The introduction of robust control theory into structure control, as well as design procedure of stabilizing controllers for structures with parameter uncertainty and model error is discussed. A stability bound is der...The introduction of robust control theory into structure control, as well as design procedure of stabilizing controllers for structures with parameter uncertainty and model error is discussed. A stability bound is derived from the polar decomposition of the nominal system matrix. In addition, our study shows that application of low pass filters avoids spillover by eliminating the unconsidered high frequency components. It is demonstrated, via an example, our approach leads to excellent control result and offers far better robustness than previous solutions.展开更多
The problem of adaptive robust state observer design is considered for a class of uncertain dynamical systems with Time-varying delays. A new method is presented whereby a class of memoryless adaptive robust state obs...The problem of adaptive robust state observer design is considered for a class of uncertain dynamical systems with Time-varying delays. A new method is presented whereby a class of memoryless adaptive robust state observers with simpler structure is proposed. It is also shown that by employing the proposed adaptive robust state observer, the observation error between the observer state estimate and the true state can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, a numerical example is given to demonstrate the validity of the results.展开更多
To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning s...To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.展开更多
Robust state estimation problem for wireless sensor networks consisting of multiple remote units and a fusion unit is investigated subject to a limitation on the communication rate.An analytical robust fusion estimato...Robust state estimation problem for wireless sensor networks consisting of multiple remote units and a fusion unit is investigated subject to a limitation on the communication rate.An analytical robust fusion estimator based on an event-triggered transmission approach is derived to reduce the network traffic congestion and save the energy consumption of the sensor units.Some conditions guaranteeing the uniformly bounded estimation errors of the robust fusion estimator are investigated.Numerical simulations are provided to show the effectiveness of the proposed approach.展开更多
The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs...The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs) enhances the monitoring level. The trade-offs of computational performance and robustness of state estimation in monitoring the network states are of great significance for ADNs with D-PMUs and DGs. This paper proposes a second-order cone programming(SOCP) based robust state estimation(RSE) method considering multi-source measurements. Firstly, a linearized state estimation model related to the SOCP state variables is formulated. The phase angle measurements of D-PMUs are converted to equivalent power measurements. Then, a revised SOCP-based RSE method with the weighted least absolute value estimator is proposed to enhance the convergence and bad data identification. Multi-time slots of D-PMU measurements are utilized to improve the estimation accuracy of RSE. Finally, the effectiveness of the proposed method is illustrated in the modified IEEE 33-node and IEEE 123-node systems.展开更多
Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable energy.However,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy management.The curren...Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable energy.However,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy management.The currentestimator is also not robust against bad data.This study introducesthe concepts of relative error to construct an improvedrobust SE(IRSE)optimization model with mixed-integer nonlinearprogramming(MINLP)that overcomes the disadvantage ofinaccurate results derived from different measurements whenthe same tolerance range is considered in the robust SE(RSE).To improve the computation efficiency of the IRSE optimizationmodel,the number of binary variables is reduced based on theprojection statistics and normalized residual methods,which effectivelyavoid the problem of slow convergence or divergenceof the algorithm caused by too many integer variables.Finally,an embedded consensus alternating direction of multiplier method(ADMM)distribution algorithm based on outer approximation(OA)is proposed to solve the IRSE optimization model.This algorithm can accurately detect bad data and obtain SE resultsthat communicate only the boundary coupling informationwith neighbors.Numerical tests show that the proposed algorithmeffectively detects bad data,obtains more accurate SE results,and ensures the protection of private information in all microgrids.展开更多
