基于单网络ADP的一类未知非线性系统的近似最优控制  

Near-optimal control of a class of unknown nonlinear systems based on single network ADP

作　　者：崔黎黎[1] 刘杰[1] 张勇[1] 

机构地区：[1]沈阳师范大学科信软件学院,沈阳110034

出　　处：《控制与决策》2013年第9期1423-1426,1430,共5页Control and Decision

基　　金：国家自然科学基金项目(60970112)

摘　　要：针对一类未知的连续非线性系统,提出一个基于单网络近似动态规划(ADP)的近似最优控制方案.该方案通过设计一个新型的递归神经网络(RNN)辨识器放松了系统模型需已知或部分已知的要求,并利用一个神经网络(NN)近似系统的性能指标函数消除了常规ADP方法中的控制网络.通过Lyapunov理论分析严格证明了闭环系统内所有信号一致最终有界,并且所获得的性能指标函数和控制输入分别收敛到最优性能指标函数和最优控制输入的小邻域内.仿真结果验证了所提出控制方案的有效性.The near-optimal control scheme is proposed for a class of unknown continuous-time nonlinear systems based on single network approximate dynamic programming（ADP）.The proposed scheme relaxes the requirement of the system model being known or partly known by designing a novel recurrent neural network（RNN） identifier,and eliminates the action network of ordinary ADP methods by employing a neural network（NN） to approximate the performance index function.By Lyapunov theory,it is proved that all the signals in the closed-loop system are ultimately uniformly bounded and the obtained optimal performance index function and control input lie in small neighborhoods of the optimal performance index function and the optimal control input,respectively.Simulation results demonstrate the effectiveness of the proposed scheme.

关 键 词：未知非线性系统 递归神经网络 近似动态规划 自适应 最优控制 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]