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Impact of the Prediction Error on the Performance of Model Predictive Controllers with Long Prediction Horizons for Modular Multilevel Converters - Linear vs. Nonlinear System Models

机译:预测误差对模块化多电平转换器具有长预测期的模型预测控制器的性能的影响-线性与非线性系统模型

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The closed loop control performance of MMCs can be significantly improved by using Model Predictive Control (MPC). This paper evaluates an MPC algorithm based on a linearised MMC model regarding the performance limits caused by the prediction error due to the linearisation. To decrease the prediction error to a minimum and to improve the performance it is proposed to use a nonlinear MMC model as a prediction model for the MPC. The steady state and transient performance of the MPC with both MMC models is compared in detail using simulations to analyse the effect of the prediction error on the control performance.
机译:通过使用模型预测控制(MPC),可以显着提高MMC的闭环控制性能。本文评估了基于线性化MMC模型的MPC算法,其中考虑了由于线性化导致的预测误差而导致的性能极限。为了将预测误差减小到最小并改善性能,提出了使用非线性MMC模型作为MPC的预测模型。使用仿真对两种MMC模型的MPC的稳态和瞬态性能进行了详细比较,以分析预测误差对控制性能的影响。

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