A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC co...A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.展开更多
The sufficient conditions of stability for uncertain discrete-time systems with state delay have been proposed by some researchers in the past few years, yet these results may be conservative in application. The stabi...The sufficient conditions of stability for uncertain discrete-time systems with state delay have been proposed by some researchers in the past few years, yet these results may be conservative in application. The stability analysis of these systems is discussed, and the necessary and sufficient condition of stability is derived by method other than constructing Lyapunov function and solving Riccati inequality. The root locations of system characteristic polynomial, which is obtained by augmentation approach and Laplace expansion, determine the stability of uncertain discrete-time systems with state delay, the system is stable if and only if all roots lie within the unit circle. In order to analyze robust stability of system characteristic polynomial effectively, Kharitonov theorem and edge theorem are applied. Example shows the practicability of these methods.展开更多
This paper focused on a class of linear state-delayed systems with or without uncertainty. As for uncertain systems, dissipative uncertainty description contains norm-bounded and positive real uncertainties as special...This paper focused on a class of linear state-delayed systems with or without uncertainty. As for uncertain systems, dissipative uncertainty description contains norm-bounded and positive real uncertainties as special cases. The paper is concerned with the design of dissipative static state feedback controllers such that the closed-loop system is (robustly) asymptotically stable and strictly (Q,S,R)-dissipative. Sufficient conditions for the existence of the quadratic dissipative state feedback controllers are obtained by using a linear matrix inequality (LMI) approach. It is shown that the solvability of dissipative controller design problem is implied by the feasibility of LMIs. The main results of this paper unify the existing results on H ∞ control and passive control.展开更多
This paper focuses on the H_ mixed sensitivity problems of the system with input multiplicative uncertainty, and proposes a new robust H_ /LTR synthesis method. The design procedure consists of two steps. First, an H_...This paper focuses on the H_ mixed sensitivity problems of the system with input multiplicative uncertainty, and proposes a new robust H_ /LTR synthesis method. The design procedure consists of two steps. First, an H_ full state feedback control is designed to satisfy the robust stability and performance specifications. Subsequently, the properties of the state feedback are reobtained by designing full state observers.展开更多
This paper focuses on the H∞ controller design for linear systems with time-varying delays and norm-bounded parameter perturbations in the system state and control/disturbance. On the existence of delayed/undelayed f...This paper focuses on the H∞ controller design for linear systems with time-varying delays and norm-bounded parameter perturbations in the system state and control/disturbance. On the existence of delayed/undelayed full state feedback controllers, we present a sufficient condition and give a design method in the form of Riccati equation. The controller can not only stabilize the time-delay system, but also make the H∞ norm of the closed-loop system be less than a given bound. This result practically generalizes the related results in current literature.展开更多
无迹卡尔曼滤波(unscented Kalman filter,UKF)是锂离子电池荷电状态(state of charge,SOC)估计的常用算法之一。然而在实际应用中,由于受到外界环境温度变化、电池容量退化等不确定性干扰,以及非高斯过程噪声的影响,需要进一步提高算...无迹卡尔曼滤波(unscented Kalman filter,UKF)是锂离子电池荷电状态(state of charge,SOC)估计的常用算法之一。然而在实际应用中,由于受到外界环境温度变化、电池容量退化等不确定性干扰,以及非高斯过程噪声的影响,需要进一步提高算法的性能才能更有效地保证估计精度。基于此,提出一种改进的无迹卡尔曼滤波算法(PO-RUKF)。首先,在UKF中引入H∞滤波提高算法的鲁棒性,用来克服各种干扰带来的不良影响。其次,利用鹦鹉优化算法对UKF的过程噪声协方差矩阵进行自适应调整,以解决滤波噪声参数先验确定的问题,从而提高滤波精度。最后,采用马里兰大学的FUDS和HPPC工况下的两种公开数据集进行了实验验证,结果表明,在不同的温度、电池容量退化状态以及不同的工况下,相比于传统的UKF算法以及鲁棒UKF算法,改进后的算法具有更高的SOC估计精度,平均绝对误差小于0.50%,均方根误差小于0.56%,此外还展现出更强的鲁棒性和普适性。证实所提方法可以为锂离子电池SOC估计提供更可靠、有效的技术支撑。展开更多
In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system...In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.展开更多
