基于量子并行粒子群优化算法的分数阶混沌系统参数估计

黄宇; 刘玉峰; 彭志敏; 丁艳军

doi:10.7498/aps.64.030505

摘要

分数阶混沌系统参数估计的本质是多维参数优化问题, 其对于实现分数阶混沌控制与同步至关重要. 提出一种基于量子并行特性的粒子群优化新算法, 用于解决分数阶混沌的系统参数估计问题. 利用量子计算的并行特性, 设计出了一种新的量子编码, 使每代运算的可计算次数呈指数增加. 在此基础上, 构建了由量子当前旋转角、个体最优旋转角和全局最优旋转角共同组成的粒子演化方程, 以约束粒子在量子空间中的运动行为, 使算法的搜索能力得到了较大提高. 以分数阶Lorenz混沌系统和分数阶Chen混沌系统的参数估计为例, 进行了未知参数估计的数值仿真, 结果显示本算法具有良好的有效性、鲁棒性和通用性.

关键词:

Abstract

Parameter estimation for fractional-order chaotic systems is a multi-dimensional optimization problem, which is one of the important issues in fractional-order chaotic control and synchronization. With the characteristic of quantum parallel, a new quantum parallel particle swarm optimization algorithm is proposed for solving the problem of parameter estimation in fractional-order chaotic systems. A new method of quantum coding is presented with quantum parallel characteristic which can make the calculation number of each generation increase exponentially. On the basis of this method, a particle evolution equation composed of quantum current rotation angle, individual optimal rotation angle, and global optimum rotation angle is proposed, which can restraint the behavior of particles in quantum space, and also can improve the search capability of the algorithm. Numerical simulations of the fractional-order Lorenz system and the fractional-order Chen system are conducted and the results demonstrate the effectiveness, robustness and versatility of the proposed algorithm.

Keywords:

作者及机构信息

1.
清华大学热能系, 电力系统与发电设备控制与仿真国家重点实验室, 北京 100084;

2.
华北电力大学控制与计算机工程学院, 保定 071003

基金项目: 国家自然科学基金(批准号: 51206086, 51176085)和中央高校基本科研业务费专项资金(批准号: 12MS117)资助的课题.

Authors and contacts

1.
State Key Laboratory of Power Systems, Department of Thermal Engineering, Tsinghua University, Beijing 100084, China;

2.
School of Control and Computer Engineering, North China Electric Power University, Baoding 071003, China

Funds: Project supported by the National Science Foundation of China (Grant Nos. 51206086, 51176085), and the Fundamental Research Funds for the Central Universities (Grant No. 12MS117).

参考文献

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[12]	Wang L, He W P, Wan S Q, Liao J L, He T 2014 Acta Phys. Sin. 63 019203 (in Chinese) [王柳, 何文平, 万仕全, 廖乐健, 何涛 2014 物理学报 63 019203]
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施引文献

[1]	Sheikhan M, Shahnazi R, Garoucy S 2013 Neural Computing and Application 22 361
[2]	Gandomi A H, Yun G J, Yang X S, Talatahari S 2013 Communications in Nonlinear Science and Numerical Simulation 18 327
[3]	Yassi M, Yassi A, Yaghoobi M 2014 Iranian Conference on Intelligent Bam, Iran, February 4-6 2014 p1
[4]	Gao X 2007 Ph. Dissertation D (Xian: Xidian University)) (in Chinese) [高心2005 博士学位论文(西安: 电子科技大学)]
[5]	Ho W H, Chou J H, Guo C Y 2010 Nonlinear Dyn. 61 29
[6]	Yang K Q, Maginu K J, Nomura H 2009 International Journal of Computer Mathematics 86 2225
[7]	Chang, W D. 2007 Chaos Soliton. Fract. 32 1469
[8]	Parlitz U, Junge L 1996 Phys. Rev. E 54 6253
[9]	Wang L, Ye X, Ling P L 2011 Expert System with Applications 38 3238
[10]	Long W, Jiao J J 2012 Acta Phys. Sin. 61 110507 (in Chinese) [龙文, 焦建军 2012 物理学报 61 110507]
[11]	Lin J, Xu L 2013 Acta Phys. Sin. 62 030505 (in Chinese) [林剑, 许力 2013 物理学报 62 030505]
[12]	Wang L, He W P, Wan S Q, Liao J L, He T 2014 Acta Phys. Sin. 63 019203 (in Chinese) [王柳, 何文平, 万仕全, 廖乐健, 何涛 2014 物理学报 63 019203]
[13]	Wang D F, Zhang J Y, Wang X Y 2013 Chin. Phys. B 22 100504
[14]	Li A P, Liu G R, Shen X Q 2013 Computer Engineering and Applications 49 4 (in Chinese) [李安平, 刘国荣, 沈细群 2013 计算机工程应用 49 4]
[15]	Nielsen M, Chuang I 2010 Quantum Computation and Quantum Information (London: Cambridge University Press) pp 61-75
[16]	Li S Y, Li P C 2007 Chinese Jounal of Quantum Electronics 24 569 (in Chinese) [李士勇, 李盼池 2007 量子电子学报 24 569]
[17]	Caponetto R 2010 Fractional order systems: modeling and control applications (World Scientific) pp 62-65
[18]	He Q, Wang L, Liu B 2007 Chaos Soliton. Fract. 34 645
[19]	Li C, Chen G 2004 Chaos Soliton. Fract. 22 549

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