Title :
A nonlinear neural-net based PID controller using local linear models
Author :
Ohnishi, Y. ; Hirata, M.
Author_Institution :
Dept. of Electr. Eng., Kure Nat. Coll. of Technol., Japan
Abstract :
PID control schemes based on the classical control theory have been widely used for various process control systems for a long time. However, it is difficult to find a set of suitable PID parameters for nonlinear systems. In this paper, a compensation method of PID parameters for the nonlinear systems is proposed by using a neural network.
Keywords :
linear systems; neurocontrollers; nonlinear control systems; three-term control; PID controller; classical control theory; local linear models; nonlinear neural nets; nonlinear systems; process control systems; Control system synthesis; Control systems; Control theory; Educational institutions; Integrated circuit modeling; Neural networks; Nonlinear control systems; Nonlinear systems; Process control; Three-term control;
Conference_Titel :
Industrial Electronics Society, 2004. IECON 2004. 30th Annual Conference of IEEE
Print_ISBN :
0-7803-8730-9
DOI :
10.1109/IECON.2004.1431847
