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Design of fuzzy controller based on data mining

机译:基于数据挖掘的模糊控制器设计

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The design of existing empirical fuzzy controller is based on the practical experience or expert knowledge, which has obvious subjectivity and strong uncertainty. Meanwhile, the value of large process data that imply various patterns and much useful information is ignored. Aiming at these problems, one type of design method of fuzzy controller based on data driven is proposed in this paper, which extracts fuzzy subsets and fuzzy rules from the test data directly. Especially, an improved data mining(iDM) method of rule base is presented. Using a second-order plus time delay model, a series of simulation experiments are conducted and the results show that the method is feasible and effective. As a contrast to the PID controller and the general fuzzy controller, the control effect of this proposed method is demonstrated and the superior performance is verified.
机译:现有的经验模糊控制器的设计是基于实践经验或专家知识,具有明显的主观性和较强的不确定性。同时,忽略了包含各种模式和大量有用信息的大型过程数据的价值。针对这些问题,提出了一种基于数据驱动的模糊控制器设计方法,该方法直接从测试数据中提取模糊子集和模糊规则。特别是,提出了一种改进的规则库数据挖掘方法。利用二阶加时滞模型进行了一系列的仿真实验,结果表明该方法是可行和有效的。与PID控制器和通用模糊控制器相比,该方法的控制效果得到了证明,并证明了其优越的性能。

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