Title :
The application of a neural-fuzzy logic controller to process control
Author :
Kelly, D.J. ; Burton, P.D. ; Rahman, M.A.
Author_Institution :
Dept. of Electron. & Comput. Eng., Limerick Univ., Ireland
Abstract :
A neural-fuzzy controller is an intelligent system that allows for the combination of qualitative knowledge in fuzzy rules and the learning capabilities of neural networks. This paper examines the suitability of one particular neural-fuzzy model, the adaptive network fuzzy interference system (ANFIS) proposed by J.-S.R. Jang, for use as part of control systems. The adaptive neural-fuzzy controller developed uses the sign of the output error and the gradient descent algorithm to update its parameters and gives superior control than PID. The controller accommodates modifications made to the original plant
Keywords :
adaptive control; fuzzy control; fuzzy logic; intelligent control; neurocontrollers; PID; adaptive network fuzzy interference system; fuzzy rules; gradient descent algorithm; intelligent system; learning capabilities; neural networks; neural-fuzzy logic controller; output error; process control; qualitative knowledge; Adaptive systems; Control systems; Fuzzy control; Fuzzy neural networks; Fuzzy systems; Intelligent networks; Intelligent systems; Logic; Neural networks; Process control;
Conference_Titel :
Fuzzy Information Processing Society Biannual Conference, 1994. Industrial Fuzzy Control and Intelligent Systems Conference, and the NASA Joint Technology Workshop on Neural Networks and Fuzzy Logic,
Conference_Location :
San Antonio, TX
Print_ISBN :
0-7803-2125-1
DOI :
10.1109/IJCF.1994.375131
