Constrained model predictive control for T-S fuzzy system with randomly occurring actuator saturation and packet losses via PDC and non-PDC strategies

被引：0
|
作者：
Liu, Na [1 ]
Tang, Xiaoming [1 ]
Deng, Li [1 ]
机构：
[1] Chongqing Univ Posts & Telecommun, Minist Educ, Key Lab Ind Internet Things & Networked Control, Chongqing 400065, Peoples R China
来源：
TRANSACTIONS OF THE INSTITUTE OF MEASUREMENT AND CONTROL | 2020年 / 42卷 / 08期
基金：
中国国家自然科学基金;
关键词：
Actuator saturation; packet losses; model predictive control; fuzzy system; NETWORKED CONTROL-SYSTEMS; EVENT-TRIGGERED CONTROL; LINEAR-SYSTEMS; QUANTIZATION; DELAYS; STABILIZATION; DROPOUT;
D O I：
10.1177/0142331218803414
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
This paper studies model predictive control for a Takagi-Sugeno (T-S) fuzzy system with randomly occurring actuator saturation and packet losses. The nonlinearity of the actuator saturation is transformed into a set of convex hulls, while the packet losses are assumed to obey the rules of Bernoulli distribution. Both parallel-distributed-compensation (PDC) and non-parallel-distributed-compensation (non-PDC) strategies are adopted to design the controller for the system. In addition, sufficient conditions of the stability for the closed-loop system are given in terms of linear matrix inequalities. It is shown that the non-PDC strategy behaves less conservatively than the PDC strategy in controlling the considered T-S fuzzy system, when the input and output constraints are explicitly considered. Two simulation examples are provided to illustrate the effectiveness of the proposed design techniques.
引用
收藏
页码：1437 / 1447
页数：11
相关论文
共 37 条
  • [1] Robust stabilization of T-S fuzzy discrete systems with actuator saturation via PDC and non-PDC law
    Zhao, Ling
    Li, Li
    NEUROCOMPUTING, 2015, 168 : 418 - 426
  • [2] Model Predictive Control for T-S Fuzzy System with Random Actuator Saturation and Packet Losses
    Liu, Na
    Tang, Xiaoming
    Deng, Li
    Yang, Shuang
    2018 2ND INTERNATIONAL CONFERENCE ON ROBOTICS AND AUTOMATION SCIENCES (ICRAS), 2018, : 191 - 195
  • [3] Non-PDC Interval Type-2 Fuzzy Model Predictive Microclimate Control of a Greenhouse
    Hamza, Azzedine
    Ramdani, Messaoud
    JOURNAL OF CONTROL AUTOMATION AND ELECTRICAL SYSTEMS, 2020, 31 (01) : 62 - 72
  • [4] Non-PDC Interval Type-2 Fuzzy Model Predictive Microclimate Control of a Greenhouse
    Azzedine Hamza
    Messaoud Ramdani
    Journal of Control, Automation and Electrical Systems, 2020, 31 : 62 - 72
  • [5] NON-PDC OBSERVER-BASED T-S FUZZY TRACKING CONTROLLER DESIGN AND ITS APPLICATION IN CHAOS CONTROL
    Asemani, Mohammad Hassan
    Vatankhah, Ramin
    ASIAN JOURNAL OF CONTROL, 2017, 19 (03) : 969 - 982
  • [6] Study and stability analysis on PDC fuzzy control system based on predictive controller of T-S model's subsystems
    Wang, Shubin
    Hu, Pinhui
    Lin, Li
    WCICA 2006: SIXTH WORLD CONGRESS ON INTELLIGENT CONTROL AND AUTOMATION, VOLS 1-12, CONFERENCE PROCEEDINGS, 2006, : 3915 - +
  • [7] Stability Analysis and Control Design for a Kind of Nonlinear Descriptor System via T-S Fuzzy Model with Actuator Saturation
    Zhu Baoyan
    Zhang Jingjun
    Xing Shuangyun
    Sun Changchun
    PROCEEDINGS OF THE 35TH CHINESE CONTROL CONFERENCE 2016, 2016, : 1539 - 1544
  • [8] Observer-based event-triggered non-PDC control for networked T-S fuzzy systems under actuator failures and aperiodic DoS attacks
    Guo, Siyi
    Xu, Yanan
    Ma, Yuechao
    Fu, Lei
    INFORMATION SCIENCES, 2023, 629 : 276 - 298
  • [9] Event-based weighted residual generator design via non-PDC scheme for fault diagnosis in T-S fuzzy systems
    Wang, Xiao-Lei
    Yang, Guang-Hong
    JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS, 2018, 355 (06): : 3145 - 3167
  • [10] Fuzzy PDC Controller for a Class of T-S Fuzzy Bilinear System via Output Feedback
    Hamdy, M.
    Hamdan, I.
    Ibrahim, M.
    2014 INTERNATIONAL CONFERENCE ON ENGINEERING AND TECHNOLOGY (ICET), 2014,
1234