Load simulator is a key test equipment for aircraft actuation systems in hardware-in-the-loop-simulation. Static loading is an essential function of the load simulator and widely used in the static/dynamic stiffness t...Load simulator is a key test equipment for aircraft actuation systems in hardware-in-the-loop-simulation. Static loading is an essential function of the load simulator and widely used in the static/dynamic stiffness test of aircraft actuation systems. The tracking performance of the static loading is studied in this paper. Firstly, the nonlinear mathematical models of the hydraulic load simulator are derived, and the feedback linearization method is employed to construct a feed-forward controller to improve the force tracking performance. Considering the effect of the friction, a LuGre model based friction compensation is synthesized, in which the unmeasurable state is estimated by a dual state observer via a controlled learning mechanism to guarantee that the estimation is bounded. The modeling errors are attenuated by a well-designed robust controller with a control accuracy measured by a design parameter. Employing the dual state observer is to capture the different effects of the unmeasured state and hence can improve the friction compensation accuracy. The tracking performance is summarized by a derived theorem. Experimental results are also obtained to verify the high performance nature of the proposed control strategy.展开更多
The delayed-state-derivative feedback （DSDF） is in- troduced into the existing consensus protocol to simultaneously improve the robustness to communication delay and accele- rate the convergence speed of achieving t...The delayed-state-derivative feedback （DSDF） is in- troduced into the existing consensus protocol to simultaneously improve the robustness to communication delay and accele- rate the convergence speed of achieving the consensus. The frequency-domain analysis, together with the algebra graph the- ory, is employed to derive the sufficient and necessary condition guaranteeing the average consensus. It is shown that introduc- ing the DSDF with the proper intensity in the existing consensus protocol can improve the robustness to communication delay. By analyzing the effect of DSDF on the closed-loop poles, this pa- per proves that for a supercritical-delay multi-agent system, this strategy can also accelerate the convergence speed of achieving the consensus with provided the proper intensity of the DSDE Simulations are provided to demonstrate the effectiveness of the theoretical results.展开更多
The sufficient condition based on piecewise quadratic simultaneous Lyapunov functions for robust stabilization of uncertain control systems via a constant linear state feedback control law is obtained. The objective i...The sufficient condition based on piecewise quadratic simultaneous Lyapunov functions for robust stabilization of uncertain control systems via a constant linear state feedback control law is obtained. The objective is to use a robust stability criterion that is less conservative than the usual quadratic stability criterion. Numerical example is given, showing the advanteges of the proposed method.展开更多
The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS...The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS with short time-delay. Based on the designed states observer, a robust fault detection approach is proposed for NCS. In addition, an optimization method for the selection of the detection threshold is introduced for better tradeoff between the robustness and the sensitivity. Finally, some simulation results demonstrate that the presented states observer is robust and the fault detection for NCS is effective.展开更多
文摘The introduction of robust control theory into structure control, as well as design procedure of stabilizing controllers for structures with parameter uncertainty and model error is discussed. A stability bound is derived from the polar decomposition of the nominal system matrix. In addition, our study shows that application of low pass filters avoids spillover by eliminating the unconsidered high frequency components. It is demonstrated, via an example, our approach leads to excellent control result and offers far better robustness than previous solutions.
文摘The problem of adaptive robust state observer design is considered for a class of uncertain dynamical systems with Time-varying delays. A new method is presented whereby a class of memoryless adaptive robust state observers with simpler structure is proposed. It is also shown that by employing the proposed adaptive robust state observer, the observation error between the observer state estimate and the true state can be guaranteed to be uniformly exponentially convergent towards a ball which can be as small as desired. Finally, a numerical example is given to demonstrate the validity of the results.
基金This work was supported in part by National Natural Science Foundation of China(No.52077076)in part by the State Key Laboratory of Alternate Electrical Power System with Renewable Energy Sources(No.LAPS2021-18).
