Article
Computer Science, Artificial Intelligence
Zhi-Min Li, Xiao-Heng Chang, Jun Xiong
Summary: This article investigates the problem of event-based output feedback tracking control for discrete-time nonlinear networked systems with dynamic quantization. The Takagi-Sugeno (T-S) fuzzy systems theory is utilized to approximate the investigated nonlinear systems. Three general dynamic quantizers and an improved asynchronous event-triggering communication scheme are carried out to decrease the amount of data in the communication of network and realize the rational utilization of limited communication resources. The objective is to design an event-based static output feedback tracking controller for achieving asymptotical stabilization and predefined tracking performance in the presence of dynamic quantization, and the parameters for the desired dynamic quantizers and tracking controller can be obtained simultaneously by solving a set of linear matrix inequalities. Finally, simulation responses are provided to demonstrate the validity of the proposed tracking control strategy.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Mathematics, Interdisciplinary Applications
Rajarathinam Vadivel, Porpattama Hammachukiattikul, Seralan Vinoth, Kantapon Chaisena, Nallappan Gunasekaran
Summary: This study presents an extended dissipative analysis of a fractional order fuzzy networked control system with uncertain parameters. A network-based fuzzy controller is designed for the model, and a new Lyapunov-Krasovskii functional approach, inequality techniques, and sufficient conditions are established to ensure quadratic stability under the extended dissipative criteria. The conditions are expressed as linear matrix inequalities (LMIs), and the controller gains are designed for larger sampling intervals. Two numerical examples are provided to demonstrate the viability of the obtained criteria.
FRACTAL AND FRACTIONAL
(2022)
Article
Computer Science, Artificial Intelligence
Qunxian Zheng, Shengyuan Xu, Baozhu Du
Summary: This article investigates the quantized guaranteed cost static output feedback control problem for a class of discrete-time nonlinear networked control systems using the Takagi-Sugeno fuzzy model and dynamic quantizers, introducing a novel guaranteed cost performance function and obtaining sufficient conditions through linear matrix inequalities.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Automation & Control Systems
Zhi-Min Li, Xiao-Heng Chang, Ju H. Park
Summary: This article studies the H-infinity static output feedback tracking control problem for discrete-time nonlinear networked systems subject to quantization effects and asynchronous event-triggered constraints, using the Takagi-Sugeno fuzzy model and a novel asynchronous event-triggered strategy. The goal is to design a quantized event-triggered tracking controller that ensures system stability and H-infinity tracking performance, with design conditions formulated as linear matrix inequalities (LMIs) and effectiveness demonstrated through simulation example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Bo Wu, Xiao-Heng Chang, Xudong Zhao
Summary: This article investigates H-infinity dynamic output feedback control for discrete-time nonlinear systems using Takagi-Sugeno rules and a fuzzy Markov jump model. It aims to design a controller to ensure stability and H-infinity performance, presenting design conditions in terms of linear matrix inequalities and providing simulation examples to verify the effectiveness of the proposed method.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2021)
Article
Computer Science, Information Systems
Han Sol Kim, Kwangil Lee
Summary: In this paper, a sampled-data fuzzy observer (SDFO) for oscillating nonlinear systems based on the Takagi-Sugeno (T-S) fuzzy-model based approach is proposed. An exponentially time-varying gain matrix is employed to enhance the decay rate performance of the state estimation error dynamics, and the design conditions are formulated in terms of linear matrix inequalities (LMIs). Simulation results demonstrate that the proposed method outperforms conventional studies in terms of state estimation performance.
INFORMATION SCIENCES
(2021)
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Mathematics, Applied
Yong-Sheng Ma, Wei-Wei Che, Chao Deng
Summary: This paper studies the observer-based fuzzy containment control problem of nonlinear networked multi-agent systems (MASs) under denial-of-service (DoS) attacks. The proposed method utilizes a fuzzy model and an observer design method to develop a resilient containment controller to counter DoS attacks. Simulation results demonstrate the effectiveness of the designed fuzzy observer and containment controller.
APPLIED MATHEMATICS AND COMPUTATION
(2022)
Article
Automation & Control Systems
Rodrigo Farias Araujo, Leonardo A. B. Torres, Reinaldo Martinez Palhares
Summary: This article addresses the design of nonlinear distributed control laws for continuous-time networked nonlinear heterogeneous systems with bounded sector nonlinear interconnections. New sufficient conditions are derived in terms of linear matrix inequalities, taking into account state constraints and actuators saturation, which can reduce conservatism over decentralized and linear distributed control laws derived following the same method. The closed-loop system can be made asymptotically stable while maximizing the estimate of the domain of attraction (DoA).
