. The simulation results show that the IWOA algorithm 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 optimization algorithm (IWOA); 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
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
by Jian Zhao Cao, Ru Wei Ma, Oloro Michael Opeyemi
Abstract: Background modeling 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 are proposed for people counting. The kernel density estimation background model is improved by early-break method and LUT. Distance transform adopted is used to separate people who are closed together as one blob. It has been tested in a 2.6GHz Intel Core computer with 25fps on 432×240 images without code optimization. The result shows that the improved method can be used in real-time processing and has a good result.
Keywords: image processing;background model;kernel density estimation;distance transform;people counting
PLANING AVOIDANCE H-inf DESIGN FOR SUPERCAVITATING VEHCICLES
by pang aiping, he zhen, Liu minglei, yang jing
Abstract: For the planing forces generated when the underwater high speed vehicles aft end pierces the bubble which lead to oscillatory motion, planning avoidance control was designed based on observer and compensation in this paper. The effect of this compensation is related to the performance of the controller, we consider controllers designed via the H-inf feedback control. In the paper, the H-inf performance requirement which lead to the weight selection problem was analyzed aslo. 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 inserting the compensating observer can avoid the planing force genrated. This method of H-inf weighting coefficients and the compensation method of the disturbance observer can also be a reference for other system design as well.
Keywords: Supercavitating vehicles; Planning avoidance; H-inf control; Disturbance observer;Compensation.
Analysis of Estimator and Energy Consumption With Multiple Faults Over the Distributed Integrated WSN
by Rui Wang, Xianyu Wang, Hui Sun, Yongtao Huang, Zengqiang Chen
Abstract: In this paper, based on 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 have been proved in this paper, and the influence of the triggered threshold on the energy consumption of the algorithm is analyzed. Finally, the simulation proves that compared with the existed 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
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 linearization model of the system is obtained by the method of small disturbance linearization, 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 principal component analysis 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
Special Issue on: ICEE2015 Signals and System Modelling, Design and Simulation
Protection of 25kV Electrified railway system
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 modeled using the Models section in ATP EMTP. Protective effect of the surge arrester and discharge current which passes through it is analyzed and discussed in case lightning strikes a mast. The simulation results have shown that the surge arrester reduce overvoltage in primary power transformer traction below the Basic Insulation Level BIL, under critical conditions.
Keywords: Railway traction network; Overvoltage; Lightning; Modelling; Simulation; Surge arrester ZnO.