Search

Article

x

留言板

尊敬的读者、作者、审稿人, 关于本刊的投稿、审稿、编辑和出版的任何问题, 您可以本页添加留言。我们将尽快给您答复。谢谢您的支持!

姓名
邮箱
手机号码
标题
留言内容
验证码

Feedback compensation control on chaotic system with uncertainty based on radial basis function neural network

Zeng Zhe-Zhao

Feedback compensation control on chaotic system with uncertainty based on radial basis function neural network

Zeng Zhe-Zhao
PDF
Get Citation

(PLEASE TRANSLATE TO ENGLISH

BY GOOGLE TRANSLATE IF NEEDED.)

  • For the problem of controlling uncertain chaotic systems, a method of feedback compensation control based on the radial basis function neural network (RBFNN) is studied. In the proposed method, dynamic properties of chaotic system is first trained by RBFNN, and then feedback compensation control for chaotic system is implemented using trained good RBFNN model. The characteristics of this method is that this method can quickly track any given reference signal with on requirement for any mathematic model of controlled chaos system. The numerical simulation results show that the proposed control method not only has the fast response speed, high control accuracy, but also has a stronger ability to suppress parameter perturbation and to resist interference to chaos system.
    • Funds: Project supported by the National Natural Science Foundation of China (Grant No. 61040049), the Natural Science Foundation of Hunan Province, China (Grant No. 11JJ6064) and Key Laboratory of Intelligent Power Grid Operation and Control of Human Province, China.
    [1]

    Colet P, Roy R 1994 Opt. Lett. 19 2056

    [2]

    Sugawara T, Tachikawa M, Tsukamoto T, Shimizu T 1994 Phys. Rev. Lett. 72 3502

    [3]

    Lu J A, Wu X Q, Lü J H 2002 Phys. Lett. A 305 365

    [4]

    Zhu S P, Qian F C, Liu D 2010 Acta Phys. Sin. 59 2250 (in Chinese) [朱少平, 钱富才, 刘丁 2010 物理学报 59 2250]

    [5]

    Ott E, Grebogi C, Yorke A J 1990 Phys. Rev. Lett. 64 1196

    [6]

    Pyragas K 1992 Phys. Lett. A 170 421

    [7]

    Pyragas K 1993 Phys. Lett. A 180 99

    [8]

    Tang G N, Luo X S, Kong L J 2000 Acta Phys. Sin. 49 30 (in Chinese) [唐国宁, 罗晓曙, 孔令江 2000 物理学报 49 30]

    [9]

    Guan X P, Fan Z P, Peng H P, Wang Y Q 2001 Acta Phys. Sin. 50 2108 (in Chinese) [关新平, 范正平, 彭海朋, 王益群 2001 物理学报 50 2108]

    [10]

    Song Y Z, Zhao G Z, Qi D L 2007 Control Theory and Applications 24 795 (in Chinese) [宋运忠, 赵光宙, 齐冬莲 2007 控制理论与应用 24 795]

    [11]

    Gao X, Liu X W 2007 Acta Phys. Sin. 56 84 (in Chinese) [高心, 刘兴文 2007 物理学报56 84]

    [12]

    Wang F Q, Liu C X 2006 Acta Phys. Sin. 55 5055 ( in Chinese) [王发强, 刘崇新 2006 物理学报 55 5055]

    [13]

    Chen G P, Hao J B 2009 Acta Phys. Sin. 58 2914 (in Chinese) [陈光平, 郝加波 2009 物理学报 58 2914]

    [14]

    Wang X F, Xue H J, Si S K, Yao Y T 2009 Acta Phys. Sin. 58 3729 (in Chinese) [王晓锋, 薛红军, 司守奎, 姚跃亭 2009 物理学报 58 3729]

    [15]

    Luo X H, Li H Q, Chen Q H 2009 Acta Phys. Sin. 58 7532 (in Chinese) [罗小华, 李华青, 陈秋华 2009 物理学报 58 7532]

