Sensorless linear induction motor speed tracking using fuzzy observers

In this study, the authors develop a sensorless speed controller for linear induction motors (LIMs) based on a fuzzy observer. The authors use a fifth-order non-linear LIM dynamical model with end-effects approximated by Taylor series. Then, the authors represent the LIM by a T-S fuzzy model and construct a fuzzy observer to estimate the immeasurable mover speed and secondary flux states. By computationally solving a set of linear matrix inequalities to obtain the observer gains, the authors achieve exponential convergence of estimation errors when fuzzy membership functions fit a Lipshitz-like property. Based on the fuzzy observer, the control law synthesis is carried out by using a virtual desired variable concept where a skew-symmetric property is utilised. The exponential convergence for both estimation error and tracking error is ensured by the controller design. Finally, speed tracking experiments are carried out to verify the theoretical results and show satisfactory performance.