Decentralized Output Feedback Adaptive NN Tracking Control for Time-Delay Stochastic Nonlinear Systems With Prescribed Performance

被引:120
作者
Hua, Changchun [1 ]
Zhang, Liuliu [1 ]
Guan, Xinping [2 ,3 ]
机构
[1] Yanshan Univ, Inst Elect Engn, Qinhuangdao 066004, Peoples R China
[2] Shanghai Jiao Tong Univ, Dept Automat, Shanghai 200030, Peoples R China
[3] Yanshan Univ, Inst Elect Engn, Qinghuangdao City 066004, Peoples R China
基金
中国国家自然科学基金;
关键词
Neural network (NN) approach; prescribed performance control (PPC); reduced-order observer design; stochastic interconnected time-delay system; DEPENDENT EXPONENTIAL STABILITY; NEURAL-NETWORK CONTROL; H-INFINITY CONTROL; STATE-FEEDBACK; VARYING DELAY; STABILIZATION; OBSERVER;
D O I
10.1109/TNNLS.2015.2392946
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper studies the dynamic output feedback tracking control problem for stochastic interconnected time-delay systems with the prescribed performance. The subsystems are in the form of triangular structure. First, we design a reduced-order observer independent of time delay to estimate the unmeasured state variables online instead of the traditional full-order observer. Then, a new state transformation is proposed in consideration of the prescribed performance requirement. Using neural network to approximate the composite unknown nonlinear function, the corresponding decentralized output tracking controller is designed. It is strictly proved that the resulting closed-loop system is stable in probability in the sense of uniformly ultimately boundedness and that both transient-state and steady-state performances are preserved. Finally, a simulation example is given, and the result shows the effectiveness of the proposed control design method.
引用
收藏
页码:2749 / 2759
页数:11
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