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New approach using ant colony optimization with ant set partition for fuzzy control design applied to the ball and beam system

机译:蚁群算法结合蚁群划分的模糊控制设计新方法应用于球与梁系统

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摘要

In this paper we describe the design of a fuzzy logic controller for the ball and beam system using a modified Ant Colony Optimization (ACO) method for optimizing the type of membership functions, the parameters of the membership functions and the fuzzy rules. This is achieved by applying a systematic and hierarchical optimization approach modifying the conventional ACO algorithm using an ant set partition strategy. The simulation results show that the proposed algorithm achieves better results than the classical ACO algorithm for the design of the fuzzy controller. (C) 2014 Elsevier Inc. All rights reserved.
机译:在本文中,我们描述了一种使用改进的蚁群优化(ACO)方法对球和梁系统进行模糊逻辑控制器设计的方法,以优化隶属函数的类型,隶属函数的参数和模糊规则。这是通过应用系统化和分层的优化方法来实现的,该方法使用蚂蚁集划分策略修改了常规ACO算法。仿真结果表明,所提出的算法在设计模糊控制器方面比经典的ACO算法取得了更好的效果。 (C)2014 Elsevier Inc.保留所有权利。

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