文摘To overcome the shortcomings of model-driven state estimation methods, this paper proposes a data-driven robust state estimation (DDSE) method through off-line learning and on-line matching. At the off-line learning stage, a linear regression equation is presented by clustering historical data from supervisory control and data acquisition (SCADA), which provides a guarantee for solving the over-learning problem of the existing DDSE methods;then a novel robust state estimation method that can be transformed into quadratic programming (QP) models is proposed to obtain the mapping relationship between the measurements and the state variables (MRBMS). The proposed QP models can well solve the problem of collinearity in historical data. Furthermore, the off-line learning stage is greatly accelerated from three aspects including reducing historical categories, constructing tree retrieval structure for known topologies, and using sensitivity analysis when solving QP models. At the on-line matching stage, by quickly matching the current snapshot with the historical ones, the corresponding MRBMS can be obtained, and then the estimation values of the state variables can be obtained. Simulations demonstrate that the proposed DDSE method has obvious advantages in terms of suppressing over-learning problems, dealing with collinearity problems, robustness, and computation efficiency.
基金the National Natural Science Foundation of China[grant number 61573203][grant number 61573204]China Postdoctoral Science Foundation[grant number 2017M612190]。
文摘Robust state estimation problem for wireless sensor networks consisting of multiple remote units and a fusion unit is investigated subject to a limitation on the communication rate.An analytical robust fusion estimator based on an event-triggered transmission approach is derived to reduce the network traffic congestion and save the energy consumption of the sensor units.Some conditions guaranteeing the uniformly bounded estimation errors of the robust fusion estimator are investigated.Numerical simulations are provided to show the effectiveness of the proposed approach.
基金supported by the National Key R&D Program of China (No. 2020YFB0906000 and 2020YFB0906001)。
文摘The volatile and intermittent nature of distributed generators(DGs) in active distribution networks(ADNs) increases the uncertainty of operating states. The introduction of distribution phasor measurement units(D-PMUs) enhances the monitoring level. The trade-offs of computational performance and robustness of state estimation in monitoring the network states are of great significance for ADNs with D-PMUs and DGs. This paper proposes a second-order cone programming(SOCP) based robust state estimation(RSE) method considering multi-source measurements. Firstly, a linearized state estimation model related to the SOCP state variables is formulated. The phase angle measurements of D-PMUs are converted to equivalent power measurements. Then, a revised SOCP-based RSE method with the weighted least absolute value estimator is proposed to enhance the convergence and bad data identification. Multi-time slots of D-PMU measurements are utilized to improve the estimation accuracy of RSE. Finally, the effectiveness of the proposed method is illustrated in the modified IEEE 33-node and IEEE 123-node systems.
基金supported by the National Natural Science Foundation of China(No.5217070269).
文摘Networked microgrids(NMGs)are critical in theaccommodation of distributed renewable energy.However,theexisting centralized state estimation(SE)cannot meet the demandsof NMGs in distributed energy management.The currentestimator is also not robust against bad data.This study introducesthe concepts of relative error to construct an improvedrobust SE(IRSE)optimization model with mixed-integer nonlinearprogramming(MINLP)that overcomes the disadvantage ofinaccurate results derived from different measurements whenthe same tolerance range is considered in the robust SE(RSE).To improve the computation efficiency of the IRSE optimizationmodel,the number of binary variables is reduced based on theprojection statistics and normalized residual methods,which effectivelyavoid the problem of slow convergence or divergenceof the algorithm caused by too many integer variables.Finally,an embedded consensus alternating direction of multiplier method(ADMM)distribution algorithm based on outer approximation(OA)is proposed to solve the IRSE optimization model.This algorithm can accurately detect bad data and obtain SE resultsthat communicate only the boundary coupling informationwith neighbors.Numerical tests show that the proposed algorithmeffectively detects bad data,obtains more accurate SE results,and ensures the protection of private information in all microgrids.
