Please wait a minute...
Chin. Phys. B, 2011, Vol. 20(12): 120503    DOI: 10.1088/1674-1056/20/12/120503
GENERAL Prev   Next  

A novel robust proportional-integral (PI) adaptive observer design for chaos synchronization

Mahdi Pourgholi and Vahid Johari Majd
Intelligent Control Systems Laboratory, School of Electrical and Computer Engineering, Tarbiat Modares University, Tehran, Iran
Abstract  In this paper, chaos synchronization in the presence of parameter uncertainty, observer gain perturbation and exogenous input disturbance is considered. A nonlinear non-fragile proportional-integral (PI) adaptive observer is designed for the synchronization of chaotic systems; its stability conditions based on the Lyapunov technique are derived. The observer proportional and integral gains, by converting the conditions into linear matrix inequality (LMI), are optimally selected from solutions that satisfy the observer stability conditions such that the effect of disturbance on the synchronization error becomes minimized. To show the effectiveness of the proposed method, simulation results for the synchronization of a Lorenz chaotic system with unknown parameters in the presence of an exogenous input disturbance and abrupt gain perturbation are reported.
Keywords:  adaptive observer      H-infinity design      chaos synchronization      linear matrix inequality  
Received:  26 February 2011      Revised:  30 June 2011      Accepted manuscript online: 
PACS:  05.45.-a (Nonlinear dynamics and chaos)  

Cite this article: 

Mahdi Pourgholi and Vahid Johari Majd A novel robust proportional-integral (PI) adaptive observer design for chaos synchronization 2011 Chin. Phys. B 20 120503

