Fuzzy Virtual Reference Model Sensorless Tracking Control for Linear Induction Motors

This paper introduces a fuzzy virtual reference model (FVRM) synthesis method for linear induction motor (LIM) speed sensorless tracking control. First, we represent the LIM as a Takagi-Sugeno fuzzy model. Second, we estimate the immeasurable mover speed and secondary flux by a fuzzy observer. Third, to convert the speed tracking control into a stabilization problem, we define the internal desired states for state tracking via an FVRM. Finally, by solving a set of linear matrix inequalities (LMIs), we obtain the observer gains and the control gains where exponential convergence is guaranteed. The contributions of the approach in this paper are threefold: 1) simplified approach-speed tracking problem converted into stabilization problem; 2) omit need of actual reference model-FVRM generates internal desired states; and 3) unification of controller and observer design-control objectives are formulated into an LMI problem where powerful numerical toolboxes solve controller and observer gains. Finally, experiments are carried out to verify the theoretical results and show satisfactory performance both in transient response and robustness.