Hybrid Intelligent Formation Control Using PSO_GEN

Mehdi J. Marie, S. S. Mahdi, Esraa Y. Yahia
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引用次数: 1

Abstract

In this paper , hybrid intelligent formation control by using particle swarm optimization and genetic algorithms is studied .,Firstly a survey about the formation control is presented .Then a close loop system is selected to be controlled by optimized PID controller. The PID optimized in three methods which are particle swarm optimization , genetic algorithm and combination of PSO and genetic algorithms .The fitness function used in all three cases is integral square error (ISE) .Different swarm numbers and steps are used for comparison .The simulation results show that combination method has a better performance than both PSO and GA as it produces minimum error.
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基于PSO_GEN的混合智能编队控制
本文研究了基于粒子群算法和遗传算法的混合智能群体控制,首先对群体控制进行了概述,然后选择了一个闭环系统,通过优化后的PID控制器进行控制。采用粒子群算法、遗传算法和粒子群算法与遗传算法相结合的三种方法对PID进行优化,三种方法的适应度函数均为积分平方误差(ISE),并采用不同的群数和步长进行比较,仿真结果表明,粒子群算法与遗传算法相结合的方法产生的误差最小,性能优于粒子群算法和遗传算法。
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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