    [16]

    Liu Z H, Zhang Y J, Zhang J, Wu J H 2011 Acta Phys. Sin. 60 019501 (in Chinese) [刘朝华, 张英杰, 章兢, 吴建辉 2011 物理学报 60 019501

    [17]

    Li L X, Peng H P, Lu H B 2001 Acta Phys. Sin. 50 629 (in Chinese) [李丽香, 彭海朋, 卢辉斌 2001 物理学报 50 629]

    [18]

    Wang X Y, Shi Q J 2005 Acta Phys. Sin. 54 5591 (in Chinese) [王兴元, 石其江 2005 物理学报 54 5591]

    [19]

    Ning D, Lu J A 2005 Acta Phys. Sin. 54 4590 (in Chinese) [宁娣, 陆君安 2005 物理学报 54 4590]

    [20]

    Wu W G, Gu T X 2000 Acta Phys. Sin. 49 1922 (in Chinese) [伍维根, 古天祥2000 物理学报 49 1922]

    [21]

    Li G H, Xu D M, Zhou S P 2003 Acta Phys. Sin. 52 181 (in Chinese) [李国辉, 徐得名, 周世平 2003 物理学报 52 181]

    [22]

    Liu D, Ren H P, Kong Z Q 2003 Acta Phys. Sin. 52 531 (in Chinese) [刘丁, 任海鹏, 孔志强 2003 物理学报 52 531]

  • [1]

    Colet P, Roy R 1994 Opt. Lett. 19 2056

    [2]

    Sugawara T, Tachikawa M, Tsukamoto T, Shimizu T 1994 Phys. Rev. Lett. 72 3502

    [3]

    Lu J A, Wu X Q, Lü J H 2002 Phys. Lett. A 305 365

    [4]

    Zhu S P, Qian F C, Liu D 2010 Acta Phys. Sin. 59 2250 (in Chinese) [朱少平, 钱富才, 刘丁 2010 物理学报 59 2250]

    [5]

    Ott E, Grebogi C, Yorke A J 1990 Phys. Rev. Lett. 64 1196

    [6]

    Pyragas K 1992 Phys. Lett. A 170 421

    [7]

    Pyragas K 1993 Phys. Lett. A 180 99

    [8]

    Tang G N, Luo X S, Kong L J 2000 Acta Phys. Sin. 49 30 (in Chinese) [唐国宁, 罗晓曙, 孔令江 2000 物理学报 49 30]

    [9]

    Guan X P, Fan Z P, Peng H P, Wang Y Q 2001 Acta Phys. Sin. 50 2108 (in Chinese) [关新平, 范正平, 彭海朋, 王益群 2001 物理学报 50 2108]

    [10]

    Song Y Z, Zhao G Z, Qi D L 2007 Control Theory and Applications 24 795 (in Chinese) [宋运忠, 赵光宙, 齐冬莲 2007 控制理论与应用 24 795]

    [11]

    Gao X, Liu X W 2007 Acta Phys. Sin. 56 84 (in Chinese) [高心, 刘兴文 2007 物理学报56 84]

    [12]

    Wang F Q, Liu C X 2006 Acta Phys. Sin. 55 5055 ( in Chinese) [王发强, 刘崇新 2006 物理学报 55 5055]

    [13]

    Chen G P, Hao J B 2009 Acta Phys. Sin. 58 2914 (in Chinese) [陈光平, 郝加波 2009 物理学报 58 2914]

    [14]

    Wang X F, Xue H J, Si S K, Yao Y T 2009 Acta Phys. Sin. 58 3729 (in Chinese) [王晓锋, 薛红军, 司守奎, 姚跃亭 2009 物理学报 58 3729]

    [15]

    Luo X H, Li H Q, Chen Q H 2009 Acta Phys. Sin. 58 7532 (in Chinese) [罗小华, 李华青, 陈秋华 2009 物理学报 58 7532]

    [16]

