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A novel adaptive three stages model predictive control based on fuzzy systems: Application in MIMO controlling of MED-TVC process

机译:基于模糊系统的新型自适应三阶段模型预测控制:在MED-TVC过程的MIMO控制中的应用

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摘要

In the present study, a novel technique is suggested for the adaptive non-linear model predictive control based on the fuzzy approach in three stages. In the presented approach, in the first stage, the prediction and control horizons are obtained from a fuzzy system in each control step. Another fuzzy system is employed to determine the weight factors before the optimization stage of developing new controller. The proposed controller gives the parameters of the model predictive control (MPC) in each control step in order to improve the performance of nonlinear systems. The proposed control scheme is compared with the traditional MPC and Generic Model Control for controlling MED-TVC process. The performances of the three proposed controllers have been investigated in the absence and presence of disturbance in order to evaluate the stability and robustness of the proposed controllers. The results reveal that the novel adaptive controller based on fuzzy approach performs better than the two other controllers in set-point tracking and disturbance rejection with lower IAE criteria. In addition, the average computational time for the adaptive MPC exhibits a decline of 34% in comparison with the traditional MPC. (C) 2019 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
机译:在本研究中,提出了一种基于模糊方法的三个阶段的自适应非线性模型预测控制的新技术。在提出的方法中,在第一阶段,在每个控制步骤中从模糊系统获得预测和控制范围。在开发新控制器的优化阶段之前,采用另一个模糊系统来确定权重因子。所提出的控制器在每个控制步骤中给出了模型预测控制(MPC)的参数,以提高非线性系统的性能。将所提出的控制方案与传统的MPC和通用模型控制进行比较,以控制MED-TVC过程。为了评估所提出控制器的稳定性和鲁棒性,在不存在和存在干扰的情况下,对这三种所提出控制器的性能进行了研究。结果表明,基于模糊方法的新型自适应控制器在设定点跟踪和抑制干扰方面具有比其他两个控制器更好的性能,且IAE准则较低。此外,与传统的MPC相比,自适应MPC的平均计算时间减少了34%。 (C)2019富兰克林研究所。由Elsevier Ltd.出版。保留所有权利。

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