In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The ...In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.展开更多
This paper investigates the problem of delay-dependent robust stability analysis for a class of neutral systems with interval time-varying delays and nonlinear perturbations. Such nonlinear perturbations are with time...This paper investigates the problem of delay-dependent robust stability analysis for a class of neutral systems with interval time-varying delays and nonlinear perturbations. Such nonlinear perturbations are with time-varying but norm-bounded characteristics. Based on a new Lyapunov-Krasovskii functional together with a free-weighting matrices technique,improved delay-dependent stability criteria are established. It is shown that less conservative results can be obtained in terms of linear matrix inequalities( LMIs). Numerical examples are provided to demonstrate the effectiveness and less conservatism of the proposed approach.展开更多
This paper investigates the control problem of high-order fully actuated nonlinear systems with time-varying delays in the discrete-time domain.To make the compensation for time-varying delays concise,active and unive...This paper investigates the control problem of high-order fully actuated nonlinear systems with time-varying delays in the discrete-time domain.To make the compensation for time-varying delays concise,active and universal,a novel nonlinear predictive control method is proposed.The designed nonlinear predictive controller can achieve the same expected control performance as the nonlinear systems without delays.At the same time,the necessary and sufficient conditions for the stability of the closed-loop nonlinear predictive control systems are derived.Numerical examples show that the proposed nonlinear predictive controller design method can completely compensate for the time-varying delays of nonlinear systems.展开更多
This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RS...This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features.In addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem.The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample time.In the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion method.Furthermore,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is bounded.Finally,a numerical example is provided,which can show the usefulness of the developed DRFF approach.展开更多
This paper studies the problem of tracking control for a class of switched nonlinear systems with time-varying delay. Based on the average dwell-time and piecewise Lyapunov functional methods, a new exponential stabil...This paper studies the problem of tracking control for a class of switched nonlinear systems with time-varying delay. Based on the average dwell-time and piecewise Lyapunov functional methods, a new exponential stability criterion is obtained for the switched nonlinear systems. The designed output feedback H∞controller can be obtained by solving a set of linear matrix inequalities(LMIs).Moreover, the proposed method does not need that a common Lyapunov function exists for the switched systems, and the switching signal just depends on time. A simulation example is provided to demonstrate the effectiveness of the proposed design scheme.展开更多
基金supported by National Natural Science Foundationof China (No. 60774017 and No. 60874045)
文摘In this paper, adaptive variable structure neural control is presented for a class of uncertain multi-input multi-output (MIMO) nonlinear systems with state time-varying delays and unknown nonlinear dead-zones. The unknown time-varying delay uncer- tainties are compensated for using appropriate Lyapunov-Krasovskii functionals in the design. The approach removes the assumption of linear function outside the deadband without necessarily constructing a dead-zone inverse as an added contribution. By utilizing the integral-type Lyapunov function and introducing an adaptive compensation term for the upper bound of the residual and optimal approximation error as well as the dead-zone disturbance, the closed-loop control system is proved to be semi-globally uniformly ultimately bounded. In addition, a modified adaptive control algorithm is given in order to avoid the high-frequency chattering phenomenon. Simulation results demonstrate the effectiveness of the approach.
基金Sponsored by the National Natural Science Foundation of China(Grant No.61004038)
文摘This paper investigates the problem of delay-dependent robust stability analysis for a class of neutral systems with interval time-varying delays and nonlinear perturbations. Such nonlinear perturbations are with time-varying but norm-bounded characteristics. Based on a new Lyapunov-Krasovskii functional together with a free-weighting matrices technique,improved delay-dependent stability criteria are established. It is shown that less conservative results can be obtained in terms of linear matrix inequalities( LMIs). Numerical examples are provided to demonstrate the effectiveness and less conservatism of the proposed approach.
基金This research was supported in part by the National Natural Science Foundation of China under Grant Nos.62173255 and 62188101.
文摘This paper investigates the control problem of high-order fully actuated nonlinear systems with time-varying delays in the discrete-time domain.To make the compensation for time-varying delays concise,active and universal,a novel nonlinear predictive control method is proposed.The designed nonlinear predictive controller can achieve the same expected control performance as the nonlinear systems without delays.At the same time,the necessary and sufficient conditions for the stability of the closed-loop nonlinear predictive control systems are derived.Numerical examples show that the proposed nonlinear predictive controller design method can completely compensate for the time-varying delays of nonlinear systems.
基金This work was supported in part by the National Natural Science Foundation of China under Grant Nos.12171124,61873058,and 61673141the Natural Science Foundation of Heilongjiang Province of China under Grant No.ZD2022F003+1 种基金the Key Foundation of Educational Science Planning in Heilongjiang Province of China under Grant No.GJB1422069the Alexander von Humboldt Foundation of Germany。
文摘This paper is concerned with the distributed resilient fusion filtering(DRFF)problem for a class of time-varying multi-sensor nonlinear stochastic systems(MNSSs)with random sensor delays(RSDs).The phenomenon of the RSDs is modeled by a set of random variables with certain statistical features.In addition,the nonlinear function is handled via Taylor expansion in order to deal with the nonlinear fusion filtering problem.The aim of the addressed issue is to propose a DRFF scheme for MNSSs such that,for both RSDs and estimator gain perturbations,certain upper bounds of estimation error covariance(EEC)are given and locally minimized at every sample time.In the light of the obtained local filters,a new DRFF algorithm is developed via the matrix-weighted fusion method.Furthermore,a sufficient condition is presented,which can guarantee that the local upper bound of the EEC is bounded.Finally,a numerical example is provided,which can show the usefulness of the developed DRFF approach.
基金supported by National Natural Science Foundation of China(Nos.61473082,61273119,and 61104068)Six Talents Peaks Program of Jiangsu Province(No.2014-DZXX-003)the Fundamental Research Funds for the Central Universities(No.2242013R30006)
文摘This paper studies the problem of tracking control for a class of switched nonlinear systems with time-varying delay. Based on the average dwell-time and piecewise Lyapunov functional methods, a new exponential stability criterion is obtained for the switched nonlinear systems. The designed output feedback H∞controller can be obtained by solving a set of linear matrix inequalities(LMIs).Moreover, the proposed method does not need that a common Lyapunov function exists for the switched systems, and the switching signal just depends on time. A simulation example is provided to demonstrate the effectiveness of the proposed design scheme.