Adaptive robust fuzzy control for a class of uncertain chaotic systems

In this paper, the output feedback control of uncertain chaotic systems is addressed via an adaptive robust fuzzy approach. Fuzzy logic systems are employed to approximate uncertain nonlinear functions in the chaotic systems. Because only partial information of the system’s states is needed to be known, an observer is given to estimate the unmeasured states. Compared with the existing results in the observer design, the prior knowledge on dynamic uncertainties is relaxed and a class of more general chaotic systems is considered as well as robustness to the approximation error is improved. It can be proven that the closed-loop system is stable in the sense that all the variables are bounded. Simulation example for the unified chaotic systems is given to verify the effectiveness of the proposed method. This work was supported in part by the National Natural Science Foundation of China (60874056) and the Foundation of Educational Department of Liaoning Province (2008312).     

Neural network-based adaptive control of a class of uncertain nonlinear systems

I.ProblemF0muIationandAssumptionsConsiderthenonlinearsystemfwhereeeR-isthestate,andavailableformeasurement,'.ERistheinput,geRistheoutput.hisasmoothfunctiononR-withh(0)=O,andthevectorfieldsI',g"aresmo0thonR-withg'(x)*O,VxeR--andI'(O)-O.ForcIarity0fexpositi…     

Adaptive smooth control for nonlinear uncertain systems

Nonlinear Dynamics - This paper presents an adaptive smooth controller for a class of nonlinear dynamical systems in the presence of bounded uncertainties with unknown bounds. Motivated by the...     

Adaptive fuzzy output-feedback control of uncertain SISO nonlinear systems

The output-feedback control problem of a class of uncertain SISO nonlinear systems is investigated based on an indirect adaptive fuzzy approach. Because the system states are not required to be available for measurement, an observer is designed to estimate the system states. Compared with the existing results in the observer design, the main advantages of the proposed adaptive fuzzy output-feedback control approach are as follows: (1) It does not require to assume that the sign of the control gain coefficient is known and Nussbaum-gain technique is utilized to control the nonlinear systems with both the unknown control direction and the unmeasured states; (2) The observer in this paper is designed for the states rather than the tracking errors, then it is convenient to compute; (3) The controller singularity problem is perfectly avoided. The stability of the closed-loop system is analyzed by using Lyapunov method. A simulation example is given to verify the feasibility of the proposed approach.     

Adaptive tracking control for a class of nonlinear non-strict-feedback systems

This paper focuses on the adaptive tracking control problem for a class of nonlinear non-strict-feedback systems. By introducing a compact set, the restrictive assumption that the lower bounds of the control gain functions must be positive constants is canceled in the proposed method, and the compact set is proved to be invariant set eventually. The functions in non-strict-feedback system are no longer required to be differentiable, and the neural networks are constructively used to deal with the unknown system functions, which contain the whole state variables of the non-strict-feedback system. Furthermore, it is rigorously proved that all the closed-loop signals are bounded and the tracking error converges to a small residual set asymptotically. Finally, simulation examples are provided to demonstrate the effectiveness of the designed method.     

Optimal control of quadratic functionals for affine nonlinear systems

In this paper we analyze the optimal control problem for a class of affine nonlinear systems under the assumption that the associated Lie algebra is nilpotent. The Lie brackets generated by the vector fields which define the nonlinear system represent a remarkable mathematical instrument for the control of affine systems. We determine the optimal control which corresponds to the nilpotent operator of the first order. In particular, we obtain the control that minimizes the energy of the given nonlinear system. Applications of this control to bilinear systems with first order nilpotent operator are considered.     

On the asymptotical behaviour of solutions of a class of nonlinear control systems

Ｃｏｎｓｉｄｅｒｔｈｅｆｏｌｌｏｗｉｎｇｎｏｎｌｉｎｅａｒｃｏｎｔｒｏｌｓｙｓｔｅｍ：·ｘ＝Ａｘ＋Ｂ（σ）,σ＝ＣＴｘ,（１）ｗｈｅｒｅｘ＝（ｘ１,ｘ２,…,ｘｎ）Ｔ∈Ｒｎ,ｔｈｅｎｏｔｅＴｅｘｐｒｅｓｓｅｓｔｈｅｔｒａｎｓｐｏｓｅｏｆｍａｔｒｉｘａｎｄｖｅｃｔｏｒ,Ａ,ＢａｎｄＣａｒｅｎ×ｎ,ｎ×ｍａｎｄｎ×ｍｃｏｎｓｔａｎｔｍａｔｒｉｃｅｓｒｅｓｐｅｃｔｉｖｅｌｙ,σ＝（σ１,σ２,…,σｍ）Ｔ∈Ｒｍａｎｄ（σ）＝（１（σ１）,２（σ２）,…,ｍ（σｍ））Ｔ：Ｒｍ→Ｒｍｉｓｃｏｎｔ…     

