带饱和执行器的非线性离散时滞系统的最优控制  

Optimal Control for Nonlinear Discrete-Time Time Delay Systems with Saturating Actuators

作　　者：王涛[1] 罗艳红[1] 

机构地区：[1]东北大学信息科学与工程学院,辽宁沈阳110819

出　　处：《东北大学学报（自然科学版）》2014年第4期461-465,共5页Journal of Northeastern University(Natural Science)

基　　金：国家自然科学基金资助项目(50977008;61034005);国家基础研究计划项目(2009CB320601);辽宁省自然科学基金资助项目(201202201)

摘　　要：主要针对带有饱和执行器的时滞非线性离散时间系统更加一般的形式,通过启发式动态规划(HDP)算法求解无限时间最优控制策略问题,并在值函数中引入折扣因子.首先通过迭代HDP算法给出值函数序列和相应的控制序列,并给出了收敛性证明,即值函数序列收敛到值函数的最优值,以及控制序列收敛到最优控制;其次为了实现HDP算法,引入3个神经网络:模型网络、评判网络、控制作用网络.模型网络用来近似系统模型,评判网络用来近似值函数,控制作用网络用来近似控制;最后通过一个仿真例子说明上述方法的可行性.For the more general form of nonlinear discrete-time time delays systems with saturating actuators, an infinite-time optimal control scheme was developed by heuristic dynamic programming （HDP） algorithm. In the proposed scheme, the discount factor was added in the value function. Firstly, value function series and control series were given through iterative HDP algorithm, and the convergence analysis was presented to prove that value function series and control series reach the optimal value simultaneously. Secondly, three neural networks （NN） which are model NN, critic NN, action NN were introduced to carry out the HDP algorithm. Model NN was used to approximate system model, critic NN to approximate value function, action NN to approximate control policy. Lastly, the validity of HDP algorithm was illustrated by one simulation example.

关 键 词：近似动态规划 启发式动态规划 值函数 神经网络 最优控制 

分 类 号：TP273.1[自动化与计算机技术—检测技术与自动化装置]