Fuzzy Logic Enhanced Speed Controller of Sensorless Field Orientation Control Induction Motor Drive

Abstract

The goal of this paper is control and estimation speed of indirect field orientation control induction motor. The system is nonlinear and one therefore cannot directly use any linear system tools for estimation. However, the standard discrete Kalman filter (KF) has been used for state estimation. As such, the nonlinear model has been discredited and extended to be suitably applied for such filter. The entire state estimated system has been modeled using MATLAB/SIMULINK blocks. The state estimation algorithm and motor discretized model are coded inside special S- function of m-file type. Also, the error covariance matrices of measurement and process will be developed from the system model. PI controller is replaced by fuzzy logic controller. The common conclusion drawn from such study is that fuzzy logic controller has shown a superior performance.