Adaptive controllability of microscopic chaos generated in chemical reactor system using anti-synchronization strategy

In this manuscript, we design a methodology to investigate the anti-synchronization scheme in chaotic chemical reactor system using adaptive control method (ACM). Initially, an ACM has been proposed and analysed systematically for controlling the microscopic chaos found in the discussed system which is essentially described by employing Lyapunov stability theory (LST). The required asymptotic stability criterion of the state variables of the discussed system having unknown parameters is derived by designing appropriate control functions and parameter updating laws. In addition, numerical simulation results in MATLAB software are performed to illustrate the effective presentation of the considered strategy. Simulations outcomes correspond that the primal aim of chaos control in the given system have been attained computationally.

[1]  Wayne Luk,et al.  Exploiting the chaotic behaviour of atmospheric models with reconfigurable architectures , 2017, Comput. Phys. Commun..

[2]  Zhixia Ding,et al.  Projective synchronization of nonidentical fractional-order neural networks based on sliding mode controller , 2016, Neural Networks.

[3]  Xiaofeng Liao,et al.  Complete and lag synchronization of hyperchaotic systems using small impulses , 2004 .

[4]  Kwok-Wo Wong,et al.  An image encryption scheme based on time-delay and hyperchaotic system , 2012, Nonlinear Dynamics.

[5]  Ayub Khan,et al.  Hybrid projective combination–combination synchronization in non-identical hyperchaotic systems using adaptive control , 2020, Arabian Journal of Mathematics.

[6]  M. T. Yassen,et al.  Adaptive control and synchronization of a modified Chua's circuit system , 2003, Appl. Math. Comput..

[7]  Vijay K. Yadav,et al.  Synchronization between fractional order complex chaotic systems , 2017 .

[8]  Dong Li,et al.  Impulsive synchronization of fractional order chaotic systems with time-delay , 2016, Neurocomputing.

[9]  Sundarapandian Vaidyanathan,et al.  Dynamics, circuit realization, control and synchronization of a hyperchaotic hyperjerk system with coexisting attractors , 2017 .

[10]  Grebogi,et al.  Using chaos to direct trajectories to targets. , 1990, Physical review letters.

[11]  D. Baleanu,et al.  Image encryption technique based on fractional chaotic time series , 2016 .

[12]  E. Lorenz Deterministic nonperiodic flow , 1963 .

[13]  Manfeng Hu,et al.  Hybrid projective synchronization in a chaotic complex nonlinear system , 2008, Math. Comput. Simul..

[14]  Kais Bouallegue,et al.  A new class of neural networks and its applications , 2017, Neurocomputing.

[15]  Zhengzhi Han,et al.  Controlling and synchronizing chaotic Genesio system via nonlinear feedback control , 2003 .

[16]  Binoy Krishna Roy,et al.  Microscopic chaos control of chemical reactor system using nonlinear active plus proportional integral sliding mode control technique , 2019, The European Physical Journal Special Topics.

[17]  Banshidhar Sahoo,et al.  The chaos and control of a food chain model supplying additional food to top-predator , 2014 .

[18]  K. Sebastian Sudheer,et al.  Hybrid synchronization of hyperchaotic Lu system , 2009 .

[19]  Nikola Samardzija,et al.  Nonlinear chemical kinetic schemes derived from mechanical and electrical dynamical systems , 1989 .

[20]  Y. Kuramoto,et al.  Dephasing and bursting in coupled neural oscillators. , 1995, Physical review letters.

[21]  Teh-Lu Liao,et al.  Adaptive synchronization of chaotic systems and its application to secure communications , 2000 .

[22]  Arindum Mukherjee,et al.  Generation & control of chaos in a single loop optoelectronic oscillator , 2018, Optik.

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

[24]  Sunil Kumar Kashyap,et al.  Matrix-Binary Codes based Genetic Algorithm for path planning of mobile robot , 2017, Comput. Electr. Eng..

[25]  P. Katsaloulis,et al.  Dynamics of chaotic maps for modelling the multifractal spectrum of human brain Diffusion Tensor Images , 2012 .

[26]  Taqseer Khan,et al.  Estimation and Identifiability of Parameters for Generalized Lotka-Volterra Biological Systems Using Adaptive Controlled Combination Difference Anti-Synchronization , 2020 .

[27]  H. Yau Design of adaptive sliding mode controller for chaos synchronization with uncertainties , 2004 .

[28]  Eckmann,et al.  Liapunov exponents from time series. , 1986, Physical review. A, General physics.

[29]  Kangsheng Chen,et al.  Experimental study on tracking the state of analog Chua's circuit with particle filter for chaos synchronization , 2008 .

[30]  Xinchu Fu,et al.  Complex projective synchronization in coupled chaotic complex dynamical systems , 2012 .

[31]  Wei Zhu,et al.  Function projective synchronization for fractional-order chaotic systems , 2011 .

[32]  Tasawar Hayat,et al.  Phase synchronization between two neurons induced by coupling of electromagnetic field , 2017, Appl. Math. Comput..

[33]  Daolin Xu,et al.  A secure communication scheme using projective chaos synchronization , 2004 .

[34]  Zhu Wang,et al.  An image encryption scheme based on a new hyperchaotic finance system , 2015 .

[35]  Hadi Delavari,et al.  Hybrid Complex Projective Synchronization of Complex Chaotic Systems Using Active Control Technique with Nonlinearity in the Control Input , 2018 .

[36]  Sundarapandian Vaidyanathan,et al.  Synchronization of Hyperchaotic Liu System via Backstepping Control with Recursive Feedback , 2012 .

[37]  Sundarapandian Vaidyanathan,et al.  Anti-synchronization of four-wing chaotic systems via sliding mode control , 2012, Int. J. Autom. Comput..

[38]  Guohui Li Modified projective synchronization of chaotic system , 2007 .

[39]  Li-Wei Ko,et al.  Adaptive synchronization of chaotic systems with unknown parameters via new backstepping strategy , 2012, Nonlinear Dynamics.