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Li D.-J.,Liaoning University of Technology
Nonlinear Dynamics | Year: 2012

In this paper, an adaptive output feedback control algorithm based on the dynamic surface control (DSC) is proposed for a class of uncertain chaotic systems. Because the system states are assumed to be unavailable, an observer is designed to estimate those unavailable states. The main advantage of this algorithm can overcome the problem of "explosion of complexity" inherent in the backstepping design. Thus, the proposed control approach is simpler than the traditional backstepping control for the uncertain chaotic systems. The stability analysis shows that the system is stable in the sense that all signals in the closed-loop system are uniformly ultimately bounded (UUB) and the system output can track the reference signal to a bounded compact set. Finally, an example is provided to illustrate the effectiveness of the proposed control system. © 2011 Springer Science+Business Media B.V.


Li D.J.,Liaoning University of Technology
Science China Information Sciences | Year: 2014

In this paper, the control problem of continuous stirred tank reactors (CSTR) is studied. The considered CSTR are required to contain unknown functions and unknown dead zone input. An adaptive controller that uses the neural networks (NNs) is provided to solve the unknown terms. The proposed approach overcomes the effect of the dead zone input. The dead zone input in the systems is compensated for by introducing a new Lyapunov form and Young’s inequality. The backstepping procedure is exploited to implement controller design with adaptation laws. The stability is analyzed using Lyapunov method. The performance is examined for CSTR to confirm the effectiveness of the proposed approach based on computer simulation. © 2014, Science China Press and Springer-Verlag Berlin Heidelberg.


Tong S.,Liaoning University of Technology | Wang T.,Liaoning University of Technology | Li Y.,Liaoning University of Technology | Chen B.,Qingdao University
IEEE Transactions on Fuzzy Systems | Year: 2013

In this paper, an adaptive fuzzy output feedback control approach is investigated for a class of stochastic nonlinear strict-feedback systems without the requirement of states measurement. The stochastic nonlinear system addressed in this paper is assumed to possess unstructured uncertainties (unknown nonlinear functions) and, in the presence of unmodeled dynamics, dynamics disturbances. Fuzzy logic systems are used to approximate the unstructured uncertainties, and a fuzzy state observer is designed to estimate the unmeasured states. By combining the backstepping design technique with the stochastic small-gain approach, a new adaptive fuzzy output feedback control approach is developed. It is proved that the proposed control approach can guarantee that the closed-loop system is input-state-practically stability (ISpS) in probability, and the observer errors and the output of the system converge to a small neighborhood of the origin by appropriate choice of the design parameters. Simulation results are included to indicate that the proposed adaptive fuzzy control approach has a satisfactory control performance. In addition, the simulation comparisons with the previous methods show that the proposed adaptive fuzzy control approach has robustness to the dynamical uncertainties. © 1993-2012 IEEE.


Liu Y.-J.,Liaoning University of Technology | Tong S.,Liaoning University of Technology | Chen C.L.P.,Macau University of Science and Technology
IEEE Transactions on Fuzzy Systems | Year: 2013

In this paper, the problems of stability and tracking control for a class of large-scale nonlinear systems with unmodeled dynamics are addressed by designing the decentralized adaptive fuzzy output feedback approach. Because the dynamic surface control technique is introduced, the designed controllers can avoid the issue of 'explosion of complexity,' which comes from the traditional backstepping design procedure that deals with large-scale nonlinear systems with unmodeled dynamics. In addition, a reduced-order observer is designed to estimate those immeasurable states. Based on the Lyapunov stability method, it is proven that all the signals in the closed-loop system are bounded, and the system outputs track the reference signals to a small neighborhood of the origin by choosing the design parameters appropriately. The simulation examples are given to verify the effectiveness of the proposed techniques. © 1993-2012 IEEE.


Tong S.,Liaoning University of Technology | Li Y.,Liaoning University of Technology
IEEE Transactions on Fuzzy Systems | Year: 2013

In this paper, the problem of adaptive fuzzy decentralized backstepping control is considered for a class of nonlinear large-scale strict-feedback systems with unknown dead zones and immeasurable states. Fuzzy logic systems are used to approximate the unknown nonlinear functions, and a state filter is designed to estimate the immeasurable states. Applying an adaptive backstepping design technique and combining it with the dead-zone inverse method, an adaptive fuzzy decentralized output-feedback backstepping control is developed. It is proved that all the signals of the resulting closed-loop adaptive control system are semiglobally uniformly ultimately bounded, and tracking errors converge to a small neighborhood of the origin by appropriate choice of design parameters. Simulation results are given to demonstrate that the proposed adaptive decentralized control approach has a satisfactory control performance. © 1993-2012 IEEE.

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