带饱和执行器的非线性离散时滞系统的最优控制

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.

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

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.