Title :
Backpropagation neurofuzzy controller for nonlinear dynamic system
Author :
Gherari, Z. ; Hamam, L.Y.
Author_Institution :
Dept. of Autom., ESIEE, Noisy-le-Grand, France
Abstract :
In this paper, a new paradigm of a neurofuzzy controller is developed. Two architectures are used: the first consists of a one step predictor and the second is a backpropagation neurofuzzy controller (BPNFC). A generalized backpropagation algorithm is developed and used to train both the one step neural network predictor and the neurofuzzy controller. The control mechanism is then analysed and simulation results show that the scheme has a high capability to learn and generalize, and can deal with large unknown nonlinearities
Keywords :
backpropagation; control system analysis; fuzzy control; neurocontrollers; nonlinear dynamical systems; predictive control; backpropagation neurofuzzy controller; generalized backpropagation algorithm; large unknown nonlinearities; one step predictor; Automatic control; Backpropagation; Control systems; Fuzzy control; Fuzzy logic; Fuzzy sets; Fuzzy systems; Neural networks; Nonlinear control systems; Nonlinear dynamical systems;
Conference_Titel :
Fuzzy Systems, 1996., Proceedings of the Fifth IEEE International Conference on
Conference_Location :
New Orleans, LA
Print_ISBN :
0-7803-3645-3
DOI :
10.1109/FUZZY.1996.552345
