A New Tuning Approach for MPC Applied to a Disturbed DC Motor

M. Turki, Ismail Oukkacha, N. Langlois, A. Yassine, M. Camara, B. Dakyo
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Abstract

In order to get correct results using the Model Predictive Control (MPC), one must find the suitable values of its parameters. Despite a large number of papers in literature on MPC tuning methods, there is no available analytical approach permitting to identify explicitly the robustness area of a process independently of its order. Here we intend to overcome this limit thanks to an analytical one. The interest of our approach is to be applicable to a wide set of linear controllable and observable single-input single-output (SISO) processes. The issues of optimal closed-loop stability and the energy consumed are addressed in this paper. The proposed method is tested experimentally via a DC motor. Finally, a performance comparison is made with existing methods to emphasize its effectiveness.
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一种应用于扰动直流电动机的MPC调谐新方法
为了使用模型预测控制(MPC)得到正确的结果,必须找到合适的参数值。尽管文献中有大量关于MPC调优方法的论文,但没有可用的分析方法允许明确地识别独立于其顺序的过程的鲁棒性区域。在这里,我们打算借助分析性限制来克服这一限制。我们的方法的兴趣是适用于广泛的线性可控和可观察的单输入单输出(SISO)过程。本文讨论了最优闭环稳定性和能量消耗问题。通过直流电机对该方法进行了实验验证。最后,与现有方法进行了性能比较,以强调其有效性。
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