Robust adaptive finite-time synchronization of nonlinear resource management system

In this paper, the robust adaptive finite-time synchronization problem for nonlinear resource management system with uncertain parameters is discussed. By incorporating the finite-time stability theory and adaptive control approach, a novel and more general adaptive finite-time synchronization control scheme is proposed. The developed result depends on the terminal attractors, which can not only guarantee the robust synchronization of nonlinear resource management system with uncertain parameters in finite-time, but also can guarantee the uncertain parameters to be identified effectively simultaneously. Furthermore, due to the tuning parameters of the terminal attractors, a faster synchronization speed can be obtained by adjusting the parameters in the designed controllers. Finally, an illustrative example with simulation results is provided to illustrate and verify the effectiveness of the proposed control scheme. HighlightsThe robust adaptive finite-time synchronization problem for nonlinear energy resource management system is discussed in detail.A novel and more general robust adaptive finite-time synchronization controller designing scheme is proposed.The robust finite-time synchronization and identifications of the uncertain parameters can be realized in finite time simultaneously.By introducing the terminal attractors with tuning parameters, a faster synchronization speed can be also obtained.

[1]  Zuolei Wang Chaos synchronization of an energy resource system based on linear control , 2010 .

[2]  Carroll,et al.  Synchronization in chaotic systems. , 1990, Physical review letters.

[3]  Guanrong Chen,et al.  A time-varying complex dynamical network model and its controlled synchronization criteria , 2004, IEEE Trans. Autom. Control..

[4]  Jinde Cao,et al.  Synchronization Error Estimation and Controller Design for Delayed Lur'e Systems With Parameter Mismatches , 2012, IEEE Transactions on Neural Networks and Learning Systems.

[5]  Wilfrid Perruquetti,et al.  Finite-time stability and stabilization of time-delay systems , 2008, Syst. Control. Lett..

[6]  Rongwei Guo,et al.  Finite-time stabilization of a class of chaotic systems via adaptive control method , 2012 .

[7]  Xuerong Shi,et al.  Synchronization of a four-dimensional energy resource system via linear control , 2011 .

[8]  Haijun Jiang,et al.  Finite-time synchronization of delayed neural networks with Cohen-Grossberg type based on delayed feedback control , 2014, Neurocomputing.

[9]  Jinde Cao,et al.  Exponential synchronization of stochastic perturbed chaotic delayed neural networks , 2007, Neurocomputing.

[10]  Gao Tiegang,et al.  Robust finite time synchronization of chaotic systems , 2005 .

[11]  Jinde Cao,et al.  Global synchronization of delay-coupled genetic oscillators , 2009, Neurocomputing.

[12]  Jinde Cao,et al.  Exponential Synchronization of Hybrid Coupled Networks With Delayed Coupling , 2010, IEEE Transactions on Neural Networks.

[13]  Yiguang Hong,et al.  Adaptive finite-time control of nonlinear systems with parametric uncertainty , 2006, IEEE Transactions on Automatic Control.

[14]  Wei Zhang,et al.  Finite-time chaos control of unified chaotic systems with uncertain parameters , 2009 .

[15]  Lixin Tian,et al.  An energy resources demand–supply system and its dynamical analysis , 2007 .

[16]  Ping Ju,et al.  Stochastic synchronization of nonlinear energy resource system via partial feedback control , 2012 .

[17]  Jinde Cao,et al.  Adaptive synchronization of neural networks with or without time-varying delay. , 2006, Chaos.

[18]  Haijun Jiang,et al.  Exponential synchronization for delayed recurrent neural networks via periodically intermittent control , 2013, Neurocomputing.

[19]  Jinde Cao,et al.  Adaptive synchronization between two different noise-perturbed chaotic systems with fully unknown parameters , 2007 .

[20]  Xinsong Yang,et al.  Can neural networks with arbitrary delays be finite-timely synchronized? , 2014, Neurocomputing.

[21]  Jinde Cao,et al.  Lag Quasi-Synchronization of Coupled Delayed Systems With Parameter Mismatch , 2011, IEEE Transactions on Circuits and Systems I: Regular Papers.

[22]  Jinde Cao,et al.  Synchronization of a growing chaotic network model , 2011, Appl. Math. Comput..

[23]  Kai Schneider,et al.  Adaptive numerical simulation of pulsating planar flames for large Lewis and Zeldovich ranges , 2006 .

[24]  Lixin Tian,et al.  Feedback control and adaptive control of the energy resource chaotic system , 2007 .

[25]  Xuerong Shi,et al.  Robust chaos synchronization of four-dimensional energy resource system via adaptive feedback control , 2010 .

[26]  V. Haimo Finite time controllers , 1986 .

[27]  Lixin Tian,et al.  A new four-dimensional energy resources system and its linear feedback control , 2009 .

[28]  Zhidong Teng,et al.  Impulsive Control and Synchronization for Delayed Neural Networks With Reaction–Diffusion Terms , 2010, IEEE Transactions on Neural Networks.

[29]  F. M. Moukam Kakmeni,et al.  Chaos synchronization and duration time of a class of uncertain chaotic systems , 2006, Math. Comput. Simul..

[30]  Wei Zhang,et al.  Finite-time chaos synchronization of unified chaotic system with uncertain parameters , 2009 .

[31]  Jinde Cao,et al.  Finite-time stochastic synchronization of complex networks , 2010 .