    Liu Z H, Zhang Y J, Zhang J, Wu J H 2011 Acta Phys. Sin. 60 019501 (in Chinese) [刘朝华, 张英杰, 章兢, 吴建辉 2011 物理学报 60 019501

    [17]

    Li L X, Peng H P, Lu H B 2001 Acta Phys. Sin. 50 629 (in Chinese) [李丽香, 彭海朋, 卢辉斌 2001 物理学报 50 629]

    [18]

    Wang X Y, Shi Q J 2005 Acta Phys. Sin. 54 5591 (in Chinese) [王兴元, 石其江 2005 物理学报 54 5591]

    [19]

    Ning D, Lu J A 2005 Acta Phys. Sin. 54 4590 (in Chinese) [宁娣, 陆君安 2005 物理学报 54 4590]

    [20]

    Wu W G, Gu T X 2000 Acta Phys. Sin. 49 1922 (in Chinese) [伍维根, 古天祥2000 物理学报 49 1922]

    [21]

    Li G H, Xu D M, Zhou S P 2003 Acta Phys. Sin. 52 181 (in Chinese) [李国辉, 徐得名, 周世平 2003 物理学报 52 181]

    [22]

    Liu D, Ren H P, Kong Z Q 2003 Acta Phys. Sin. 52 531 (in Chinese) [刘丁, 任海鹏, 孔志强 2003 物理学报 52 531]