[1] Zhu Z and Leung H 2000 emphIEEE Trans. Circ. Sys. I: emphFund. Theor. Appl. 47 1072
[2] Ayati M and Khaloozadeh H 2009 emphChaos, Solitions and Fractals 42 2473
[3] Santoboni G, Yu A and Nijmeijer H 2001 emphPhys. Lett. A 291 265
[4] Hu J, Chen S and Chen L 2005 emphPhys. Lett. A 339 455
[5] Bastin G and Gevers M R 1988 emphIEEE Trans. Autom. Control 33 650
[6] Marino R 1990 emphIEEE Trans. Autom. Control 35 1054
[7] Marino R and Tomei P 1992 emphIEEE Trans. Autom. Control 37 1239
[8] Marino R and Tomei P 1995 emphIEEE Trans. Autom. Control 40 1300
[9] Rajamani R and Hedrick J K 1995 emphIEEE Trans. Control Sys. Technol. 3 86
[10] Zhang J, Xu H B and Wang H J 2006 emphChin. Phys. 15 953
[11] Li S, Xu W and Li R 2007 emphPhys. Lett. A 361 98
[12] Hu J and Zhang Q J 2008 emphChin. Phys. B 17 503
[13] Marino R, Santosuosso G L and Tomei P 2001 emphIEEE Trans. Autom. Control 46 967
[14] Jung J, Hul K, Fathy H K and Srein J L 2006 emphAmerican Control Conf. p. 3637
[15] Jung J, Hwang J and Huh K 2007 emphProc. ACC. p. 1931
[16] Jeong C S, Yaz E E, Bahakeem A and Yaz Y I 2006 emphProc. ACC. p. 111
[17] Keel L H and Bhattacharyya S P 1997 emphIEEE Trans. Autom. Control 42 1098
[18] Jeong C S, Yaz E E and Yaz Y I 2008 emphIEEE Multi-conference on Systems and Control p. 942
[19] Jeong C S, Yaz E E and Yaz Y I 2007 emphIEEE Conf. CDC p. 1227
[20] Pourgholi M and Majd V J 2009 emphIEEE Multi-conference on Systems and Control p. 643
[21] Pourgholi M and Majd V J 2011 emphSpringer-Circuits Sys. Signal Process. DOI 10.1007/s00034-011-9320-y
[22] Boyd S, Ghaoui L E, Feron E and Balakrishnan V 1994 emphLinear Matrix Inequalities in System and Control Theory (Philadelphia: Society for Industrial and Applied Mathematics)
[23] Chen F and Zhang W 2007 emphNonlinear Analysis 67 3384
[24] Krstic M, Kanellakopoulos I and Kokotovic P 1995 emphNonlinear and Adaptive Control Design (New York: John Wiley and Sons)
[25] Lofberg J 2004 emphIEEE Int. Symp. Comput. Aided Contol Syst. Design Conf. p. 284
[26] Gahinet P, Nemirovski A, Laub A and Chilai M 1995 emphLMI Control Toolbox User's Guide (Massachusetts: The Mathworks)
[1] Multi-target ranging using an optical reservoir computing approach in the laterally coupled semiconductor lasers with self-feedback
Dong-Zhou Zhong(钟东洲), Zhe Xu(徐喆), Ya-Lan Hu(胡亚兰), Ke-Ke Zhao(赵可可), Jin-Bo Zhang(张金波),Peng Hou(侯鹏), Wan-An Deng(邓万安), and Jiang-Tao Xi(习江涛). Chin. Phys. B, 2022, 31(7): 074205.
[2] Adaptive synchronization of chaotic systems with less measurement and actuation
Shun-Jie Li(李顺杰), Ya-Wen Wu(吴雅文), and Gang Zheng(郑刚). Chin. Phys. B, 2021, 30(10): 100503.
[3] Robust pre-specified time synchronization of chaotic systems by employing time-varying switching surfaces in the sliding mode control scheme
Alireza Khanzadeh, Mahdi Pourgholi. Chin. Phys. B, 2016, 25(8): 080501.
[4] Robust H control for uncertain Markovian jump systems with mixed delays
R Saravanakumar, M Syed Ali. Chin. Phys. B, 2016, 25(7): 070201.
[5] Robust H control of uncertain systems with two additive time-varying delays
M. Syed Ali, R. Saravanakumar. Chin. Phys. B, 2015, 24(9): 090202.
[6] Prescribed performance synchronization for fractional-order chaotic systems
Liu Heng (刘恒), Li Sheng-Gang (李生刚), Sun Ye-Guo (孙业国), Wang Hong-Xing (王宏兴). Chin. Phys. B, 2015, 24(9): 090505.
[7] Chaotic synchronization in Bose–Einstein condensate of moving optical lattices via linear coupling
Zhang Zhi-Ying (张志颖), Feng Xiu-Qin (冯秀琴), Yao Zhi-Hai (姚治海), Jia Hong-Yang (贾洪洋). Chin. Phys. B, 2015, 24(11): 110503.
[8] Stability analysis of Markovian jumping stochastic Cohen–Grossberg neural networks with discrete and distributed time varying delays
M. Syed Ali. Chin. Phys. B, 2014, 23(6): 060702.
[9] Improved delay-dependent robust H control of an uncertain stochastic system with interval time-varying and distributed delays
M. Syed Ali, R. Saravanakumar. Chin. Phys. B, 2014, 23(12): 120201.
[10] Finite-time sliding mode synchronization of chaotic systems
Ni Jun-Kang (倪骏康), Liu Chong-Xin (刘崇新), Liu Kai (刘凯), Liu Ling (刘凌). Chin. Phys. B, 2014, 23(10): 100504.
[11] Generalized projective synchronization of the fractional-order chaotic system using adaptive fuzzy sliding mode control
Wang Li-Ming (王立明), Tang Yong-Guang (唐永光), Chai Yong-Quan (柴永泉), Wu Feng (吴峰). Chin. Phys. B, 2014, 23(10): 100501.
[12] Cluster exponential synchronization of a class of complex networks with hybrid coupling and time-varying delay
Wang Jun-Yi (王军义), Zhang Hua-Guang (张化光), Wang Zhan-Shan (王占山), Liang Hong-Jing (梁洪晶). Chin. Phys. B, 2013, 22(9): 090504.
[13] Continuous-time chaotic systems:Arbitrary full-state hybrid projective synchronization via a scalar signal
Giuseppe Grassi. Chin. Phys. B, 2013, 22(8): 080505.
[14] Chaos synchronization of a chain network based on a sliding mode control
Liu Shuang (柳爽), Chen Li-Qun (陈立群). Chin. Phys. B, 2013, 22(10): 100506.
[15] Novel delay dependent stability analysis of Takagi–Sugeno fuzzy uncertain neural networks with time varying delays
M. Syed Ali . Chin. Phys. B, 2012, 21(7): 070207.
No Suggested Reading articles found!