Title :
Self-tuning control of nonlinear systems
Author :
Farsi, M. ; Abdulaziz, A.
Author_Institution :
Dept. of Electr. & Electron. Eng., Newcastle upon Tyne Univ., UK
fDate :
29 June-1 July 1994
Abstract :
The paper deals with self-tuning control of Hammerstein type nonlinear systems that contain linear parameters and a nonlinear quasi-input function of the real input signal. Linear estimation algorithm has been used to estimate the linear parametric part, whilst a neural feedforward net is employed to estimate the remaining nonlinearity. The performance of the controller is illustrated by a hybrid algorithm simulation.
Keywords :
adaptive control; feedforward neural nets; nonlinear control systems; parameter estimation; self-adjusting systems; Hammerstein type nonlinear systems; hybrid algorithm simulation; linear estimation algorithm; linear parameters; neural feedforward net; nonlinear quasi-input function; nonlinearity; self-tuning control; Backpropagation algorithms; Computational modeling; Control systems; Control theory; Kernel; Nonlinear control systems; Nonlinear equations; Nonlinear systems; Power system modeling; Prediction algorithms;
Conference_Titel :
American Control Conference, 1994
Print_ISBN :
0-7803-1783-1
DOI :
10.1109/ACC.1994.735230
