永磁同步电机高效非线性模型预测控制

永磁电机控制器要求电机有很强的转速跟踪能力，并且要保证系统参数变化及负荷扰动下系统的鲁棒性. 永磁电机包含很多不确定因素，是强耦合的非线性系统，传统的线性控制器很难对其进行控制. 针对永磁电机的转速控制构造非线性模型预测控制方法. 非线性永磁电机模型通过输入-输出反馈线性化策略解耦成为新的线性系统. 为保证可行解的收敛性，提出一种迭代二次规划方法来处理由输入-输出反馈线性化导致的非线性约束. 仿真结果表明，控制器能有效降低计算负担，具有很好的动态控制性能，能抑制转矩脉动，并保证在参数变化和负荷扰动下控制系统的鲁棒性.

Efficient Nonlinear Model Predictive Control for Permanent Magnet Synchronous Motor

Reliable control of the permanent magnet synchronous motor is necessary to ensure high speed-following capability and robustness under model parameter and load torque variations. This is often difficult to achieve using conventional linear controllers, as permanent magnet synchronous motor (PMSM) is a nonlinear and high coupling system containing many uncertainties. This paper proposes a nonlinear model predictive controller for a speed control of PMSM. The nonlinear PMSM decouples into a new linear system via the input-output feedback linearization scheme. To guarantee its convergence, an iterative quadratic program routine is proposed to solve the linear model based predictive control, problem with nonlinear constraints. Simulation results show the proposed controller has good dynamic and static performance and robustness under system parameter and load torque variations while reducing computational burden and torque ripples.