NN-adaptive predictive control for a class of discrete-time nonlinear systems with input-delay

被引:10
|
作者
Zhao, Jiemei [1 ]
机构
[1] Wuhan Polytech Univ, Sch Math & Comp Sci, Wuhan 430023, Peoples R China
关键词
Discrete-time nonlinear systems; Input-delay; Predictive control; Neural network (NN); OUTPUT-FEEDBACK CONTROL; NEURAL-NETWORK; TRACKING CONTROL; MODEL; TELEOPERATION; ALGORITHM;
D O I
10.1016/j.neucom.2015.09.059
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
An adaptive neural network (NN) predictive control algorithm is proposed for a class of uncertain discrete-time nonlinear systems with input-delay. For approximate the nonlinear part of the uncertain discrete-time nonlinear system, the recurrent neural network (RNN) is employed. A version of discretetime NN weight update rule is given. For compensate the reconstructive error of the RNN and the external disturbances, the robust control term is designed. In order to compensate the time-delay in input channel, a predictive control algorithm is proposed. Then the synchronous tracking objective can be realized. An illustrative example is provided to demonstrate the effectiveness of the proposed control strategy. (C) 2015 Elsevier B.V. All rights reserved.
引用
收藏
页码:1832 / 1838
页数:7
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