Type-2 Fuzzy PD Controller Tuning using Quantum-inspired Evolutionary algorithm

S. Cho, Joon-Woo Lee, Jujang Lee
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引用次数: 1

Abstract

Fuzzy Logic Controller (FLC) is used widely since it can control non-linear system which are hard to be solved by conventional control method. The design of fuzzy logic controller (FLC), however, has some difficulties such as formation of the fuzzy rules, tuning of the scale factor and the rule explosion. The decision of fuzzy rules are not easy since the fuzzy rule is formed by the expert's experience. Finding suitable scale factor is difficult as conventional PID ones since it takes long time. As input increase, fuzzy rule increase exponentially. To overcome these problems, the information integration is used for preventing the rule explosion and fixed the fuzzy rules and scaling factor is used. we proposed Fuzzy PD Controller Tuning method by using Quantum-inspired Evolution algorithm (QEA). This proposed method also was demonstrated by control of double inverted pendulum.
基于量子进化算法的2型模糊PD控制器整定
模糊逻辑控制器(FLC)由于能够控制传统控制方法难以解决的非线性系统而得到广泛应用。然而,模糊控制器的设计存在模糊规则的形成、比例因子的调整和规则爆炸等问题。由于模糊规则是由专家的经验形成的,因此模糊规则的确定并不容易。与传统PID相比,寻找合适的比例因子比较困难,耗时较长。随着输入的增加,模糊规则呈指数增长。为了克服这些问题,采用信息集成的方法防止规则爆炸,并采用固定模糊规则和比例因子的方法。提出了一种基于量子进化算法的模糊PD控制器整定方法。通过对双倒立摆的控制,验证了该方法的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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