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Mathematics
Tawfik Guesmi, Badr M. Alshammari, Yosra Welhazi, Hsan Hadj Abdallah, Ahmed Toumi
Summary: This paper presents a new control technique based on uncertain fuzzy models for handling uncertainties in nonlinear dynamic systems. The proposed strategy is tested on a multimachine power system subject to disturbances, and the effectiveness of the suggested fuzzy controller is compared with conventional regulators.
Article
Automation & Control Systems
Yuechao Ma, Chuifeng Kong
Summary: This article discusses dissipative asynchronous Takagi-Sugeno-Kong fuzzy control for a type of singular semi-Markov jump system. An adjustable quantized approach is proposed to handle uncertainties, nonlinear disturbances, actuator faults, and time-varying delays. By utilizing an asynchronous method and designing a novel asynchronous sliding-mode controller, along with solving linear matrix inequalities, the sufficient conditions are obtained to ensure system performance and reachability of the sliding-mode surface.
IEEE TRANSACTIONS ON CYBERNETICS
(2022)
Article
Automation & Control Systems
Huiying Chen, Zuxin Li, Weifeng Xia, Renwei Liu
Summary: This article proposes a dissipative asynchronous filtering method for networked Takagi-Sugeno fuzzy Markov jumping systems subject to packet dropouts. It introduces a logarithmic quantizer for system measurements and a Bernoulli model for handling packet dropouts in the communication channel. Both the quantizer and the filter are mode dependent and governed by hidden Markov models. The article presents a condition for stochastically stable and strictly dissipative filtering error system using a Lyapunov function method and further designs suitable dissipative filters using the slack-matrix approach and Finsler's lemma if certain linear matrix inequalities are feasible. The efficiency of the proposed results is demonstrated through examples including a tunnel-diode circuit system.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2023)
Article
Automation & Control Systems
Basil Mohammed Al-Hadithi, Jose Miguel Adanez, Mayra Comina, Agustin Jimenez
Summary: In this work, a fuzzy predictive optimal control method is proposed for multivariable nonlinear systems with pure time delays. The method uses dynamic local linear state models obtained from fuzzy Takagi-Sugeno (T-S) modeling and observes the state using the Kalman Filter (KF). Compared to traditional Model Predictive Control (MPC) methods, the proposed approach calculates the control signal increment based on the error between a reference state vector and the prediction at N-steps of the state vector, resulting in computational savings and suitability for real-time applications.
IET CONTROL THEORY AND APPLICATIONS
(2022)
Article
Computer Science, Artificial Intelligence
Ting-Ting Pan, Xiao-Heng Chang, Yi Liu
Summary: This article studies the robust quantized feedback control problem for nonlinear discrete-time systems described by the T-S fuzzy model with norm-bounded uncertainties. An improved two-step design approach is proposed based on the LMI technique.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Jing Xu, Yugang Niu, Hak-Keung Lam
Summary: This article discusses the design of a control synthesis method for singularly perturbed nonlinear systems under a nonperiodic multirate sampling mechanism, and provides guidance on the choice of maximum allowable sampling time intervals for multirate sensors. The sampled system is converted into a fuzzy singularly perturbed model, and sufficient conditions for stabilizing the multirate sampled system are derived. A linear matrix inequality-based design method is proposed, and the upper bound of the perturbation parameter is determined to compute the maximum allowable sampling time interval for fast states. The optimal match is detected for a tradeoff among stability, performance, and cost. The obtained results are demonstrated in an example system.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Mathematics, Applied
Venkatesan Nithya, Rathinasamy Sakthivel, Fanchao Kong, Veeralpatti Thangavel Suveetha
Summary: This paper focuses on the problem of mixed H infinity and passivity-based filtering for networked nonlinear systems with randomly occurring parameter uncertainties, multipath data packet dropouts, time-varying delay, and quantization effects. It models the discrete-time nonlinear plant as a Takagi-Sugeno fuzzy system with plant rules. The paper considers both measurement and performance output signals affected by data missing phenomenon and employs measurement quantization to reduce network bandwidth utilization. It derives a set of sufficient conditions for stochastic stability of the filtering error system using Lyapunov stability theory. Numerical examples are provided to validate the developed filter design algorithm, including mass-spring-damper and tunnel diode circuit models.
