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Observer-based fuzzy feedback control for nonlinear systems subject to transmission signal quantization

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  • Chang, Xiao-Heng
  • Jin, Xue

Abstract

This paper investigates the observer-based quantized output feedback control for a kind of nonlinear discrete-time systems. The system studied in this paper is denoted by a Takagi–Sugeno (T–S) fuzzy model. Under digital communication channels, all transmitted signals between the system and the actuator (including the controller and the observer) will be quantized by the dynamic quantizers in the closed-loop system. Taking into consideration the design of the controller, observer, and dynamic parameters of quantizers, an effective matrix inequality decoupling method is presented to handle the problem. One is shown that the proposed design conditions of the controller, observer, dynamic parameters of quantizers are summarized in a matrix inequality, which can be synthesized synchronously. The resulting design ensures that the quantized closed-loop system can meet the prescribed H∞ performance. Finally, the availability and the feasibility of the presented design method are demonstrated by a mechanical motion system.

Suggested Citation

  • Chang, Xiao-Heng & Jin, Xue, 2022. "Observer-based fuzzy feedback control for nonlinear systems subject to transmission signal quantization," Applied Mathematics and Computation, Elsevier, vol. 414(C).
    • Handle: RePEc:eee:apmaco:v:414:y:2022:i:c:s0096300321007414
    DOI: 10.1016/j.amc.2021.126657
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    Cited by:

    1. Zhu, Hao-Yang & Jiang, Xiaoyue & Li, Yuan-Xin & Tong, Shaocheng, 2023. "Finite-time adaptive fuzzy output tracking of switched nonlinear systems with ISD-ADT," Applied Mathematics and Computation, Elsevier, vol. 443(C).
    2. Xu, Ziqiang & Li, Yun & Zhan, Xisheng & Yan, Huaicheng & Han, Yiyan, 2024. "Time-varying formation of uncertain nonlinear multi-agent systems via adaptive feedback control approach with event-triggered impulsive estimator," Applied Mathematics and Computation, Elsevier, vol. 475(C).
    3. Zou, Ying & Deng, Chao & Dong, Lu & Ding, Lei & Lu, Ming, 2022. "Distributed output feedback consensus tracking control of multiple nonholonomic mobile robots with only position information of leader," Applied Mathematics and Computation, Elsevier, vol. 422(C).
    4. Zhimin Li & Chengming Lu & Hongyu Wang, 2023. "Non-Fragile Fuzzy Tracking Control for Nonlinear Networked Systems with Dynamic Quantization and Randomly Occurring Gain Variations," Mathematics, MDPI, vol. 11(5), pages 1-20, February.
    5. Harshavarthini, S. & Kwon, O.M. & Lee, S.M., 2022. "Uncertainty and disturbance estimator-based resilient tracking control design for fuzzy semi-Markovian jump systems," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    6. Mathiyalagan, K. & Nidhi, A. Shree & Su, H. & Renugadevi, T., 2022. "Observer and boundary output feedback control for coupled ODE-transport PDE," Applied Mathematics and Computation, Elsevier, vol. 426(C).
    7. Zhu, Lin & Che, Wei-Wei & Jin, Xiao-Zheng, 2022. "Dynamic event-triggered tracking control for model-free networked control systems," Applied Mathematics and Computation, Elsevier, vol. 431(C).
    8. Sorin Lugojan & Loredana Ciurdariu & Eugenia Grecu, 2022. "Chenciner Bifurcation Presenting a Further Degree of Degeneration," Mathematics, MDPI, vol. 10(9), pages 1-17, May.
    9. Chen, Xiang & Li, Shi & Wang, Ronghao & Xiang, Zhengrong, 2023. "Event-Triggered output feedback adaptive control for nonlinear switched interconnected systems with unknown control coefficients," Applied Mathematics and Computation, Elsevier, vol. 445(C).
    10. Hu, Yifan & Liu, Wenhui & Liu, Guobao, 2022. "Adaptive finite‐time event‐triggered control for uncertain nonlinearly parameterized systems with unknown control direction and actuator failures," Applied Mathematics and Computation, Elsevier, vol. 435(C).
    11. Jiao, Ticao & Qi, Xiaomei & Jiang, Jishun & Yu, Mingzheng, 2022. "Noise-input-to-state stability analysis of switching stochastic nonlinear systems with mode-dependent multiple impulses," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    12. Chen, Qi-Xin & Chang, Xiao-Heng, 2022. "Resilient filter of nonlinear network systems with dynamic event-triggered mechanism and hybrid cyber attack," Applied Mathematics and Computation, Elsevier, vol. 434(C).
    13. Ma, Yong-Sheng & Che, Wei-Wei & Deng, Chao, 2022. "Observer-Based fuzzy containment control for nonlinear networked mass under dos attacks," Applied Mathematics and Computation, Elsevier, vol. 421(C).
    14. Zhang, Ning & Qi, Wenhai & Pang, Guocheng & Cheng, Jun & Shi, Kaibo, 2022. "Observer-based sliding mode control for fuzzy stochastic switching systems with deception attacks," Applied Mathematics and Computation, Elsevier, vol. 427(C).
    15. Saravanan Shanmugam & Rajarathinam Vadivel & Nallappan Gunasekaran, 2023. "Finite-Time Synchronization of Quantized Markovian-Jump Time-Varying Delayed Neural Networks via an Event-Triggered Control Scheme under Actuator Saturation," Mathematics, MDPI, vol. 11(10), pages 1-24, May.
    16. Ren, Yingying & Ding, Da-Wei & Long, Yue, 2023. "Finite-frequency fixed-order dynamic output-feedback control via a homogeneous polynomially parameter-dependent technique," Applied Mathematics and Computation, Elsevier, vol. 441(C).
    17. Ma, Yan & Zhang, Zhenzhen & Yang, Li & Chen, Hao & Zhang, Yihao, 2022. "A resilient optimized dynamic event-triggered mechanism on networked control system with switching behavior under mixed attacks," Applied Mathematics and Computation, Elsevier, vol. 430(C).

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