OBSERVER-BASED SYNCHRONIZATION OF UNCERTAIN CHAOTIC SYSTEMS: COMPARISON BETWEEN REDUCED-ORDER AND FULL-ORDER OBSERVERS

2008 ◽  
Vol 18 (10) ◽  
pp. 3129-3136 ◽  
Author(s):  
FANG-LAI ZHU ◽  
MAO-YIN CHEN
Keyword(s):  
Chaotic Systems ◽  
Drive System ◽  
Reduced Order ◽  
Response System ◽  
System A ◽  
Unknown Disturbances ◽  
Reduced Order Observer ◽  
Uncertain Chaotic Systems ◽  
Robust Adaptive ◽  
Better Than

Within the drive-response configuration, this paper considers the synchronization of uncertain chaotic systems based on observers. Even if there are unknown disturbances and parameters in the drive system, a robust adaptive full-order observer can be used to realize chaos synchronization. Further, we develop a reduced-order observer-based response system to synchronize the drive system. By choosing a special reduced-order gain matrix, the reduced-order observer-based response system turns out to be linear and can eliminate the influence of the unknown disturbances and parameters directly. We also discuss the above mentioned two kinds of observers in numerical simulation, and demonstrate that the linear reduced-order observer-based response system is better than the full-order observer-based one.

ADAPTIVE OBSERVER BASED SYNCHRONIZATION OF A CLASS OF UNCERTAIN CHAOTIC SYSTEMS

2008 ◽  
Vol 18 (08) ◽  
pp. 2425-2435 ◽  
Author(s):  
SAMUEL BOWONG ◽  
RENÉ YAMAPI
Keyword(s):  
Chaotic Systems ◽  
Lyapunov Stability Theory ◽  
Adaptive Observer ◽  
Adaptive Synchronization ◽  
External Disturbances ◽  
Parameter Mismatch ◽  
Lipschitz Constants ◽  
Response Systems ◽  
Uncertain Chaotic Systems ◽  
Robust Adaptive

This study addresses the adaptive synchronization of a class of uncertain chaotic systems in the drive-response framework. For a class of uncertain chaotic systems with parameter mismatch and external disturbances, a robust adaptive observer based on the response system is constructed to practically synchronize the uncertain drive chaotic system. Lyapunov stability theory ensures the practical synchronization between the drive and response systems even if Lipschitz constants on function matrices and bounds on uncertainties are unknown. Numerical simulation of two illustrative examples are given to verify the effectiveness of the proposed method.

LINEAR AND NONLINEAR GENERALIZED SYNCHRONIZATION OF CHAOTIC SYSTEMS

2010 ◽  
Vol 24 (31) ◽  
pp. 6143-6155
Author(s):  
XING-YUAN WANG ◽  
JING ZHANG
Keyword(s):  
Numerical Simulations ◽  
Chaotic Systems ◽  
Sufficient Conditions ◽  
State Observer ◽  
Drive System ◽  
Generalized Synchronization ◽  
Response System ◽  
Linear And Nonlinear ◽  
Synchronization Scheme ◽  
Application Scope

In this paper, the linear and nonlinear generalized synchronization of chaotic systems is investigated. Based on the modified state observer method, a new synchronization approach is proposed with more extensive application scope. The proposed synchronization scheme can realize the linear and nonlinear generalized synchronizations of same dimensional or different dimensional chaotic systems. Sufficient conditions of global asymptotic generalized synchronization between the drive system and the response system are gained on the basis of the state observer theory. Numerical simulations further illustrate the effectiveness of the proposed scheme.

scholarly journals Research on UDE control based on load torque compensation of PMSM

2021 ◽  
Vol 2137 (1) ◽  
pp. 012024
Author(s):  
Hongliang Yan ◽  
Weizhi Zhai ◽  
Yan Geng
Keyword(s):  
Control Strategy ◽  
Permanent Magnet Synchronous Motor ◽  
Tracking Error ◽  
Frequency Component ◽  
High Frequency Component ◽  
Load Torque ◽  
Reduced Order ◽  
System A ◽  
Reduced Order Observer ◽  
Disturbance Estimator

Abstract In order to solve the problem that the traditional uncertainty and disturbance estimator (UDE) control needs to increase the filter order to keep good performance when facing rapid disturbance changes, thus lead to cost increase in implementing the system, a speed control strategy of permanent magnet synchronous motor (PMSM) driver based on reduced order observer compensation is proposed. The designed control strategy is robust to the system with internal parameter variation and external torque disturbance. Through the compensation of load torque, the pressure of UDE controller is relieved, and then the tracking error of high-frequency component in load torque is eliminated, and the control performance of the system is improved more effectively. This paper proves the superiority of the new compound controller through comparison of simulation. results

scholarly journals Robust Adaptive Synchronization of a Class of Uncertain Chaotic Systems with Unknown Time-Delay

2020 ◽  
Vol 10 (24) ◽  
pp. 8875 ◽  
Author(s):  
Assef Zare ◽  
Seyede Zeynab Mirrezapour ◽  
Majid Hallaji ◽  
Afshin Shoeibi ◽  
Mahboobeh Jafari ◽  
...  
Keyword(s):  
Adaptive Control ◽  
Time Delays ◽  
Chaotic Systems ◽  
Control Mechanism ◽  
Robust Adaptive Control ◽  
Robust Synchronization ◽  
Uncertain Chaotic Systems ◽  
Adaptation Rules ◽  
Robust Adaptive ◽  
Unknown Time Delays

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.

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