Title :
Optimal control for a class of nonlinear systems with state delay based on Adaptive Dynamic Programming with ε-error bound
Author :
Xiaofeng Lin ; Nuyun Cao ; Yuzhang Lin
Author_Institution :
Sch. of Electr. Eng., Guangxi Univ., Nanning, China
Abstract :
In this paper, a finite-horizon ε-optimal control for a class of nonlinear systems with state delay is proposed by Adaptive Dynamic Programming (ADP) algorithm. First of all, the performance index function is defined and the Hamilton-Jacobi-Bellman (HJB) equation is obtained for the problem, the convergence of the iterative algorithm is also presented. Then, ADP algorithm for finite-horizon optimal control is introduced with an ε-error bound so as to get the ε-optimal control, and BP neural network is used to implement ADP algorithm. At last, an example is given to demonstrate the effectiveness of the proposed algorithm.
Keywords :
Jacobian matrices; backpropagation; convergence of numerical methods; dynamic programming; iterative methods; neurocontrollers; nonlinear control systems; optimal control; performance index; ε-error bound; ADP algorithm; BP neural network; HJB equation; Hamilton-Jacobi-Bellman equation; adaptive dynamic programming algorithm; finite horizon ε-optimal control; iterative algorithm convergence; nonlinear systems; performance index function; state delay; Delays; Dynamic programming; Heuristic algorithms; Neural networks; Nonlinear systems; Optimal control; Performance analysis; ε-optimal control; Adaptive Dynamic Programming; finite time; nonlinear systems; state delay;
Conference_Titel :
Adaptive Dynamic Programming And Reinforcement Learning (ADPRL), 2013 IEEE Symposium on
Conference_Location :
Singapore
DOI :
10.1109/ADPRL.2013.6615005