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
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