Simplified robust adaptive control of a class of time‐varying chaotic systems

Author(s):  
Jorge L. Estrada ◽  
Manuel A. Duarte‐Mermoud ◽  
Juan C. Travieso‐Torres ◽  
Nicolás H. Beltrán
2019 ◽  
Vol 17 (9) ◽  
pp. 2193-2202 ◽  
Author(s):  
Saim Ahmed ◽  
Haoping Wang ◽  
Muhammad Shamrooz Aslam ◽  
Imran Ghous ◽  
Irfan Qaisar

2020 ◽  
Vol 10 (24) ◽  
pp. 8875 ◽  
Author(s):  
Assef Zare ◽  
Seyede Zeynab Mirrezapour ◽  
Majid Hallaji ◽  
Afshin Shoeibi ◽  
Mahboobeh Jafari ◽  
...  

In this paper, a robust adaptive control strategy is proposed to synchronize a class of uncertain chaotic systems with unknown time delays. Using Lyapunov theory and Lipschitz conditions in chaotic systems, the necessary adaptation rules for estimating uncertain parameters and unknown time delays are determined. Based on the proposed adaptation rules, an adaptive controller is recommended for the robust synchronization of the aforementioned uncertain systems that prove the robust stability of the proposed control mechanism utilizing the Lyapunov theorem. Finally, to evaluate the proposed robust and adaptive control mechanism, the synchronization of two Jerk chaotic systems with finite non-linear uncertainty and external disturbances as well as unknown fixed and variable time delays are simulated. The simulation results confirm the ability of the proposed control mechanism in robust synchronization of the uncertain chaotic systems as well as to estimate uncertain and unknown parameters.


Author(s):  
James P. Nelson ◽  
Mark J. Balas ◽  
Richard S. Erwin

Many systems must operate in the presence of delays both internal to the system and in its inputs and outputs. In this paper we present a robustness result for mildly nonlinear systems. We use this result to show that, for small unknown time varying input delays, a simple adaptive controller can produce output regulation to a neighborhood with radius dependent upon the size of an upper bound on the delay. This regulation occurs in the presence of persistent disturbances and the convergence is exponential. We conclude with an example to illustrate the behavior of this adaptive control law.


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