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In this paper, the master-slave synchronization of chaotic Lur'e systems is presented by means of quantization measurement of synchronization errors. The quantizer adopted takes finitely many values, which possess a common adjustable time-varying parameter. By using the adaptive laws for the time-varying parameter, and estimating boundary error values of quantization, a new adaptive quantized state...
This paper discusses the problem of adaptive stabilization for stochastic feedforward nonlinear systems with time-delay. A universal-type adaptive update law is introduced into the observer and controller to deal with unknown growth rates. With the help of the appropriate Lyapunov-Krasovskii functional and stochastic Barbalat's lemma, it can be proved that the universal-type adaptive output feedback...
This paper considers the global finite-time output-feedback stabilization for a class of uncertain nonlinear systems. Essentially different from the existing related literature, the systems in question allow serious parametric unknowns and serious time-variations coupling to the unmeasurable states, and possess remarkably inherent nonlinearities allowing to be low-order and high-order with respect...
This paper studies the drag-free satellite systems with double actuators along each single dimensional, an adaptive failure compensation scheme is developed for the systems with uncertain actuator failures by employing backstepping strategy. The design method is to estimate the failure parameters and use the parameter estimates to construct the control law. The control law calculation is done simultaneously...
In this paper, output feedback control is investigated for a class of uncertain non-affine nonlinear discrete-time systems. Feedback linearization is employed and a novel dynamic linear observer is built based on the measured output information, which can be used to estimate the unknown feedback linearization error. The proposed control is robust to the modeling errors and of great significance in...
A robust diffusion adaptive filtering algorithm, called the diffusion recursive least lp-norm (DRLP), is developed for distributed estimation over network. The new algorithm aims at recursively minimizing the lp-norm of error, and can offer a more stable and robust solution than traditional adaptive filtering schemes based on minimization of the squared error, such as the diffusion recursive least...
This paper is devoted to the adaptive output-feedback control of the uncertain hybrid PDE-ODE systems. To estimate the unmeasured states of the considered system, an observer is first given, and based on which we construct the desired adaptive controller successfully by using the backstepping technique. Next, by semigroup theory, we establish the well-posedness of the entire closed-loop system. At...
This paper considers the global practical tracking via adaptive output-feedback for a class of uncertain nonlinear systems with function control coefficients. The feature of the system under investigation is that the control coefficients are functions of output, and the growth rate is of polynomial-of-output multiplying an unknown constant. To solve the problem, a high-gain observer is introduced...
This paper considers the tracking fault-tolerant controller design problem for a class of nonlinear systems with unknown functions and actuator dead-zone. Based on dynamic surface control scheme and neural network approximated technique, some assumptions on nonlinear functions are removed. Also, the structure of controller is simple without the problem of ‘explosion of complexity’. Simultaneously,...
The problem of fault-tolerant tracking control is studied for a class of uncertain nonlinear systems with actuator failures. An adaptive neural networks (NNs) fault-tolerant tracking control strategy is proposed by combing backstepping with NNs, the implicit function theory, the mean value theorem and the dynamic surface control (DSC) technique. It is proven that it can guarantee all signals in the...
This paper focuses on adaptive neural control of robot manipulator with unknown system dynamics under the limitation of prescribed performance. A performance function is introduced to express the prescribed constraints of tracking errors. Subsequently, a performance transformation method is proposed to solve the problem of the prescribed performance. The unknown dynamics of robot are approximated...
In this paper, the problem of adaptive tracking control for a class of linear continuous time-invariant systems subject to constrained actuators is investigated. A novel control strategy is developed to ensure the bounded tracking of the systems. Based on Lyapunov stability theory, a result that indicates the tracking bound can be reduced as small as desired via adjusting control parameters is obtained...
The synchronization of uncertain chaotic neural networks with time delays was studied in this paper. Based on the sliding mode control (SMC) approach, some sufficient conditions for synchronization of the two coupled networks are obtained. Finally, an example and its simulation are given to illustrate the effectiveness of our results.
For the chaotic systems of uncertain model, synchronization problem of the driver response system with unknown parameters and the interference were studied. Based on Lyapunov stability theory, by constructing Lyapunov function, using the sliding mode control method to design dynamic sliding mode surface and the adaptive sliding mode controller, simultaneously to estimation parameter aim to unknown...
This paper presents a constraints transformation-based robust adaptive DSC design for a class of semi-strict feedback nonlinear systems with output constraints. In the proposed approach, a constraints transformation technique is firstly introduced to transform the original constrained system into an unconstrained normal one. Subsequently, by using a decoupled dynamic surface control (DSC) methodology,...
This paper is concerned with the robust tracking control for a class of SISO pure-feedback nonlinear systems in pseudo-affine form. Under the lowly restrictive assumption that the bounds of each unknown nonlinearities can be expressed by a known function multiplied by an unknown parameter, an approximation-free adaptive dynamic surface control (DSC) scheme is developed. Through Lyapunov synthesis,...
For the ultralow altitude airdrop decline stage, many factors such as actuator nonlinearity, the uncertain atmospheric disturbances and model unknown nonlinearity affect the precision of trajectory tracking, A robust adaptive neural network dynamic surface control method is proposed. The ultra-low altitude airdrop longitudinal dynamics with actuator input nonlinearity is established, the neural network...
This notes focuses on the state-feedback stabilization problem for a class of high-order nonlinear parameterized systems in presence of time-varying control coefficient. The conditions on parameterized nonlinear functions and time-varying control coefficient are further relaxed by adopting Nussbaum function approach and backsetpping technique. In addition, the uniform ultimate boundedness of the closed-loop...
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