电励磁同步电机全速域自适应模型预测控制

针对传统模型预测控制(MPC)单一权值系数存在的局部最优问题,提出一种全速域自适应模型预测控制(FSA-MPC)方法。该方法采取离线初选和在线优化两个步骤完成权值系数配置,保证了MPC中滚动优化的控制品质。首先,建立电励磁同步电机的离散预测模型,并以加权求和的形式配置价值函数;其次,分析不同权值系数对各项优化目标的影响,统计得出了一个理想最优权值系数覆盖区域;最后,考虑到离线穷举法配置权值系数的不完备性,引入在线自适应机制进行在线修正。基于55k W样机验证了全速区域范围内FSA-MPC的可行性,并与传统MPC进行了对比分析,结果表明FSA-MPC可在全速域范围内保持优异的控制效果。

Full Speed Adaptive Model Predictive Control for Electrical Excitation Synchronous Motor

The complicated multi-objective optimization problem exists when traditional model predictive control (MPC) is applied to the electrical excitation synchronous motor speed regulating system. Therefore, this paper proposes a full speed adaptive MPC (FSA-MPC) method. This method includes two primary steps of offline and online optimization, which ensures the quality of the rolling optimization. First of all, this paper establishes a discrete prediction model of electrical excitation synchronous motor, and designs the cost function weighted sum. Then the effects of different weighting coefficients on the optimization objects are analyzed. An ideal optimal weighting coefficient of coverage area by statistics is obtained. Finally, due to the incomplete configuration of weighting coefficients by offline exhaustive method, the online adaptive mechanism for online correction is introduced. The feasibility of FSA-MPC at full speed area is verified based on a 55kW prototype. Compared with the traditional MPC, the results show that the FSA-MPC achieves excellent control effects at full speed range.