Title :
Neural dynamic optimization for control systems.III. Applications
Author :
Seong, Chang-Yun ; Widrow, Bernard
Author_Institution :
Dept. of Electr. Eng., Stanford Univ., CA, USA
fDate :
8/1/2001 12:00:00 AM
Abstract :
For pt.II. see ibid., p. 490-501. The paper presents neural dynamic optimization (NDO) as a method of optimal feedback control for nonlinear multi-input-multi-output (MIMO) systems. The main feature of NDO is that it enables neural networks to approximate the optimal feedback solution whose existence dynamic programming (DP) justifies, thereby reducing the complexities of computation and storage problems of the classical methods such as DP. This paper demonstrates NDO with several applications including control of autonomous vehicles and of a robot-arm, while the two other companion papers of this topic describes the background for the development of NDO and present the theory of the method, respectively
Keywords :
MIMO systems; computational complexity; dynamic programming; feedback; neural nets; optimal control; autonomous vehicles; dynamic programming; neural dynamic optimization; neural networks; nonlinear multi-input-multi-output systems; optimal feedback control; optimal feedback solution; robot-arm; Computer networks; Control systems; Dynamic programming; Feedback control; MIMO; Neural networks; Neurofeedback; Optimal control; Optimization methods; Vehicle dynamics;
Journal_Title :
Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
DOI :
10.1109/3477.938256