Sugeno fuzzy PID tuning, by genetic-neutral for AVR in electrical power generation
Integrated model is developed by combining genetic algorithm (GA), radial basis function neural network (RBF-NN) and Sugeno fuzzy logic approaches. Optimal PID gains obtained by the proposed RBF-NN tuning for various operating conditions are used to develop the rule base of the Sugeno fuzzy system. The RBF-NN is used to enhance the PID parameters obtained from GA. Enhanced PID parameters are used to design Sugeno fuzzy PID controller tuned by excitation parameter (Ke, ?e) of the AVR system to improve the system's response.
ga rbf-nn sugeno fuzzy logic develop the rule base avr system design a pid controller