Integral barrier Lyapunov function-based adaptive fuzzy output feedback control for nonlinear delayed systems with time-varying full-state constraints

被引:9
|
作者
Ye, Dan [1 ,2 ]
Wang, Kaiyu [1 ]
Yang, Haijiao [1 ]
Zhao, Xingang [3 ]
机构
[1] Northeastern Univ, Coll Informat Sci & Engn, Shenyang, Peoples R China
[2] Northeastern Univ, State Key Lab Synthet Automat Proc Ind, Shenyang, Peoples R China
[3] Chinese Acad Sci, Shenyang Inst Automat, State Key Lab Robot, Shenyang 110016, Peoples R China
基金
中国国家自然科学基金;
关键词
adaptive fuzzy control; IBLF; input saturation; output-feedback; time-varying full-state constraints; DYNAMIC SURFACE CONTROL; TRACKING CONTROL; NEURAL-CONTROL;
D O I
10.1002/acs.3172
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
In this article, an adaptive fuzzy output feedback control method is presented for nonlinear time-delay systems with time-varying full state constraints and input saturation. To overcome the problem of time-varying constraints, the integral barrier Lyapunov functions (IBLFs) integrating with dynamic surface control (DSC) are applied for the first time to keep the state from violating constraints. The effects of unknown time delays can be removed by using designed Lyapunov-Krasovskii functions (LKFs). An auxiliary design system is introduced to solve the problem of input saturation. The unknown nonlinear functions are approximated by the fuzzy logic systems (FLS), and the unmeasured states are estimated by a designed fuzzy observer. The novel controller can guarantee that all signals remain semiglobally uniformly ultimately bounded and satisfactory tracking performance is achieved. Finally, two simulation examples illustrate the effectiveness of the presented control methods.
引用
收藏
页码:1677 / 1696
页数:20
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