Litcius/Paper detail

A Robust Predictive Speed Control for SPMSM Systems Using a Sliding Mode Gradient Descent Disturbance Observer

Fengxiang Wang, Long He, José Rodríguez

2022IEEE Transactions on Energy Conversion35 citationsDOI

Abstract

This paper proposes a sliding mode gradient descent disturbance observer-based adaptive reaching law sliding mode predictive speed control (GD-SMPC+ARL) for surface-mounted permanent magnet synchronous motor (SPMSM) systems to achieve outstanding disturbance rejection ability and tracking performance. Firstly, an SPMSM model with disturbance is given by incorporating the lumped disturbances into the q-axis current's coefficient. Then, a stable sliding mode gradient descent disturbance observer (SM-GDDO) is designed to identify the q-axis current's coefficient that varies with the lumped disturbance. Finally, a GD-SMPC+ARL strategy, which utilizes an adaptive reaching law-based cost function, is developed on the basis of the proposed SPMSM model, where the q-axis current's coefficient is estimated by utilizing SM-GDDO and updated at each control period. Compared with conventional reaching laws, the proposed adaptive reaching law suppresses the chattering while maintaining a fast following speed. Simulation and experimental results verify the excellent robustness and tracking performances of the proposed method.

Topics & Concepts

Control theory (sociology)Robustness (evolution)Gradient descentSliding mode controlDisturbance (geology)Computer scienceEngineeringNonlinear systemPhysicsControl (management)Artificial neural networkArtificial intelligenceBiologyQuantum mechanicsGeneBiochemistryPaleontologyChemistrySensorless Control of Electric MotorsIterative Learning Control SystemsMagnetic Bearings and Levitation Dynamics