  • [1] Zhang Jun-Feng, Hu Shou-Song. Chaotic time series prediction based on RBF neural networks with a new clustering algorithm. Acta Physica Sinica, 2007, 56(2): 713-719. doi: 10.7498/aps.56.713
    [2] Han Min, Xu Mei-Ling. A hybrid prediction model of multivariate chaotic time series based on error correction. Acta Physica Sinica, 2013, 62(12): 120510. doi: 10.7498/aps.62.120510
    [3] Sima Wen-Xia, Liu Fan, Sun Cai-Xin, Liao Rui-Jin, Yang Qing. Chaos control of ferroresonance system based on improved RBF neural network. Acta Physica Sinica, 2006, 55(11): 5714-5720. doi: 10.7498/aps.55.5714
    [4] Liu Ding, Ren Hai-Peng, Kong Zhi-Qiang. Control of chaos solely based on RBF neural network without an analytical model. Acta Physica Sinica, 2003, 52(3): 531-535. doi: 10.7498/aps.52.531
    [5] Guo Hui-Jun, Liu Jun_Hua. Chaos control of Lorenz system via RBF neuralnetwork sliding mode controller. Acta Physica Sinica, 2004, 53(12): 4080-4086. doi: 10.7498/aps.53.4080
    [6] Liu Xian, Ma Bai-Wang, Liu Hui-Jun. Performance of closed-loop control of epileptiform spikes in neural mass models. Acta Physica Sinica, 2013, 62(2): 020202. doi: 10.7498/aps.62.020202
    [7] Zhang Xu-Dong, Zhu Ping, Xie Xiao-Ping, He Guo-Guang. A dynamic threshold value control method for chaotic neural networks. Acta Physica Sinica, 2013, 62(21): 210506. doi: 10.7498/aps.62.210506
    [8] HE GUO-GUANG, CAO ZHI-TONG. CONTROLLING CHAOS IN CHAOTIC NEURAL NETWORK. Acta Physica Sinica, 2001, 50(11): 2103-2107. doi: 10.7498/aps.50.2103
    [9] Miao Zhi-Qiang, Wang Yao-Nan. Robust adaptive radial wavelet neural network control for chaotic systems using backstepping design. Acta Physica Sinica, 2012, 61(3): 030503. doi: 10.7498/aps.61.030503
    [10] Wang Yao-Nan, Liu Zhu-Run, Zhou Shao-Wu, Tan Wen. . Acta Physica Sinica, 2002, 51(11): 2463-2466. doi: 10.7498/aps.51.2463
    [11] Tang Jia-Shi, Liu Su-Hua. Linear feedback control of Hopf bifurcation in Langford system. Acta Physica Sinica, 2007, 56(6): 3145-3151. doi: 10.7498/aps.56.3145
    [12] Lin Min, Huang Yong-Mei, Fang Li-Min. The feedback control of stochastic resonance in bistable system. Acta Physica Sinica, 2008, 57(4): 2041-2047. doi: 10.7498/aps.57.2041
    [13] Fan Li-Ming, Lü Ming-Tao, Huang Ren-Zhong, Gao Tian-Fu, Zheng Zhi-Gang. Investigation on the directed transport efficiency of feedback-control ratchet. Acta Physica Sinica, 2017, 66(1): 010501. doi: 10.7498/aps.66.010501
    [14] Lai Xin-Quan, Li Zu-He, Yuan Bing, Wang Hui, Ye Qiang, Zhao Yong-Rui. Control of chaos in double-loop current-mode DC/DC based on adaptive slope compensation. Acta Physica Sinica, 2010, 59(4): 2256-2263. doi: 10.7498/aps.59.2256
    [15] Chen Xuan, Gao Zi-You, Zhao Xiao-Mei, Jia Bin. Study on the two-lane feedback controled car-following model. Acta Physica Sinica, 2007, 56(4): 2024-2029. doi: 10.7498/aps.56.2024
    [16] Shi Zheng-Ping. Simple chaotic oscillator’s chaos behavior and its feedback control circuit design. Acta Physica Sinica, 2010, 59(9): 5940-5948. doi: 10.7498/aps.59.5940
    [17] Du Lin, Xu Wei, Jia Fei-Lei, Li Shuang. Control of gyro system based on lowpass filter function feedback. Acta Physica Sinica, 2007, 56(7): 3813-3819. doi: 10.7498/aps.56.3813
    [18] Zeng Zhe-Zhao, Lei Ni, Sheng Li-Zeng. Compensation control on chaotic systems with uncertainties based on polynomial basisfunctions model. Acta Physica Sinica, 2013, 62(15): 150506. doi: 10.7498/aps.62.150506
    [19] Yin Xiao-Zhou, Liu Yong. Suppression of spiral wave in the excitable media by using intermittent feedback scheme. Acta Physica Sinica, 2008, 57(11): 6844-6851. doi: 10.7498/aps.57.6844
    [20] Huang Li-Lian, Xin Fang, Wang Lin-Yu. Circuit implementation and control of a new fractional-order hyperchaotic system. Acta Physica Sinica, 2011, 60(1): 010505. doi: 10.7498/aps.60.010505
  • Citation:
Metrics
  • Abstract views:  1361
  • PDF Downloads:  675
  • Cited By: 0
Publishing process
  • Received Date:  18 August 2012
  • Accepted Date:  03 September 2012
  • Published Online:  05 February 2013

Feedback compensation control on chaotic system with uncertainty based on radial basis function neural network

  • 1. College of Electric and Information Engineering, Changsha University of Science and Technology, Changsha 410076, China
Fund Project:  Project supported by the National Natural Science Foundation of China (Grant No. 61040049), the Natural Science Foundation of Hunan Province, China (Grant No. 11JJ6064) and Key Laboratory of Intelligent Power Grid Operation and Control of Human Province, China.

Abstract: For the problem of controlling uncertain chaotic systems, a method of feedback compensation control based on the radial basis function neural network (RBFNN) is studied. In the proposed method, dynamic properties of chaotic system is first trained by RBFNN, and then feedback compensation control for chaotic system is implemented using trained good RBFNN model. The characteristics of this method is that this method can quickly track any given reference signal with on requirement for any mathematic model of controlled chaos system. The numerical simulation results show that the proposed control method not only has the fast response speed, high control accuracy, but also has a stronger ability to suppress parameter perturbation and to resist interference to chaos system.

Reference (22)

Catalog

    /

    返回文章
    返回