On Tracking Control and Synchronization Design for Chaotic Systems

Author(s):  
Pingping Li ◽  
Chulin Hou
2002 ◽  
Vol 11 (3) ◽  
pp. 233-237 ◽  
Author(s):  
Chen Shi-Hua ◽  
Liu Jie ◽  
Xie Jin ◽  
Lu Jun-An

2010 ◽  
Vol 37-38 ◽  
pp. 823-828
Author(s):  
Shu Bo Liu ◽  
Shu Min Zhou ◽  
Li Yong Hu

This paper applies differential evolution (DE) algorithm to realize the output tracking control and synchronization of continuous chaotic systems. The output tracking control of single-input single-output (SISO) and multi-input multi-output (MIMO) chaotic system is investigated. Moreover, synchronization of chaotic systems with parameter mismatch or structure difference is also under discussion. Numerical simulations based on the well-known models such as Lorenz and Chen systems are used to illustrate the validity of this theoretical method.


1999 ◽  
Vol 48 (9) ◽  
pp. 1618
Author(s):  
GAO JIN-FENG ◽  
LUO XIAN-JUE ◽  
MA XI-KUI ◽  
PAN XIU-QIN ◽  
WANG JUN-KUN

2021 ◽  
Vol 2021 ◽  
pp. 1-21
Author(s):  
Kuan-Yi Lin ◽  
Tung-Sheng Chiang ◽  
Chian-Song Chiu ◽  
Wen-Fong Hu ◽  
Peter Liu

Tracking control for the output using an observer-based H ∞ fuzzy synchronization of time-varying delayed discrete- and continuous-time chaotic systems is proposed in this paper. First, from a practical point of view, the chaotic systems here consider the influence of time-varying delays, disturbances, and immeasurable states. Then, to facilitate a uniform control design approach for both discrete- and continuous-time chaotic systems, the dynamic models along with time-varying delays and disturbances are reformulated using the T-S (Takagi–Sugeno) fuzzy representation. For control design considering immeasurable states, a fuzzy observer achieves master-slave synchronization. Third, combining both a fuzzy observer for state estimation and a controller (solved from generalized kinematic constraints) output tracking can be achieved. To make the design more practical, we also consider differences of antecedent variables between the plant, observer, and controller. Finally, using Lyapunov’s stability approach, the results are sufficient conditions represented as LMIs (linear matrix inequalities). The contributions of the method proposed are threefold: (i) systemic and unified problem formulation of master-slave synchronization and tracking control for both discrete and continuous chaotic systems; (ii) practical consideration of time-varying delay, immeasurable state, different antecedent variables (of plant, observer, and controller), and disturbance in the control problem; and (iii) sufficient conditions from Lyapunov’s stability analysis represented as LMIs which are numerically solvable observer and controller gains from LMIs. We carry out numerical simulations on a chaotic three-dimensional discrete-time system and continuous-time Chua’s circuit. Satisfactory numerical results further show the validity of the theoretical derivations.


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