Stochastic Linear Quadratic Optimal Tracking Control with Time-Delays Based on Adaptive Dynamic Programming
An adaptive dynamic programming(ADP)algorithm is proposed for a class of model-free stochastic linear quadratic(SLQ)optimal tracking problem with time-delay.Firstly,the equivalent system of the original time-delay system is de-rived using the double causal coordinate transformation.A new augmented system consisting of the equivalent system and the command generator is constructed,and then the stochastic algebraic equations of the augmented system are given.Secondly,in order to solve the SLQ tracking control problem,the stochastic problem is trans-formed into deterministic problem.Then the ADP algorithm is proposed and its convergence analysis is given.For the purpose of realizing the ADP algorithm,three neural networks are designed,which approximate the optimal cost function,the opti-mal control gain matrix and the system model respectively.Finally,the effectiveness of the algorithm is verified by a numeric example.
Stochastic linear systemstime-delayadaptive dynamic programmingneural networks
万方数据
维普
