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Swarm optimization based adaptive fuzzy control design from robust stability criteria

机译:基于鲁棒稳定性标准的基于群的优化自适应模糊控制设计

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摘要

In this paper, an adaptive fuzzy controller design methodology via MultiObjective Particle Swarm Optimization (MOPSO) based on robust stability criterion, is proposed. The plant to be controlled is modeled from its input-output experimental data considering a Takagi-Sugeno (TS) fuzzy NARX model, by using the fuzzy C-Means clustering algorithm (antecedent parameters estimation) and Weighted Recursive Least Squares (WRLS) algorithm (consequent parameters estimation). An adaptation mechanism as MOPSO problem for online tuning of a fuzzy model based digital PID controller parameters, based on the gain and phase margins specifications, is formulated. Experimental results for adaptive fuzzy digital PID control of a thermal plant with time varying delay is presented to illustrate the efficiency and applicability of the proposed methodology.
机译:本文提出了一种基于鲁棒稳定性标准的多目标粒子群优化(MOPSO)的自适应模糊控制器设计方法。 通过使用模糊C-Means聚类算法(前一种参数估计)和加权递归最小二乘(WRL)算法( 结果参数估计)。 根据增益和相位利润规范,制定了一种适应机制作为在线调整模糊模型的数字PID控制器参数的在线调整。 提出了具有时间变化延迟的热植物自适应模糊数字PID控制的实验结果,以说明所提出的方法的效率和适用性。

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