In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller archite...In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller architecture simple and practical,the closed-loop system is transformed into a disturbance-free nominal system and an equivalent disturbance firstly.The equivalent disturbance represents all above uncertainties and actuator failures of the original system.Then a robust controller is proposed in a simple composition consisting of a nominal controller and a robust compensator.The nominal controller is designed for the transformed nominal system.The robust compensator is developed from a second-order filter to restrict the influence of the equivalent disturbance.Stability analysis indicates that both attitude tracking errors and compensator states can converge into the given neighborhood of the origin in finite time.To verify the effectiveness of the proposed control law,numerical simulations are carried out in different cases.Presented results demonstrate that the high-precision attitude tracking control can be achieved by the proposed fault-tolerant control law.Furthermore,multiple system performances including the control accuracy and energy consumption index are fully discussed under a series of compensator parameters.展开更多
Demand response(DR)is considered to be an effective way to bring significant economic benefit to the commercial campus integrated energy system(CCIES)due to the large amount of flexible cooling and electric vehicle(EV...Demand response(DR)is considered to be an effective way to bring significant economic benefit to the commercial campus integrated energy system(CCIES)due to the large amount of flexible cooling and electric vehicle(EV)charging loads.To maximize DR’s benefits,this paper proposes an integrated DR framework that includes direct load control for cooling loads and time-of-use for EV charging station load in the CCIES.Moreover,multiple uncertainties threaten the secure and economic operation of the CCIES.To deal with these challenges,this paper establishes an interval optimization(IO)based economic dispatch(ED)model,considering the uncertain parameters,including ambient temperature,DR parameters,pipeline parameters,and maximum available PV power output.To improve the solution efficiency,the nonlinear constraints are linearized by applying multi-layer perceptron and affine arithmetic.The order relation and the possibility degrees of intervals are used to transform the interval ED model into a bi-level optimization model.The extreme value theorem of linear interval functions is used to obtain the analytical expressions of the optimal solutions of inner-level models,and the ED model is finally transformed into a solvable mix-integer linear programming model.Test results from actual CCIES demonstrate that the DR can improve the economy and reduce the uncertain fluctuation range of both the objective function and state variables.The ED result can maintain an economical and secure operation under multiple uncertain fluctuations.展开更多
The load demand and distributed generation(DG)integration capacity in distribution networks(DNs)increase constantly,and it means that the violation of security constraints may occur in the future.This can be further w...The load demand and distributed generation(DG)integration capacity in distribution networks(DNs)increase constantly,and it means that the violation of security constraints may occur in the future.This can be further worsened by short-term power fluctuations.In this paper,a scheduling method based on a multi-objective chance-constrained information-gap decision(IGD)model is proposed to obtain the active management schemes for distribution system operators(DSOs)to address these problems.The maximum robust adaptability of multiple uncertainties,including the deviations of growth prediction and their relevant power fluctuations,can be obtained based on the limited budget of active management.The systematic solution of the proposed model is developed.The max term constraint in the IGD model is converted into a group of normal constraints corresponding to extreme points of the max term.Considering the stochastic characteristics and correlations of power fluctuations,the original model is equivalently reformulated by using the properties of multivariate Gaussian distribution.The effectiveness of the proposed model is verified by a modified IEEE 33-bus distribution network.The simulation result delineates a robust accommodation space to represent the adaptability of multiple uncertainties,which corresponds to an optional active management strategy set for future selection.展开更多
This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties.The authors consider multi-input,multi-output(MIMO)linear time-invariant s...This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties.The authors consider multi-input,multi-output(MIMO)linear time-invariant systems subject to multiple static,structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion.In the stochastic control framework,this problem can be considered as one of optimal control under state-or input-dependent random noises,while in the networked control setting,a problem of networked feedback stabilization over lossy communication channels.The authors adopt a mean-square small gain analysis approach,and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback.For single-input,single-output(SISO)systems,the condition provides an analytical bound,demonstrating explicitly how plant unstable poles,nonminimum phase zeros,and time delay may impose a limit on the uncertainty variance required for mean-square stabilization.For MIMO minimum phase systems with possible delays,the condition amounts to solving a generalized eigenvalue problem,readily solvable using linear matrix inequality optimization techniques.展开更多
The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains wi...The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains with the help of train-to-train communication.The communication delay affects the operation of the system.In addition,the train monitors real-time traffic information through on-board sensors.However,no measurement can be perfect,including sensors,which are affected by factors such as railway geometry and weather conditions.The sensor detection error is uncertain,resulting in multiple information uncertainties.Therefore,this paper proposes a train-following model based on the full velocity difference model by considering multiple information uncertainties and communication delay time to describe the autonomous operation of the train under a train autonomous operation control system.Based on this trainfollowing model,a stability analysis and numerical simulation of train traffic flow are carried out.The results show that when the velocity measured by the sensor is smaller than the real velocity or the headway monitored by the sensor is greater than the real headway,the delay will increase and continue to propagate and accumulate backward,resulting in blockage.Otherwise,the opposite occurs.These findings suggest that the effects of multiple information uncertainties are two-sided,depending on the degree of uncertainty of velocity information and headway information.In addition,communication delay time has little effect on train flow and delay.展开更多
基金supported by the APSCO(Asia-Pacific Space Cooperation Organization)Student Small Satellite(SSS)Project(Microsatellite SSS-1,No.APSCO/ET&DM/SSS/IMP_C_001)。
文摘In this paper,the satellite attitude control system subject to parametric perturbations,external disturbances,time-varying input delays,actuator faults and saturation is studied.In order to make the controller architecture simple and practical,the closed-loop system is transformed into a disturbance-free nominal system and an equivalent disturbance firstly.The equivalent disturbance represents all above uncertainties and actuator failures of the original system.Then a robust controller is proposed in a simple composition consisting of a nominal controller and a robust compensator.The nominal controller is designed for the transformed nominal system.The robust compensator is developed from a second-order filter to restrict the influence of the equivalent disturbance.Stability analysis indicates that both attitude tracking errors and compensator states can converge into the given neighborhood of the origin in finite time.To verify the effectiveness of the proposed control law,numerical simulations are carried out in different cases.Presented results demonstrate that the high-precision attitude tracking control can be achieved by the proposed fault-tolerant control law.Furthermore,multiple system performances including the control accuracy and energy consumption index are fully discussed under a series of compensator parameters.
