Speed and position control of linear induction motor using LMI based FSVFB controller under internal fault conditions

Abstract Linear induction motors (LIMs) are increasingly being employed in modern transportation, automation, and robotics because they provide direct linear motion and high thrust with a simple structure. However, LIM performance is significantly impaired by internal faults such as cracks or conductivity loss in the secondary aluminum sheet, leading to rotor imbalances and electromagnetic asymmetry. This paper proposes a unified framework combining multi-objective Taguchi optimization with a Fuzzy State-Variable Feedback (FSVFB) controller, developed via the Linear Matrix Inequality (LMI) method, to increase the efficiency and fault tolerance in an LIM. Using the Taguchi algorithm, several key design parameters will be optimized to increase thrust efficiency and the power factor while minimizing slip, improving its electromagnetic design. A refined virtual-bar fault model is developed that captures current redistribution due to internal cracks, using an equivalent conductivity-degradation coefficient, and on this model the LMI-based FSVFB controller is designed to maintain stable speed and position control despite fault scenarios. Simulation results show the proposed method improved efficiency by 9.5% and increased the power factor by 12.3% compared to the standard GA-based optimization method. Additionally, position error was maintained under 0.5%, and speed oscillations were suppressed by over 85% even under severe rotor imbalance. These results confirm the robustness and effectiveness of the proposed Taguchi–LMI–FSVFB framework for high-performance LIM applications.