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中文摘要：
混沌蚂蚁群算法是受自然界真实蚂蚁的混沌行为和自组织行为启发而产生的一种基于群智能理论的优化算法。介绍了该算法的基本原理,并在对其进行算法分析的基础之上,提出了一种改进的混沌蚂蚁群算法,该改进算法采用全面学习策略和一种简单的精细搜索策略以提高算法的性能。数值实验表明,该改进算法的收敛精度和结果稳定性优于混沌蚂蚁群算法。在此基础上,将其应用于对PID控制器参数的优化,仿真显示其结果优于混沌蚂蚁群算法。
英文摘要：
The chaotic ant swarm algorithm （CAS） is an optimization algorithm based on swarm intelligence theory and it is inspired by the chaotic and self-organizing behavior of the ants in nature. Based on the analysis of the properties of the CAS, this paper proposes an improved chaotic ant swarm algorithm （ICAS）. A comprehensive learning strategy and a simple refinement searching strategy are added to the CAS in order to improve its performance. Nu- merical experiment results are given to demonstrate that the improved algorithm is superior to CAS in calculation accuracy and convergence stability. Based on these test results, the ICAS is used to optimize the PID controller parameters. Simulation shows that its optimization results are better than that of CAS.
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