In this paper,we are concerned with the output feedback exponential stabilization of cascaded parabolic PDE-ODE system where the control end suffers from the external uncertain disturbance,we design an unknown input t...
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In this paper,we are concerned with the output feedback exponential stabilization of cascaded parabolic PDE-ODE system where the control end suffers from the external uncertain disturbance,we design an unknown input type state observer with the disturbance estimator term,which is used to stabilize this cascaded system and compensate the external disturbance *** stabilizing state feedback control is designed for the observer system by the three steps backstepping transformations,which is the corresponding observer based output feedback stabilizing control for the original ***,the closed-loop system is shown to be exponentially stable.
For a class of complex networks with continuous time-varying state-dependent disturbances,adaptive coupling adjustment methods are developed to solve the problem of robust general synchronization in this *** adaptive ...
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For a class of complex networks with continuous time-varying state-dependent disturbances,adaptive coupling adjustment methods are developed to solve the problem of robust general synchronization in this *** adaptive schemes aim to estimate unknown state-dependent factors and constant ***,coupling adjustment strategies are constructed based on the estimations to compensate for the effects of *** the influence of continuous state-dependent disturbances,synchronization results are obtained by using the adaptive method combined with Lyapunov *** results verify the effectiveness of the proposed method.
Due to big delay, nonlinearity and unknown disturbance, selective catalytic reduction denitrification system cannot always achieve satisfactory control performance using PI/PID based controllers. To increase the contr...
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Due to big delay, nonlinearity and unknown disturbance, selective catalytic reduction denitrification system cannot always achieve satisfactory control performance using PI/PID based controllers. To increase the control performance, this paper uses extreme learning machine with kernels to develop a disturbance increment model for MPC. A novel online learning algorithm with an adaptive training set for extreme learning machine with kernels is proposed to make it more suitable for applications in real time. The online algorithm is employed to model and predict the disturbance increments. Then, the MPC controller with an adaptive disturbance increment model is constructed. Simulation study indicates that this controller can increase performance of SCR control system, especially for periodic and structured disturbances.
In this paper,we will study the problem of disturbance attenuation by output feedback for linear systems subject to actuator *** continuous and discrete-time systems are considered.A nonlinear output feedback,expresse...
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In this paper,we will study the problem of disturbance attenuation by output feedback for linear systems subject to actuator *** continuous and discrete-time systems are considered.A nonlinear output feedback,expressed in the form of a quasi-linear parameter-varying system,is constructed that minimizes the the effect of the disturbance on the output of the *** level of disturbance attenuation is measured in terms of the regional L
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