Online optimal regulation and tracking control of nonlinear discrete-time system with control constraints

被引：0
|
作者：
Wang, Kang [1 ]
Li, Xiaoli [1 ]
Jia, Chao [1 ]
Li, Yang [2 ]
机构：
[1] Univ Sci & Technol Beijing, Beijing 100083, Peoples R China
[2] Commun Univ China, Sch Int Studies, Beijing 100024, Peoples R China
来源：
2015 10TH ASIAN CONTROL CONFERENCE (ASCC) | 2015年
关键词：
D O I：
暂无
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 paper, an online adaptive dynamic programming (ADP) scheme is proposed to obtain the optimal control of discrete-time nonlinear system with input constraints. First, a control performance function is used to reflect the input constraints, then the neural-network-based ADP scheme is presented, in which one neural network (NN) is designed to approximate the performance function and the other one to compute the constrained optimal control. This online method does not need the knowledge of internal system dynamics and off-line computation. Meanwhile, the proposed method is also extended to the optimal tracking control for certain nonlinear system. Further, stability of the closed loop system is demonstrated by the Lyapunov method. Finally, simulation examples are given to show the effectiveness of the proposed method.
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页数：6
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