Tracking a Chaotic System Using an Observer-Based Nonlinear State-Feedback Controller

2011 ◽  
Vol 403-408 ◽  
pp. 4643-4648
Author(s):  
Tanushree Roy ◽  
Aparajita Sengupta

This paper attempts to design a Luenberger-like nonlinear observer and a nonlinear state-feedback controller for trajectory tracking of a single-input/single-output nonlinear system exhibiting chaotic dynamics. Using a nonlinear transformation, the nonlinear system is first transformed into a linear system and thereafter a control law is designed for trajectory tracking. The controller, designed on the basis of an input-output linearized model, is applied on both the linearized as well as the nonlinear system. The results are validated through simulation on a Duffing oscillator.

2012 ◽  
Vol 482-484 ◽  
pp. 1801-1804
Author(s):  
Yang Yu ◽  
Wei Wang

The paper studies fuzzy fault control for a class of nonlinear system with input delay based on T-S fuzzy model. The state feedback controller that ensures the stability of fuzzy tolerant control system is given via Lyapunov theory and derived in terms of LMI and the results are delay-dependent. Simulation examples are given to illustrate the effectiveness of the approach.


2020 ◽  
Vol 12 (7) ◽  
pp. 168781402092265
Author(s):  
Xiao Yu ◽  
Fucheng Liao

In this article, the observer-based preview tracking control problem is investigated for a class of discrete-time Lipschitz nonlinear systems. To convert the observer-based trajectory tracking problem into a regulation problem, the classical difference technique is used to construct an augmented error system containing tracking error signal and previewable reference knowledge. Then, a state feedback controller with specific structures is taken into consideration. Sufficient design condition is established, based on the Lyapunov function approach, to guarantee the asymptotic stability of the closed-loop system. By means of some special mathematical derivations, the bilinear matrix inequality condition is successfully transformed into a tractable linear matrix inequality. Meanwhile, the gains of both observer and tracking controller can be computed simultaneously only in one step. As for the original system, the developed tracking control law is composed of an integrator, an observer-based state feedback controller, and a preview action term related to the reference signal. Finally, two numerical examples are provided to demonstrate the effectiveness of the theoretical method.


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