DocumentCode :
285089
Title :
An input tracking control system using a forward model on neural network
Author :
Iwata, M. ; Kitamura, S.
Author_Institution :
Dept. of Instrum. Eng., Kobe Univ., Japan
Volume :
2
fYear :
1992
fDate :
7-11 Jun 1992
Firstpage :
793
Abstract :
A design method for an input tracking control system using a neural network is proposed. A multi-layered neural network is first trained to model the input-output mapping of a controlled object of an unknown, discrete-time nonlinear system. This neuro emulator is used for generating Jacobian information with respect to the controlled object. The Jacobian coefficients were generated by the multi-layered neural network which had been, in advance, trained to map the input-output relation of the controlled object. The potential method was then applied for generating the input sequences under constructing an asymptotically stable gradient system. The tracking property was assured in the sense of linearization approximation of the controlled object. A simple control law is determined by Lyapunov´s method so that the output of the controlled object can follow a reference input. Simulation results show the effectiveness of the proposed method
Keywords :
discrete time systems; feedforward neural nets; nonlinear systems; tracking; Jacobian coefficients; Jacobian information; asymptotically stable gradient system; discrete-time nonlinear system; forward model; input sequences; input tracking control system; input-output mapping; input-output relation; linearization approximation; multi-layered neural network; neuro emulator; reference input; Control system synthesis; Control systems; Design methodology; Jacobian matrices; Linear approximation; Lyapunov method; Multi-layer neural network; Neural networks; Nonlinear control systems; Nonlinear systems;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 1992. IJCNN., International Joint Conference on
Conference_Location :
Baltimore, MD
Print_ISBN :
0-7803-0559-0
Type :
conf
DOI :
10.1109/IJCNN.1992.226890
Filename :
226890
Link To Document :
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