摘要
混沌系统控制与同步可通过优化方法设计控制律引导混沌系统轨道来实现.类电磁机制优化算法(EM)是模拟电磁场带电粒子间吸引-排斥行为机制的一种启发式搜索方法.目前还尚未在混沌系统控制与同步问题中得到应用.本文提出一种混合类电磁机制优化算法(HEM)用于求解该优化问题,该方法采用修改的类电磁机制算法(REM)与差分进化算法(DE)相融合平衡算法对解空间的全局探索和局部开发能力,基准函数测试表明混合算法改善了全局搜索能力及求解可靠性.在此基础上,采用HEM算法引导混沌系统的轨道,搜索施加于系统的小扰动使其轨迹在短时间内跟踪到目标区域:再将混沌系统的同步问题转化为在线轨道导引问题,采用HEM优化算法解决通过典型离散Henon映射为例,数值仿真结果表明了该方法是解决混沌系统控制与同步的一种有效方法.
By using optimization method, we can design the control law for controlling and synchronizing chaotic systems to operate onto the desired directional orbits of chaotic dynamical systems. The electromagnetism-like algorithna（EM） is a recta-heuristic optimization method which simulates the attraction-repulsion behavior of electrically charged particles in the process of approaching the desired points. To the best of our knowledge, there is no research work on EM for con- trol and synchronization of chaotic systems. In this paper, an effective hybrid electromagnetism-like algorithm（HEM） is presented to solve these optimization problems. The HEM combines the revised electromagnetism-like algorithm（REM） and the differential evolutionary algorithm（DE） to strive for a well balance between the global exploration and the local ex- ploitation. The experimental results of benchmark functions show that this hybrid configuration greatly improves both the global optimization performance and the reliability performance. The proposed HEM has been applied to guide the orbits of discrete chaotic systems towards the desired target region within a short period of time, under a small bounded perturba- tion. Moreover, the synchronization of chaotic systems can be considered a problem of online guiding of orbits, solved by HEM algorithm. Numerical simulation results on the Henon mapping demonstrate the effectiveness of this hybrid.
出处
《控制理论与应用》
EI
CAS
CSCD
北大核心
2011年第7期1009-1014,共6页
Control Theory & Applications
基金
国家"863"计划重点资助项目(2008AA042602)
国家自然科学基金资助项目(61075078)
关键词
类电磁机制优化
差分进化
混沌系统
控制与同步
electromagnetism-like mechanism
differential evolution
chaotic system
control and synchronization
