Liaoning University of Technology

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Jinzhou, China
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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 | Liu Y.,Liaoning University of Technology
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics | Year: 2011

In this paper, two adaptive fuzzy output feedback control approaches are proposed for a class of uncertain stochastic nonlinear strict-feedback systems without the measurements of the states. The fuzzy logic systems are used to approximate the unknown nonlinear functions, and a fuzzy state observer is designed for estimating the unmeasured states. On the basis of the fuzzy state observer, and by combining the adaptive backstepping technique with fuzzy adaptive control design, an adaptive fuzzy output feedback control approach is developed. To overcome the problem of explosion of complexity inherent in the proposed control method, the dynamic surface control (DSC) technique is incorporated into the first adaptive fuzzy control scheme, and a simplified adaptive fuzzy output feedback DSC approach is developed. It is proved that these two control approaches can guarantee that all the signals of the closed-loop system are semi-globally uniformly ultimately bounded (SGUUB) in mean square, and the observer errors and the output of the system converge to a small neighborhood of the origin. A simulation example is provided to show the effectiveness of the proposed approaches. © 2006 IEEE.


Tong S.,Liaoning University of Technology | Huo B.,Liaoning University of Technology | Li Y.,Liaoning University of Technology
IEEE Transactions on Fuzzy Systems | Year: 2014

This paper investigates the adaptive fuzzy decentralized fault-tolerant control (FTC) problem for a class of nonlinear large-scale systems in strict-feedback form. The considered nonlinear system contains the unknown nonlinear functions, i.e., unmeasured states and actuator faults, which are modeled as both loss of effectiveness and lock-in-place. With the help of fuzzy logic systems to approximate the unknown nonlinear functions, a fuzzy adaptive observer is designed to estimate the unmeasured states. By combining the backstepping technique with the nonlinear FTC theory, a novel adaptive fuzzy decentralized FTC scheme is developed. It is proved that the proposed control approach can guarantee that all the signals of the resulting closed-loop system are bounded, and the tracking errors between the system outputs and the reference signals converge to a small neighborhood of zero by appropriate choice of the design parameters. Simulation results are provided to show the effectiveness of the control approach. © 2013 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.


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.


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

This paper is concerned with the problem of adaptive fuzzy tracking control for a class of multi-input and multi-output (MIMO) strict-feedback nonlinear systems with both unknown nonsymmetric dead-zone inputs and immeasurable states. In this research, fuzzy logic systems are utilized to evaluate the unknown nonlinear functions, and a fuzzy adaptive state observer is established to estimate the unmeasured states. Based on the information of the bounds of the dead-zone slopes as well as treating the time-varying inputs coefficients as a system uncertainty, a new adaptive fuzzy output feedback control approach is developed via the backstepping recursive design technique. It is shown that the proposed control approach can assure that all the signals of the resulting closed-loop system are semiglobally uniformly ultimately bounded. It is also shown that the observer and tracking errors converge to a small neighborhood of the origin by selecting appropriate design parameters. Simulation examples are also provided to illustrate the effectiveness of the proposed approach. © 2012 IEEE.


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.


Li D.-J.,Liaoning University of Technology
Neurocomputing | Year: 2014

An adaptive control scheme is studied for a class of continuous stirred tank reactors (CSTR) with unknown functions. Because the nonlinear property and the unknown functions are included in the considered reactor, it leads to a completed task for designing the controller. Based on the approximation property of the neural networks, several unknown functions are approximated. The main contribution of this paper is that a more general class of CSTR is controlled. A novel recursive design method is used to remove the interconnection term. It is proven that the proposed algorithm can guarantee that all the signals in the closed-loop system are bounded and the system output can converge to a neighborhood of zero based on the Lyapunov analysis method. A simulation example for continuous stirred tank reactor is illustrated to verify the validity of the algorithm. © 2014 Elsevier B.V.


Tong S.,Liaoning University of Technology | Li Y.,Liaoning University of Technology
IEEE Transactions on Fuzzy Systems | Year: 2012

In this paper, an adaptive fuzzy backstepping control approach is considered for a class of nonlinear strict-feedback systems with unknown functions, unknown dead zones, and immeasurable states. Fuzzy logic systems are utilized to approximate the unknown nonlinear functions, and a fuzzy filters state observer is designed to estimate the immeasurable states. By using the adaptive backstepping recursive design technique and constructing the dead-zone inverse, a new adaptive fuzzy backstepping output-feedback control approach is developed. It is mathematically proved that all the signals of the resulting closed-loop adaptive control system are semiglobally uniformly ultimately bounded, and the tracking error converges to a small neighborhood of the origin by appropriate choice of design parameters. The proposed approach cannot only solve the problem of the dead zones but also cancel the restrictive assumption in the previous literature that the states are all available for measurement. Two simulation examples are provided to show the effectiveness of the proposed approach. © 2012 IEEE.

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