International Journal of Modelling, Identification and Control (13 papers in press)

Regular Issues

• Outlier detection algorithm based on deviation characteristic  
  by Yong Wang, Hongbin Wang, Pengcheng Sun, Xinliang Yin 
  Abstract: Outlier mining focuses on researching rare events through detection and analysis to dig out the valuable knowledge from them. In the static data set environment, the traditional LOF algorithm calculates the local outlier factor through the whole data set and requires a lot of computing time. To solve this problem, the algorithm divides the data space into grids, and calculates the local outlier factor based on the centroids of the grids. Since the grid number is less than data point number, the time complexity is obviously reduced under acceptable error. When the new data points are added, it can rapidly detect outliers. The contrast experiment results show that the new algorithm can reduce the computation time and improve the efficiency, while achieving comparable accuracy.
  Keywords: outlier detection; local outlier factor; deviation characteristic; fast LOF detection algorithm.
  
  
• Mathematical model for impact of awareness of COVID-19 vaccination among the youth of Kenya  
  by Ancent Makau Kimulu, Abayomi Samuel Oke, Mark Kimathi, Charles Ndambuki Muli, Samuel Musili Mwalili, Winifred Nduku Mutuku 
  Abstract: Approximately 124 million cases of COVID-19 infections have been confirmed; with over 2.7 million deaths globally. Vaccines have been developed to control and contain the spread of COVID-19. However, due to the combined effects of misinformation and unawareness about the vaccines, 52% of the Kenyan youths (aged 18-35 years) are hesitantly waiting to see what happens to the vaccinated. As a result, this study models the effects of awareness on vaccine uptake among the youths in Kenya through the use of televisions, radios and social media platforms. The disease-free equilibrium (DFE) point and endemic equilibrium point of the model are obtained by setting the derivatives to zero. The reproduction number are determined by using the next-generation matrix. The condition for stability of the DFE is shown in relation to the reproduction number. The DFE was stable when the reproduction number R_0 < 1 and unstable when R_0 > 1. It is found that both means of awareness reduced the COVID-19 infections. A simultaneous use of the methods increases the number of Kenyan youths taking the COVID-19 vaccines and consequently, further reducing the number of infections among the youths.
  Keywords: COVID-19; next-generation matrix; coronavirus; awareness; vaccination.
  DOI: 10.1504/IJMIC.2023.10058163
   
  
• Intrusion detection using a SV-SMOTE method in IoMT  
  by Yonglai Zhang 
  Abstract: Intrusion detection for the internet of medical things (IoMT) is particularly important because of the problem of network attacks. Network security has become more serious during the COVID-19 pandemic. To address the problem that edge servers in IoMT are vulnerable to network traffic attacks, we propose a SV-SMOTE oversampling algorithm, and construct an IoMT intrusion detection model with machine learning algorithms as the main body. Using a benchmark dataset of network attacks, the random forest, oversampling and XGBoost algorithms are used in the proposed model for intrusion detection comparison experiments, respectively. This study makes a significant research contribution by proposing a new methodological approach to unbalanced data sets, which can lead to improved performance of classification models. The experimental results show that the proposed method can effectively detect network traffic attacks.
  Keywords: SV-SMOTE; random forest; XGBoost; internet of medical things; IoMT; intrusion detection.
  DOI: 10.1504/IJMIC.2023.10055523
   
  
• Upgradation of the automatic voltage regulator dynamic response by an optimally tuned fractional order controller  
  by Manjusha Silas, Surekha Bhusnur 
  Abstract: The performance of an automatic voltage regulator (AVR) system is of prime importance in the power system. This work contributes a significant approach to enhance the performance of an AVR system using a fractional order PID (F OP ID
  Keywords: AVR system; (F OP IλDµ) controller; optimiser algorithm; robust control; cost Function.
  DOI: 10.1504/IJMIC.2023.10055524
   
  
• Boundary control for prescribed-time stabilization of delayed parabolic reaction-diffusion systems  
  by Qian Ye, Wei Wu 
  Abstract: This work addresses the boundary control problem for prescribed-time stabilization of a parabolic reaction-diffusion system (PRDS) with time delay via the backstepping-based approach and Razumikhin method. The invertible Volterra transformation is used to convert the PRDS into a suitable prescribed-time stable PRDS with time-dependent coefficient, which is related to time-dependent kernel function. The obtained kernel partial differential equations are proven to be well-posed using the successive approximation. The boundary controller is designed by solving the kernel equations to guarantee the prescribed-time stabilization of the delayed PRDS. Finally, two numerical examples are given to testify the feasibility of the proposed methodology.
  Keywords: reaction-diffusion system; distributed parameter system; boundary control; time delay; prescribed-time stabilization; backstepping approach; Razumikhin method.
  DOI: 10.1504/IJMIC.2023.10055802
   
