Title :
A design of neural-net based predictive PID controllers
Author :
Asano, M. ; Yamamoto, Takayuki ; Oki, T. ; Kaneda, M.
Author_Institution :
Dept. of Commun. Eng., Okayama Prefectural Univ., Japan
Abstract :
PID control schemes have been widely used for various real control systems. However, in practice, since it is difficult to find suitable PID gains, a lot of research has been reported with respect to tuning schemes of PID gains. In this paper, a design scheme of neural net-based PID controllers is proposed for nonlinear systems. The modeling error between a linear nominal model and a controlled object is compensated by a multilayered neural network whose outputs are given as additive PID gains. Furthermore, the fixed PID gains are calculated for the linear nominal model based on a generalized predictive control scheme
Keywords :
control system synthesis; multilayer perceptrons; neurocontrollers; nonlinear control systems; predictive control; three-term control; additive PID gains; design scheme; generalized predictive control scheme; modeling error; multilayered neural network; neural-net based predictive PID controllers; nonlinear systems; Chemical processes; Communication system control; Control systems; Electrical equipment industry; Error correction; Industrial control; Neural networks; Predictive control; Predictive models; Three-term control;
Conference_Titel :
Systems, Man, and Cybernetics, 1999. IEEE SMC '99 Conference Proceedings. 1999 IEEE International Conference on
Conference_Location :
Tokyo
Print_ISBN :
0-7803-5731-0
DOI :
10.1109/ICSMC.1999.812566