Analysis and control of a class of uncertain linear periodic discrete-time systems

Feedback control problems for linear periodic systems （LPSs） with interval- type parameter uncertainties are studied in the discrete-time domain. First, the stability analysis and stabilization problems are addressed. Conditions based on the linear matrices inequality （LMI） for the asymptotical stability and state feedback stabilization, respec-tively, are given. Problems of L2-gain analysis and control synthesis are studied. For the L2-gain analysis problem, we obtain an LMI-based condition such that the autonomous uncertain LPS is asymptotically stable and has an L2-gain smaller than a positive scalar γ. For the control synthesis problem, we derive an LMI-based condition to build a state feedback controller ensuring that the closed-loop system is asymptotically stable and has an L2-gain smaller than the positive scalar γ. All the conditions are necessary and sufficient.     

Composite fuzzy control of a class of uncertain nonlinear systems with disturbance observer

Nonlinear Dynamics - In this paper, a novel composite control, using fuzzy logic system (FLS) and disturbance observer, is proposed for a class of uncertain nonlinear systems with actuator...     

Dynamic controller design for a class of nonlinear uncertain systems subjected to time-varying disturbance

Inheriting advantages of both proportional-integral-derivative controller and standard sliding mode control theory, a synthetic controller design for a class of nonlinear system is presented. Regarding the architecture of the developed controller, it does not include model-based nominal control term so that the method eliminates complicated processes for system parameters identification and design of extra compensators. With simple gain tuning rules, the proposed control algorithm provides global asymptotical stability and is capable of alleviating discontinuous control switching considerably. A self-sustained oscillations phenomenon caused by the proposed control configuration is also further addressed. Simulations and experiments are conducted to verify the feasibility and applicability of the proposed approach.     

Adaptive fuzzy decentralized control for a class of pure-feedback large-scale nonlinear systems

In this paper, the problem of adaptive fuzzy decentralized control is investigated for a class of pure-feedback nonlinear interconnected large-scale systems. During the controller design, fuzzy logical systems are used to model packaged unknown nonlinearities and backstepping technique is used to construct adaptive fuzzy decentralized controller. It is shown that the proposed control scheme can guarantee that all the signals in the closed-loop system are semiglobally uniformly ultimately bounded. The main advantage of this study lies in that only one adaptive parameter needs to be estimated online for each subsystem. Simulation results further illustrate the effectiveness of the suggested approach.     

Adaptive neural tracking control for a class of perturbed pure-feedback nonlinear systems

This paper focuses on the problem of the adaptive neural control for a class of a perturbed pure-feedback nonlinear system. Based on radial basis function (RBF) neural networks’ universal approximation capability, an adaptive neural controller is developed via the backstepping technique. The proposed controller guarantees that all the signals in the closed-loop system are bounded and the tracking error eventually converges to a small neighborhood around the origin. The main advantage of this note lies in that a control strategy is presented for a class of pure-feedback nonlinear systems with external disturbances being bounded by functions of all state variables. A numerical example is provided to illustrate the effectiveness of the suggested approach.     

Adaptive generalized predictive control of switched systems

IntroductionSwitchedsystemsariseinvariedcontextsinmanufacturing ,communicationnetworks,autopilotdesign ,computersynchronization ,trafficcontrol,chemicalprocesses,andsoon .Switchedsystemsareaspecialclassofhybriddynamicalsystemswhichconsistofafamilyofsubsystemsandaswitchinglawspecifyingtheswitchingbetweenthesubsystems.Inrecentyears ,therehasbeenincreasinginterestinthecontrolofswitchedsystemsduetotheirsignificancebothintheoryandapplications.Generalizedpredictivecontrol (GPC) ,asoneofthemostpopu…