  
• Interval observer-based fault-tolerant control for discrete-time switched linear system  
  by Leila Dadi, Haifa Ethabet, Mohamed Aoun 
  Abstract: This work presents the problem of interval estimation and passive Faut Tolerant Control (FTC) for discrete-time Switched Linear Systems (SLS). The considered systems are affected by disturbances, measurement noises and actuator faults. The uncertainties are supposed to be unknown but bounded with a priori known bounds. Based on a state feedback, a FTC is designed to maintain desired performances and preserve stability conditions in presence of actuator faults. The control law is designed by means of interval observer structure, guaranteeing interval estimation, where the stability conditions are expressed in terms of Linear Matrix Inequalities (LMIs). Numerical simulations are provided to demonstrate the efficiency of the proposed method.
  Keywords: fault tolerant control; actuator fault; discrete-time switched systems; hybrid systems.
  DOI: 10.1504/IJMIC.2023.10055999
   
  
• Distributed set-membership state estimation based on a zonotope method for linear parameter-varying systems  
  by Yanfei Zhu, Jiahao Yu, Chuanjiang Li, Ya Gu 
  Abstract: This paper considers the distributed set-membership state estimation (SMSE) issue for linear parameter-varying (LPV) systems with unknown but bounded (UBB) noise and disturbance. A distributed set-membership estimation method employing zonotopes has been presented to estimate the true states of the systems. The estimated errors are restricted to a family of zonotopes satisfying the dependent constraint condition. By using the F-radius of the zonotopes minimum theory, the appropriate estimators are designed and the corresponding parameters are computed. Furthermore, a recursive state estimation algorithm is introduced to address this research issue. The persuasiveness of the approach can be demonstrated through numerical simulation examples.
  Keywords: distributed set-membership estimation; unknown but bounded noise; zonotope-dependent constraint.
  DOI: 10.1504/IJMIC.2023.10056513
   
  
• Coyote optimisation algorithm for separable nonlinear models using chaotic maps technique  
  by Xixi Ji, Jing Chen, Xia Yin 
  Abstract: In this paper, a new Chebyshev chaotic map-based chaotic coyote optimization algorithm (CCOA) is applied to identify a separable nonlinear model. The CCOA uses chaotic signals instead of random numbers in identification process to increase non-repetitiveness and ergodicity. Compared with the particle swarm optimisation (PSO) and coyote optimisation algorithm (COA), the CCOA algorithm can improve the estimation accuracy and increase the parameter estimation convergence rate. Thus, the proposed algorithm can be widely used in engineering practices. To validate the developed algorithm, a series of comparative experiments are conducted. The effectiveness of the proposed algorithm is verified by the simulation results.
  Keywords: chaotic coyote optimisation algorithm; chaotic signal; separable nonlinear model; parameter estimation.
  DOI: 10.1504/IJMIC.2023.10057075
   
  
• Capacity optimisation of rural distributed energy system based on two-stage robust optimisation algorithm  
  by Juan Wang, Sirui Wang, Fengzhong Zhang, Xueyang Sun 
  Abstract: In order to improve the energy utilisation of rural waste, a rural distributed energy system including wind energy, photovoltaic energy, biogas energy and energy storage is proposed in this paper. The capacity of the rural distributed energy system is optimised based on the two-stage robust optimisation model. The annualised life cycle cost, the differentiated time-of-use electricity price, as well as the discrete wind turbine capacity allocation has been considered in the two-stage robust optimisation model. The results show that this distributed energy system, including wind energy, photovoltaic energy, biogas energy and energy storage, is suitable for rural energy distributed systems, it has excellent multi-energy complementary characteristics, which leads to a high utilisation rate of renewable energy. The capacity configuration without scheduling capacity can be calculated directly by the two-stage robust optimisation model. The uncertainty on the source and load side can be fully considered in the two-stage robust optimisation model, and it has excellent economy and security in the
  Keywords: distributed energy; biogas power generation; two-stage robust optimisation; uncertainty.
  DOI: 10.1504/IJMIC.2023.10057523
   
