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Optimization on Weighting Factors of Model Predictive Control Based on Fuzzy Technique for Linear Induction Machine

机译:基于模糊技术的线性感应机模糊技术的模型预测控制加权因素优化

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Compared with direct thrust control and vector control methods, the model predictive control (MPC) is recognized as a more effective approach. However, the weighting factors in the objective function must be tuned, which greatly increases the computation burden. In this work, based on the fuzzy technique, one weighting factor optimization method is proposed to identify the suitable control action for the linear induction machine (LIM), which can effectively simplify the selection process. At last, comprehensive simulation results have demonstrated the excellent performance of the proposed method.
机译:与直接推力控制和矢量控制方法相比,模型预测控制(MPC)被认为是一种更有效的方法。但是,必须调整目标函数中的加权因子,这大大增加了计算负担。在这项工作中,基于模糊技术,提出了一种加权因子优化方法,以识别线性感应机(LIM)的合适控制作用,其能够有效简化选择过程。最后,全面的仿真结果表明了所提出的方法的优异性能。

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