基金Supported by Natural Science Foundation of China(Grant Nos.52072051,51705044)Chongqing Municipal Natural Science Foundation of China(Grant No.cstc2020jcyj-msxmX0956)+1 种基金State Key Laboratory of Mechanical System and Vibration(Grant No.MSV202016)State Key Laboratory of Mechanical Transmissions(Grant No.SKLMT-KFKT-201806).
文摘A comparative study of model predictive control(MPC)schemes and robust Hstate feedback control(RSC)method for trajectory tracking is proposed in this paper.The main objective of this paper is to compare MPC and RSC controllers’performance in tracking predefined trajectory under different scenarios.MPC controller is designed based on the simple longitudinal-yaw-lateral motions of a single-track vehicle with a linear tire,which is an approximation of the more realistic model of a vehicle with double-track motion with a non-linear tire mode.RSC is designed on the basis of the same method as adopted for the MPC controller to achieve a fair comparison.Then,three test cases are built in CarSim-Simulink joint platform.Specifically,the verification test is used to test the tracking accuracy of MPC and RSC controller under well road conditions.Besides,the double lane change test with low road adhesion is designed to find the maximum velocity that both controllers can carry out while guaranteeing stability.Furthermore,an extreme curve test is built where the road adhesion changes suddenly,in order to test the performance of both controllers under extreme conditions.Finally,the advantages and disadvantages of MPC and RSC under different scenarios are also discussed.
基金This project was supported by National "863" High Technology Research and Development Program of China (2001-AA413130) and the National Key Research Project (2001-BA201A04).
文摘The sufficient conditions of stability for uncertain discrete-time systems with state delay have been proposed by some researchers in the past few years, yet these results may be conservative in application. The stability analysis of these systems is discussed, and the necessary and sufficient condition of stability is derived by method other than constructing Lyapunov function and solving Riccati inequality. The root locations of system characteristic polynomial, which is obtained by augmentation approach and Laplace expansion, determine the stability of uncertain discrete-time systems with state delay, the system is stable if and only if all roots lie within the unit circle. In order to analyze robust stability of system characteristic polynomial effectively, Kharitonov theorem and edge theorem are applied. Example shows the practicability of these methods.
文摘This paper focused on a class of linear state-delayed systems with or without uncertainty. As for uncertain systems, dissipative uncertainty description contains norm-bounded and positive real uncertainties as special cases. The paper is concerned with the design of dissipative static state feedback controllers such that the closed-loop system is (robustly) asymptotically stable and strictly (Q,S,R)-dissipative. Sufficient conditions for the existence of the quadratic dissipative state feedback controllers are obtained by using a linear matrix inequality (LMI) approach. It is shown that the solvability of dissipative controller design problem is implied by the feasibility of LMIs. The main results of this paper unify the existing results on H ∞ control and passive control.
文摘This paper focuses on the H_ mixed sensitivity problems of the system with input multiplicative uncertainty, and proposes a new robust H_ /LTR synthesis method. The design procedure consists of two steps. First, an H_ full state feedback control is designed to satisfy the robust stability and performance specifications. Subsequently, the properties of the state feedback are reobtained by designing full state observers.
基金This project was supported by the National Natural Science Foundation of China (No. 69974022).
文摘This paper focuses on the H∞ controller design for linear systems with time-varying delays and norm-bounded parameter perturbations in the system state and control/disturbance. On the existence of delayed/undelayed full state feedback controllers, we present a sufficient condition and give a design method in the form of Riccati equation. The controller can not only stabilize the time-delay system, but also make the H∞ norm of the closed-loop system be less than a given bound. This result practically generalizes the related results in current literature.
