摘要
针对不确定的非线性连续系统,通过神经网络对系统进行辨识.基于辨识后的确定系统,利用执行网-评价网双网结构进行同步调节解决最优跟踪问题.应用李雅谱诺夫方法进行辨识分析和系统稳定性分析,定理结论表明辨识系统为渐近辨识的,同时系统的跟踪误差和权重误差一致最终有界,倒立摆仿真例子验证了算法的有效性.
In this paper, for the unknown continuous nonlinear system, Neural Networks identifier model is applied. Based on the identified model, Approximate Dynamic Program- ming（ADP） is used and actor-critic dual networks simultaneously are tuned in order to solve the optimal tracking problem. The identified result and the stability analysis based on the Lyapunov method are given. Theorems shows the identification is asymptotic and all the tracking error and the estimate weights are UUB, the inverted pendulum system simulation verified the effectiveness of algorithm.
出处
《数学的实践与认识》
北大核心
2015年第11期266-274,共9页
Mathematics in Practice and Theory
基金
黑龙江省教育厅教改项目(JG2014011057)
牡丹江师范学院省级重点创新预研项目(SY2014005
SY2014006)
关键词
近似动态规划
神经网路
最优控制
跟踪问题
approximate dynamic programming
neural network
optimal control
trackingproblem
