A rule-based neural controller for inverted pendulum system

Author

Hao, Jianbin ; Tan, Shaohua ; Vandewalle, Joos

Author_Institution

Dept. of Electr. Eng., Katholieke Univ. Leuven, Heverlee, Belgium

fYear

1993

fDate

1993

Firstpage

534

Abstract

It is demonstrated how a heuristic neural control approach can be used to solve a complex nonlinear control problem. As well as swinging up the pendulum, the controller is required to bring the cart back to the origin of the track. Through the solution of this specific control problem, a heuristic neural control approach with task decomposition, control rule extraction and neural net rule implementation as its basic elements is illustrated. Specializing to the pendulum problem, the global control task is decomposed into sub-tasks, namely, pendulum positioning and cart positioning. Three separate neural sub-controllers are designed to cater to the sub-tasks and their coordination. The simulation result is provided to show the actual performance of the controller

Keywords

neural nets; nonlinear control systems; position control; cart positioning; complex nonlinear control; control rule extraction; global control task; heuristic neural control approach; inverted pendulum system; neural sub-controllers; pendulum positioning; rule-based neural controller; sub-tasks; task decomposition; Control design; Control systems; Feedforward neural networks; Fuzzy control; Industrial control; Neural networks; Neurons; Nonlinear control systems; Nonlinear systems; State-space methods;

fLanguage

English

Publisher

ieee

Conference_Titel

Neural Networks, 1993., IEEE International Conference on

Conference_Location

San Francisco, CA

Print_ISBN

0-7803-0999-5

Type

conf

DOI

10.1109/ICNN.1993.298614

Filename

298614