Genetic Iterative Feedback Tuning (GIFT) Method for Fuzzy Control System Development

R. Precup, S. Preitl
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引用次数: 7

Abstract

This paper proposes an original iterative feedback tuning (IFT) method employing genetic algorithms to develop a class of fuzzy control systems. The approach is based on using the linear case results from the original IFT method and on replacing the parameter update law by genetic algorithms. Then, these results are transferred to the fuzzy case in terms of the modal equivalence principle resulting in an attractive development method referred to as genetic iterative feedback tuning (GIFT). The GIFT method is applied to the development of fuzzy control systems with PI-fuzzy controllers dedicated to a class of integral type servo systems, where the linear case is focused on the IFT method in connection with the extended symmetrical optimum method to obtain the initial values of the linear PI controller parameters. Real-time experimental results corresponding to a fuzzy controlled nonlinear servo system are presented to validate the development method
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遗传迭代反馈整定方法在模糊控制系统开发中的应用
本文提出了一种利用遗传算法开发一类模糊控制系统的迭代反馈整定(IFT)方法。该方法基于利用原始IFT方法的线性情况结果,并用遗传算法代替参数更新律。然后,根据模态等效原理将这些结果转移到模糊情况下,从而产生一种有吸引力的开发方法,即遗传迭代反馈调谐(GIFT)。将GIFT方法应用于一类积分型伺服系统的PI-模糊控制器模糊控制系统的开发,其中线性案例集中在IFT方法与扩展对称最优方法相结合,以获得线性PI控制器参数的初值。给出了一个模糊控制非线性伺服系统的实时实验结果,验证了该开发方法
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