Intelligent control of synchronous machines using ANFIS and model reference neural network controller

Abstract

The paper presents a new approach to Intelligent robust speed control for synchronous motor using an adaptive neuro-fuzzy inference system (ANFIS) controller. The paper develops a simple robust ANFIS controller and a model reference (MRC) adaptive controller to deal with parameters uncertain and external disturbances. The control strategy is based on fuzzy control approaches. A complete ANFIS control based synchronous motor has been described and a MRC neural network controller is described. The system was analyzed and designed, and performances were studied and a comparison is made to visualise the ANFIS controller as a better controller than the MRC Neural Network Controller extensively by simulation to validate the theoretical concept. The simulation results show that the proposed ANFIS controller is superior to conventional neural controller in robustness and in tracking precision. It appears from the response properties that it has a high performance in presence of the plant parameters uncertain and load disturbances. The control of speed by ANFIS control gives fast dynamic response with no overshoot and a good rejection of impact load disturbance.