基金supported by the National Natural Science Foundation of China(51977080)Natural Science Foundation of Guangdong Province(2022A1515010332,2023A1515240075)。
文摘Demand response(DR)is considered to be an effective way to bring significant economic benefit to the commercial campus integrated energy system(CCIES)due to the large amount of flexible cooling and electric vehicle(EV)charging loads.To maximize DR’s benefits,this paper proposes an integrated DR framework that includes direct load control for cooling loads and time-of-use for EV charging station load in the CCIES.Moreover,multiple uncertainties threaten the secure and economic operation of the CCIES.To deal with these challenges,this paper establishes an interval optimization(IO)based economic dispatch(ED)model,considering the uncertain parameters,including ambient temperature,DR parameters,pipeline parameters,and maximum available PV power output.To improve the solution efficiency,the nonlinear constraints are linearized by applying multi-layer perceptron and affine arithmetic.The order relation and the possibility degrees of intervals are used to transform the interval ED model into a bi-level optimization model.The extreme value theorem of linear interval functions is used to obtain the analytical expressions of the optimal solutions of inner-level models,and the ED model is finally transformed into a solvable mix-integer linear programming model.Test results from actual CCIES demonstrate that the DR can improve the economy and reduce the uncertain fluctuation range of both the objective function and state variables.The ED result can maintain an economical and secure operation under multiple uncertain fluctuations.
基金supported by the National Natural Science Foundation of China(No.U1866207)。
文摘The load demand and distributed generation(DG)integration capacity in distribution networks(DNs)increase constantly,and it means that the violation of security constraints may occur in the future.This can be further worsened by short-term power fluctuations.In this paper,a scheduling method based on a multi-objective chance-constrained information-gap decision(IGD)model is proposed to obtain the active management schemes for distribution system operators(DSOs)to address these problems.The maximum robust adaptability of multiple uncertainties,including the deviations of growth prediction and their relevant power fluctuations,can be obtained based on the limited budget of active management.The systematic solution of the proposed model is developed.The max term constraint in the IGD model is converted into a group of normal constraints corresponding to extreme points of the max term.Considering the stochastic characteristics and correlations of power fluctuations,the original model is equivalently reformulated by using the properties of multivariate Gaussian distribution.The effectiveness of the proposed model is verified by a modified IEEE 33-bus distribution network.The simulation result delineates a robust accommodation space to represent the adaptability of multiple uncertainties,which corresponds to an optional active management strategy set for future selection.
基金Research Grants Council of Hong Kong under Project CityU 11203120City University of Hong Kong under Project 9380054+1 种基金the Natural Science Foundation of China under Grant 61603141the Fundamental Research Funds for the Central Universities 2019MS141。
文摘This paper studies the stabilizability and stabilization of continuous-time systems in the presence of stochastic multiplicative uncertainties.The authors consider multi-input,multi-output(MIMO)linear time-invariant systems subject to multiple static,structured stochastic uncertainties,and seek to derive fundamental conditions to ensure that a system can be stabilized under a mean-square criterion.In the stochastic control framework,this problem can be considered as one of optimal control under state-or input-dependent random noises,while in the networked control setting,a problem of networked feedback stabilization over lossy communication channels.The authors adopt a mean-square small gain analysis approach,and obtain necessary and sufficient conditions for a system to be meansquare stabilizable via output feedback.For single-input,single-output(SISO)systems,the condition provides an analytical bound,demonstrating explicitly how plant unstable poles,nonminimum phase zeros,and time delay may impose a limit on the uncertainty variance required for mean-square stabilization.For MIMO minimum phase systems with possible delays,the condition amounts to solving a generalized eigenvalue problem,readily solvable using linear matrix inequality optimization techniques.
基金supported by Beijing Natural Science Foundation(Grant No.L231009)the National Natural Science Foundation of China(Grant No.72288101)the Fundamental Research Funds for the Central Universities(Grant No.2022JBZY017)。
文摘The growing demand for capacity has prompted the rail industry to explore next-generation train control systems,such as train autonomous operation control systems,which transmit real-time information between trains with the help of train-to-train communication.The communication delay affects the operation of the system.In addition,the train monitors real-time traffic information through on-board sensors.However,no measurement can be perfect,including sensors,which are affected by factors such as railway geometry and weather conditions.The sensor detection error is uncertain,resulting in multiple information uncertainties.Therefore,this paper proposes a train-following model based on the full velocity difference model by considering multiple information uncertainties and communication delay time to describe the autonomous operation of the train under a train autonomous operation control system.Based on this trainfollowing model,a stability analysis and numerical simulation of train traffic flow are carried out.The results show that when the velocity measured by the sensor is smaller than the real velocity or the headway monitored by the sensor is greater than the real headway,the delay will increase and continue to propagate and accumulate backward,resulting in blockage.Otherwise,the opposite occurs.These findings suggest that the effects of multiple information uncertainties are two-sided,depending on the degree of uncertainty of velocity information and headway information.In addition,communication delay time has little effect on train flow and delay.
