多目标螺旋动态算法及其在PD设计中的应用

A. Nasir, A. Azwan, A. M. Ashraf, M. J. M. Falfazli
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引用次数: 6

摘要

提出了一种新的多目标螺旋动态优化(MOSDA)算法。它是单目标类型SDA的扩展版本。将非支配排序遗传算法II (NSGAII)中的非支配排序(non - dominant sorting, NS)方法引入到SDA中,开发其多目标(MO)型算法。SDA具有良好的精英化策略和简单的结构。另一方面,NS是MO型算法发展良好的Pareto Front (PF)特性的快速策略。采用各种基准函数对本文提出的算法进行了测试,用于测试一种新开发的MO算法。作为测试的结果,给出了一个PF图。并将其应用于倒立摆(IP)系统的比例导数(PD)控制器参数优化。给出了IP的时域响应,以显示优化后控制器的性能。结果表明,与NSGAII相比,MOSDA在寻找PF和求解扩展方面具有更好的性能。在实际应用中,两种算法都能很好地优化PD并控制系统。基于mosda的PD控制的IP具有较好的上升时间。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A multi-objective Spiral Dynamic algorithm and its application for PD design
This paper presents a novel multi-objective Spiral Dynamic Optimization (MOSDA) algorithm. It is an extended version of a single objective type SDA. A Non-dominated sorting (NS) approach from Non-dominated Sorting Genetic Algorithm II (NSGAII) is adopted into SDA to develop its multi-objective (MO) type algorithm. SDA has a good elitism strategy and a simple structure. On the other hand, NS is a fast strategy to develop good Pareto Front (PF) characteristics for MO type algorithm. The proposed algorithm is tested with various benchmark functions used to test a newly developed MO algorithm. A PF graph is presented as a result of the test. Moreover, it is adopted to optimize parameters of ProportionalDerivative (PD) controller for an Inverted Pendulum (IP) system. Time-domain response of the IP is presented to show performance of the optimized controller. Result presented in this paper shows that MOSDA has a better performance in terms of finding PF and solution spread when tested with benchmark functions compared to NSGAII. In terms of its application in solving a real problem, both algorithms successfully optimize the PD and control the system very well. IP controlled by MOSDA-based PD shows better rise time.
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