Hyperstability Criterion in Model Reference Adaptive Control: Enhancing Induction Motor Efficiency for Autonomous Electric Vehicles

The combination of Electric Autonomous Vehicles (EAVs) and renewable energy aligns with sustainability goals. However, to achieve these goals, it’s necessary to implement a robust control system for the key component that drives the vehicle, specifically, the electric motor. This paper explores the control of Induction Motor pursuing the Required Performance Standards for Autonomous Vehicles. The primary objective is to build a robust control system to achieve this, the first approach is the Indirect Rotor Field Oriented Control (IFOC), the Latter is implemented along with a PI controller, Lastly Model Reference Adaptive control by Hyperstability Criterion is introduced. A detailed analysis is carried out using MATLAB Simulink, which shows the efficiency of adaptive control not only in speed tracking, but also in parameter variation and disturbance. The comparative analysis between PI and Hyperstability control method validates the theory asserting the robustness and insensitivity of adaptive control to parameter uncertainty and disturbances. Furthermore, it convincingly demonstrates that the latter outperforms traditional classic controllers.