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Design and optimization of fuzzy controllers based on the operator's knowledge

机译:基于操作员知识的模糊控制器设计与优化

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摘要

Industrial processes are normally operated by skilled humans who have cumulative and logical information about the systems. Fuzzy control has been investigated for many applications. Intelligent control approaches based on fuzzy logic might be able to include human thinking. This article describes a modeling approach based upon an operator's knowledge without a mathematical model of the system and optimization of the controller. The test system applied was constructed to send a ball into the goal position using wind from two DC motors in a predefined path. A vision camera to mimic human eyes detects the ball's position. The system used in this experiment was difficult to model by mathematical methods, and could not easily be controlled by conventional methods. The controller is designed based on the input-output data as well as experimental knowledge obtained by trials, and optimized under predefined performance criteria.
机译:工业过程通常由熟练的技术人员操作,这些技术人员具有有关系统的累积和逻辑信息。对于许多应用已经研究了模糊控制。基于模糊逻辑的智能控制方法可能能够包含人类的思维。本文介绍了一种基于操作员知识的建模方法,而没有系统的数学模型和控制器的优化。所应用的测试系统构造为使用来自两个直流电动机的风以预定路径将球发送到球门位置。模仿人眼的视觉相机可以检测到球的位置。本实验中使用的系统难以通过数学方法进行建模,并且无法通过常规方法轻松控制。该控制器是根据输入输出数据以及通过试验获得的实验知识进行设计的,并在预定义的性能标准下进行了优化。

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