文摘无迹卡尔曼滤波(unscented Kalman filter,UKF)是锂离子电池荷电状态(state of charge,SOC)估计的常用算法之一。然而在实际应用中,由于受到外界环境温度变化、电池容量退化等不确定性干扰,以及非高斯过程噪声的影响,需要进一步提高算法的性能才能更有效地保证估计精度。基于此,提出一种改进的无迹卡尔曼滤波算法(PO-RUKF)。首先,在UKF中引入H∞滤波提高算法的鲁棒性,用来克服各种干扰带来的不良影响。其次,利用鹦鹉优化算法对UKF的过程噪声协方差矩阵进行自适应调整,以解决滤波噪声参数先验确定的问题,从而提高滤波精度。最后,采用马里兰大学的FUDS和HPPC工况下的两种公开数据集进行了实验验证,结果表明,在不同的温度、电池容量退化状态以及不同的工况下,相比于传统的UKF算法以及鲁棒UKF算法,改进后的算法具有更高的SOC估计精度,平均绝对误差小于0.50%,均方根误差小于0.56%,此外还展现出更强的鲁棒性和普适性。证实所提方法可以为锂离子电池SOC估计提供更可靠、有效的技术支撑。
文摘In this paper, we present a quantitative analysis of the robustness of a generalized predictive controller. The result of stability analysis shows that, under a specific bounded modelling error, the closed-loop system is BIBO stable in the presence of unmodelled dynamics.
基金National Science Fund for Distinguished Young Scholars (50825502)
文摘Load simulator is a key test equipment for aircraft actuation systems in hardware-in-the-loop-simulation. Static loading is an essential function of the load simulator and widely used in the static/dynamic stiffness test of aircraft actuation systems. The tracking performance of the static loading is studied in this paper. Firstly, the nonlinear mathematical models of the hydraulic load simulator are derived, and the feedback linearization method is employed to construct a feed-forward controller to improve the force tracking performance. Considering the effect of the friction, a LuGre model based friction compensation is synthesized, in which the unmeasurable state is estimated by a dual state observer via a controlled learning mechanism to guarantee that the estimation is bounded. The modeling errors are attenuated by a well-designed robust controller with a control accuracy measured by a design parameter. Employing the dual state observer is to capture the different effects of the unmeasured state and hence can improve the friction compensation accuracy. The tracking performance is summarized by a derived theorem. Experimental results are also obtained to verify the high performance nature of the proposed control strategy.
基金supported by the National Natural Science Foundation of China (60574088 60874053)
文摘The delayed-state-derivative feedback （DSDF） is in- troduced into the existing consensus protocol to simultaneously improve the robustness to communication delay and accele- rate the convergence speed of achieving the consensus. The frequency-domain analysis, together with the algebra graph the- ory, is employed to derive the sufficient and necessary condition guaranteeing the average consensus. It is shown that introduc- ing the DSDF with the proper intensity in the existing consensus protocol can improve the robustness to communication delay. By analyzing the effect of DSDF on the closed-loop poles, this pa- per proves that for a supercritical-delay multi-agent system, this strategy can also accelerate the convergence speed of achieving the consensus with provided the proper intensity of the DSDE Simulations are provided to demonstrate the effectiveness of the theoretical results.
基金University Key Teacher by the Ministry of Education.
文摘The sufficient condition based on piecewise quadratic simultaneous Lyapunov functions for robust stabilization of uncertain control systems via a constant linear state feedback control law is obtained. The objective is to use a robust stability criterion that is less conservative than the usual quadratic stability criterion. Numerical example is given, showing the advanteges of the proposed method.
基金supported partly by the Natural Science Foundation China (70571032).
文摘The influence of random short time-delay to networked control systems （NCS） is changed into an unknown bounded uncertain part. Without changing the structure of the system, an Hoo states observer is designed for NCS with short time-delay. Based on the designed states observer, a robust fault detection approach is proposed for NCS. In addition, an optimization method for the selection of the detection threshold is introduced for better tradeoff between the robustness and the sensitivity. Finally, some simulation results demonstrate that the presented states observer is robust and the fault detection for NCS is effective.
