To address the degradation of performance in speed control and insufficient robustness of permanent magnet synchronous motors under high dynamic operation and external load disturbances, a continuous-time model predictive control method that integrates Laguerre function-based parameterization with a nonlinear disturbance observer compensation mechanism is proposed. The method employs finite-dimensional parameterization of the control increment using Laguerre orthogonal functions to significantly reduce the optimization dimension and improve computational efficiency. An adaptive smoothing factor is designed to achieve a dynamic balance between control response speed and input smoothness. To enhance the engineering

applicability of the control system, a continuously differentiable soft constraint mechanism is introduced to avoid numerical instability caused by hard constraints. Simulation results verify that the proposed method exhibits superior speed tracking accuracy and disturbance rejection performance compared to conventional model predictive control under the same conditions.

permanent magnet synchronous motor, continuous-time model predictive control, nonlinear disturbance observer, Laguerre function, parameterization