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Type-2 Fuzzy Logic Controllers Based Genetic Algorithm for the Position Control of DC Motor

机译:基于类型2模糊逻辑控制器的遗传算法的直流电动机位置控制

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摘要

Type-2 fuzzy logic systems have recently been utilized in many control processes due to their ability to model uncertainty. This research article proposes the position control of (DC) motor. The proposed algorithm of this article lies in the application of a genetic algorithm interval type-2 fuzzy logic controller (GAIT2FLC) in the design of fuzzy controller for the position control of DC Motor. The entire system has been modeled using MATLAB R11a. The performance of the proposed GAIT2FLC is compared with that of its corresponding conventional genetic algorithm type-1 FLC in terms of several performance measures such as rise time, peak overshoot, settling time, integral absolute error (IAE) and integral of time multiplied absolute error (ITAE) and in each case, the proposed scheme shows improved performance over its conventional counterpart. Extensive simulation studies are conducted to compare the response of the given system with the conventional genetic algorithm type-1 fuzzy controller to the response given with the proposed GAIT2FLC scheme.
机译:由于类型2模糊逻辑系统具有对不确定性进行建模的能力,因此最近已在许多控制过程中使用它们。本文提出了直流电动机的位置控制方法。本文提出的算法在于遗传算法区间2型模糊逻辑控制器(GAIT2FLC)在直流电动机位置控制模糊控制器设计中的应用。整个系统已使用MATLAB R11a建模。拟议的GAIT2FLC的性能与相应的常规遗传算法类型1 FLC的性能在几个性能指标方面进行了比较,例如上升时间,峰值超调,建立时间,积分绝对误差(IAE)和时间乘以绝对误差的积分(ITAE),并且在每种情况下,所提出的方案都比传统方案具有更高的性能。进行了广泛的仿真研究,以比较给定系统与传统遗传算法1型模糊控制器的响应与拟议GAIT2FLC方案给定的响应。

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