Title :
A neural network method for the nonlinear servomechanism problem
Author :
Chu, Yun-Chung ; Huang, Jie
Author_Institution :
Dept. of Mech. & Autom. Eng., Chinese Univ. of Hong Kong, Shatin, Hong Kong
Abstract :
The solution of the nonlinear servomechanism problem relies on the solvability of a set of mixed nonlinear partial differential and algebraic equations known as the regulator equations. Due to the nonlinear nature, it is difficult to obtain the exact solution of the regulator equations. This paper proposes to solve the regulator equations based on a class of recurrent neural network, leading to an effective approach to approximately solving the nonlinear servomechanism problem
Keywords :
algebra; neurocontrollers; nonlinear control systems; nonlinear differential equations; partial differential equations; recurrent neural nets; servomechanisms; nonlinear algebraic equations; nonlinear partial differential equations; nonlinear servomechanism problem; recurrent neural network; regulator equations; solvability; Automation; Control systems; Differential algebraic equations; Neural networks; Nonlinear control systems; Nonlinear equations; Recurrent neural networks; Regulators; Servomechanisms; State feedback;
Conference_Titel :
American Control Conference, 1998. Proceedings of the 1998
Conference_Location :
Philadelphia, PA
Print_ISBN :
0-7803-4530-4
DOI :
10.1109/ACC.1998.694724
