Abstract：In order to improve the speed control performance of interior permanent magnet synchronous motor (IPMSM),a linear variable parameter model predictive control (LVP-MPC) algorithm is proposed.Herein,the extended Kalman filter (EKF) is used for estimating unknown parameters such as load torque to enhance the robustness.By linearizing the dynamic model of IPMSM at the steady-state operating point,the obtained linear state equation is equivalent to an incremental form,and the predictive model and cost function of the incremental form are designed to achieve the optimal adjustment of the speed and current.Hence,the steady-state error caused by model parameter mismatch and external disturbance is overcome.In addition,polyhedron constraints are used to approximate the quadratic constraints of the drive system.Finally,the MPC optimization problem of the speed control proposed is transformed into a standard form of quadratic programming (QP).The simulation and experimental results show that the proposed architecture has high dynamic performance and zero-offset reference tracking ability.
贾成禹, 王旭东, 周凯. 基于线性变参数模型预测控制的内置式永磁同步电机转速控制器设计[J]. 电工技术学报, 2020, 35(22): 4666-4677.
Jia Chengyu, Wang Xudong, Zhou Kai. Design of Interior Permanent Magnet Synchronous Motor Speed Controller Based on Linear Parameter-Varying Model Predictive Control. Transactions of China Electrotechnical Society, 2020, 35(22): 4666-4677.
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2020, Vol. 35 