MATHEMATICAL METHODS IN THE APPLIED SCIENCES
(2023)
Article
Automation & Control Systems
He Qiao, Zhi-Min Li, Xiao-Heng Chang
INTERNATIONAL JOURNAL OF FUZZY SYSTEMS
(2016)
Article
Mathematics, Applied
Zhi-Min Li, Xiao-Heng Chang, Lu Yu
APPLIED MATHEMATICS AND COMPUTATION
(2016)
Article
Computer Science, Artificial Intelligence
Zhi-Min Li, Xiao-Heng Chang, Xiao-Kun Du, Lu Yu
Article
Automation & Control Systems
Xiao-Heng Chang, Jun Xiong, Zhi-Min Li, Ju H. Park
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2018)
Article
Engineering, Multidisciplinary
Yifu Feng, Zhi-Min Li, Xiao-Heng Chang
MATHEMATICAL PROBLEMS IN ENGINEERING
(2017)
Article
Engineering, Electrical & Electronic
Zhi-Min Li, Xiao-Heng Chang, Kalidass Mathiyalagan, Jun Xiong
Article
Automation & Control Systems
Xiao-Heng Chang, Zhi-Min Li, Ju H. Park
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2018)
Article
Automation & Control Systems
Zhi-Min Li, Xiao-Heng Chang
Article
Automation & Control Systems
Zhi-Min Li, Jun Xiong
Summary: This article considers the H-infinity filtering issue for discrete-time nonlinear networked systems subject to event-triggered communication scheme, dynamic quantization, and stochastic cyber attacks. The Takagi-Sugeno (T-S) fuzzy model is used to describe the considered nonlinear networked system. The paper focuses on the design of event-triggered H-infinity filters and the dynamic parameter of the quantizer to achieve stochastic stability and predefined H-infinity filtering performance. The design conditions are proposed based on linear matrix inequalities (LMIs), and the effectiveness of the design methods is verified through a practical example.
Article
Automation & Control Systems
Zhi-Min Li, Xiao-Heng Chang, Ju H. Park
Summary: This article studies the H-infinity static output feedback tracking control problem for discrete-time nonlinear networked systems subject to quantization effects and asynchronous event-triggered constraints, using the Takagi-Sugeno fuzzy model and a novel asynchronous event-triggered strategy. The goal is to design a quantized event-triggered tracking controller that ensures system stability and H-infinity tracking performance, with design conditions formulated as linear matrix inequalities (LMIs) and effectiveness demonstrated through simulation example.
IEEE TRANSACTIONS ON SYSTEMS MAN CYBERNETICS-SYSTEMS
(2021)
Article
Computer Science, Artificial Intelligence
Zhi-Min Li, Xiao-Heng Chang, Jun Xiong
Summary: This article investigates the problem of event-based output feedback tracking control for discrete-time nonlinear networked systems with dynamic quantization. The Takagi-Sugeno (T-S) fuzzy systems theory is utilized to approximate the investigated nonlinear systems. Three general dynamic quantizers and an improved asynchronous event-triggering communication scheme are carried out to decrease the amount of data in the communication of network and realize the rational utilization of limited communication resources. The objective is to design an event-based static output feedback tracking controller for achieving asymptotical stabilization and predefined tracking performance in the presence of dynamic quantization, and the parameters for the desired dynamic quantizers and tracking controller can be obtained simultaneously by solving a set of linear matrix inequalities. Finally, simulation responses are provided to demonstrate the validity of the proposed tracking control strategy.
IEEE TRANSACTIONS ON FUZZY SYSTEMS
(2023)
Article
Engineering, Multidisciplinary
Jiasheng Song, Xiao-Heng Chang, Zhi-Min Li
Summary: The article focuses on solving the secure P2P nonfragile sampled-data controller design problem for a nonlinear networked system under sensor saturation and DoS attack, utilizing a T-S fuzzy model. A sampling scheme with two different sampling periods is introduced to combat DoS attacks, and a maximum control update interval is determined based on these sampling periods and the characteristics of the attacks. The article establishes P2P stability analysis criteria and proposes a new analysis condition of bounding region to ensure measurement output satisfies a given constraint condition under sensor saturation. A secure P2P nonfragile sampled-data control scheme is then provided to ensure the system meets control performance requirements in the presence of sensor saturation and DoS attack. An example is presented to illustrate the advantages of the proposed method.
IEEE TRANSACTIONS ON NETWORK SCIENCE AND ENGINEERING
(2023)
Article
Mathematics, Applied
Xiao-Heng Chang, Zhi-Min Li, Jun Xiong, Yi-Ming Wang
APPLIED MATHEMATICS AND COMPUTATION
(2017)
