Nonlinear vector control of multiphase induction motor using linear quadratic regulator and active disturbances rejection control under disturbances and parameter variations

Introduction. This paper introduces a hybrid control strategy for multiphase induction motors, specifically focusing on the dual star induction motor (DSIM) by integrating active disturbances rejection control (ADRC) and linear quadratic regulator (LQR). Problem. Conventional PI-based indirect field oriented control (IFOC) of DSIM drives exhibit 3 critical shortcomings: 1) sensitivity to parameter variations, such as rotor resistance fluctuations; 2) sluggish transient response during rapid speed and torque changes; 3) slow disturbances rejection, such as sudden load torque variations. The goal of this work is to achieve enhanced reliability, precision and robustness of DSIM drives in high-performance demand applications such as automotive. Methodology. The proposed hybrid control architecture is structured as follows: 1) IFOC decoupling. The DSIM’s stator currents are decomposed into 2 components using Park transformations, aligning the rotor flux vector to the d-axis. 2) The LQR is designed to optimize the outer speed/torque loop regulation by minimizing control efforts and state deviations. 3) ADRCs controllers are designed in the inner current loops. Each controller utilizes an extended state observer to estimate and compensate parameter variations and external disturbances in real time. Results. Simulations using MATLAB/Simulink validation on a 5 kW DSIM under multiple scenarios confirm the robustness of the proposed hybrid strategy. Scientific novelty. The contribution lies in the integration of ADRC and LQR in IFOC: The hierarchical fusion of ADRC (inner loops) and LQR (outer loop) uniquely leverages ADRC’s and the LQR’s real-time power to handle any disturbances and unmodeled dynamics. Practical value. The proposed technique demonstrates enhanced performances in speed’s response, sudden load torque demands and parameter variations. It exhibited high robustness even under degraded conditions such as phase faults, making this strategy ideal for high-performance applications like electric vehicles, where stability and adaptability are critical. References 31, tables 2, figures 24.