Estimation and Identifiability of Parameters for Generalized Lotka-Volterra Biological Systems Using Adaptive Controlled Combination Difference Anti-Synchronization

This manuscript systematically describes a procedure to investigate the combination difference anti-synchronization scheme among three identical chaotic generalized Lotka-Volterra biological systems. Initially, an adaptive parameter identification control method has been proposed which is based on the Lyapunov stability analysis. In addition, the biological adaptive control law for achieving global asymptotic stability of state variables of the considered system with unknown parameters has been derived. Numerical simulations have been thereafter presented for ensuring the effectivity and correctness of the considered technique using MATLAB. Remarkably, the obtained analytical results agree excellently with the computational results. The proposed approach has enormous applications in the area of image encryption and secure communication.

[1]  F. Ohle,et al.  Adaptive control of chaotic systems , 1990 .

[2]  Muzaffar Ahmad Bhat,et al.  Hyper-chaotic analysis and adaptive multi-switching synchronization of a novel asymmetric non-linear dynamical system , 2017 .

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

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

[5]  M. Bhat,et al.  Hyperchaotic Analysis and Adaptive Projective Synchronization of Nonlinear Dynamical System , 2017 .

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

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

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

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

[10]  Guo-Hui Li,et al.  Anti-synchronization in different chaotic systems , 2007 .

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

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

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

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

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

[16]  Alain Arneodo,et al.  Occurence of strange attractors in three-dimensional Volterra equations , 1980 .

[17]  Sundarapandian Vaidyanathan,et al.  Hybrid Synchronization of the Generalized Lotka-Volterra Three-Species Biological Systems via Adaptive Control , 2016 .

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

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

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

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

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

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

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

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

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

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

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

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

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

[31]  Ayub Khan,et al.  Analysis and hyper-chaos control of a new 4-D hyper-chaotic system by using optimal and adaptive control design , 2017 .

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

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

[34]  L. Greller,et al.  Explosive route to chaos through a fractal torus in a generalized lotka-volterra model , 1988 .

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

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

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

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

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

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