Fuzzy speed estimation in the case of sensorless induction machine vector control

Abstract

This paper deals with the problem of sensorless indirect field oriented control of an induction machine. Based on the fourth-order nonlinear model, we propose a novel structure of a full-order Takagi-Sugeno (TS) adaptive observer, through which we ensure the estimation of IM states and the rotor speed, which is considered as an immeasurable premise variable. This approach satisfies global stability for all operating conditions and operates under unknown applied load torque. In this work, a TS fuzzy model is presented to approximate a nonlinear IM model in the stationary rotating reference frame. A TS adaptive observer is then described. We then design observer gains to guarantee specified observer dynamic performances through a D-stability analysis. Meanwhile, a TS-based scheme is proposed for speed estimation. The synthesis is based on sufficient conditions that are developed and formulated into linear matrix inequalities terms. Simulation and experimental results are given to show the effectiveness of the proposed method.

A GA-based adaptive mechanism for sensorless vector control of induction motor drives for urban electric vehicles

“…Thus, several techniques are used to accurately determine speed. Two main categories are developed in the literature [5][6][7][8][9][10][11][12][13][14]: a category that does not require knowledge of the motor model (signal injection) and the others based on the motor model.…”