  
• Multi-discriminant feature fall detection algorithm based on joints  
  by Jimin Lai, Tonghui He 
  Abstract: Traditional fall detection algorithm is difficult to accurately extract and recognise human posture features, and easy to lose feature joints in the process of falling, resulting in low detection accuracy. Therefore, this paper proposes a multi-discriminant feature fall detection algorithm based on joints for nursing homes, medical rehabilitation centres and other places. Firstly, the initial features of human posture are obtained by the improved VGG-19 feature extraction model, and the initial position of the joints are obtained and coded by adding a residual module. Secondly, the decoder network is used to complete deconvolution and upsampling operations to achieve greater fine-grained resolution. Finally, the image pose refinement module is designed to analyse the relationship between different adjacent feature nodes, so as to realise the accurate identification of the node position when the fall occurs. On this basis, the corresponding fall discriminant characteristics are proposed to achieve the detection of the elderly fall action. The results show that the proposed algorithm is more accurate and effective than other traditional algorithms on some datasets.
  Keywords: fall detection; convolutional neural network; residual module.
  DOI: 10.1504/IJMIC.2023.10058394
   
  
• A new nonlinear PID controller design for a quadrotor system using teaching learning based optimisation algorithm  
  by Naima Bouhabza, Kara Kamel 
  Abstract: In this paper, a novel nonlinear proportional integral derivative controller based on the meta-heuristic optimisation technique is suggested. Owing to its straightforward implementation and structure, the proportional integral derivative controller is frequently employed in nonlinear system control. The teaching-learning-based optimisation algorithm, owing to its effectiveness, rapidity, and minimum initialisation parameter required, has gained the attention of a significant number of researchers. The quadrotor's actuation dynamics are controlled by nonlinear proportional integral derivative controllers. Moreover, under-actuated dynamics use the same controller mechanism. For each controller, six parameters are tuned using the integral time absolute error criteria. Through numerical simulation, the efficiency and control performance of the suggested scheme are proven and contrasted with those of the linear proportional integral derivative controller and the sliding mode control. The simulation research demonstrates the effectiveness and successful performance of the recommended control technique in terms of the transient response characteristics, tracking precision, and perturbation rejection.
  Keywords: quadrotor; teaching learning based optimisation; TLBO; optimisation; nonlinear PID control.
  DOI: 10.1504/IJMIC.2023.10058548
   
  
• A network control system for solving a speed coordination problem in a networked multi-motor drive  
  by Huang Jiexian, Suhaib Masroor, Zain Anwar Ali 
  Abstract: A control system connected to a sensor and actuator via communication network plays a pivotal role in a today's world. The problem of obtaining a consensus in a group of network-connected agents is one of the major areas of research in the network control systems. In industry, the multi-motor system is very demanding owing to a common load driven capacity, and cost saving. Coordinated speed plays a vital role to control the in-flight movement of multi-rotor UAV/drones, producing hovering, tilting or other necessary flight control movements. Thus, this study uses a leaderless multi-agent consensus model to achieve coordinated control of network-connected motor drives such that all the drives reach identical speeds. Moreover, this study also incorporates event-based control, so that the continuous time controller update can be avoided, thus offering energy saving. To ensure stable system design, the Lyapunov stability criterion is used, while the obtained design is simulated in MATLAB. The simulated results endorse the design concept, such that the system attains a consensus on motor speed along with energy saving.
  Keywords: network control system; NCS; leaderless multi-agent system; event-based consensus; networked multi-motor system.
  DOI: 10.1504/IJMIC.2023.10060804
   
  
• Design of MIMO fractional order fault tolerant control based on intelligent QFT controller of robotic manipulator  
  by Najah Yousfi, Asma Aribi, Awadh Aljuaid 
  Abstract: High level of technological development in our life makes systems increasingly complicated. In consequence, a possibly unexpected failures happen caused by sensor and actuator faults. Control systems that ensure safety, reliability and maintainability are being challenging tasks in order to remedy the problems caused by unexpected faults. The quantitative feedback theory (QFT) is an efficient control method used for MIMO systems with parametric uncertainties. On the other side, the well-known robust fractional PID controller and fractional prefilter are demonstrated their efficiency to ensure robust control and to guarantee performance specifications. The novelty in this work consists on associating the benefits of fractional control and the QFT approach to develop a fractional tolerant controller for MIMO systems. A new Fractional Fault Tolerant Controller (FFTC) with some special characteristics allowing to overcome the design complexity and control effort increase due to simultaneous presence of disturbance with jumping faults is developed. Additionally, high tracking performance is taken into consideration.
  Keywords: Evolutionary algorithms; Fault tolerant control; Fractional control; Multi criteria optimization; Quantitative feedback theory; Robotic systems.
  DOI: 10.1504/IJMIC.2023.10061572