Conventional model predictive direct speed control (MP-DSC) has received extensive attention because of its easy implementation, fast dynamic response, and simple structure. However, weighting factor and parameter mismatch are two key factors restricting the control performance of MP-DSC. In this article, a model-free hybrid parallel predictive speed control (MF-HPPSC) based on ultralocal model is proposed to solve the above-mentioned problems. First, the multiobjective parallel predictive speed control method realizes synchronous control of speed, torque, and flux linkage without weighting factor. The original excellent dynamic response capability is guaranteed, and the steady-state performance is simultaneously enhanced. Moreover, the linear extended state observer (LESO) designed by the unique ultralocal model makes the calculation process of future state prediction without any machine parameters, and the robustness of the system is significantly improved. Finally, the simulation and experiment comparison among the conventional MP-DSC, conventional model-free control, and the proposed MF-HPPSC verified the superiority of the proposed method.

中文翻译：

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基于永磁同步电机超局部模型的电动汽车无模型混合并行预测速度控制

传统模型预测直接速度控制（MP-DSC）因其易于实现、动态响应快、结构简单而受到广泛关注。然而，权重因子和参数不匹配是制约 MP-DSC 控制性能的两个关键因素。针对上述问题，本文提出了一种基于超局部模型的无模型混合并行预测速度控制（MF-HPPSC）。首先，多目标并行预测速度控制方法实现了速度、转矩和磁链的同步控制，无需加权因子。保证了原有优异的动态响应能力，同时提升了稳态性能。而且，独特的超局部模型设计的线性扩展状态观测器（LESO）使得未来状态预测的计算过程无需任何机器参数，显着提高了系统的鲁棒性。最后，通过对传统 MP-DSC、传统无模型控制和提出的 MF-HPPSC 的仿真和实验比较，验证了所提方法的优越性。