Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more a...Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system（IHPS） based on a nonlinear unknown input observer（NUIO） is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.展开更多
This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appea...This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults.展开更多
Unknown input observer is one of the most famous strategies for robust fault diagnosis of linear systems, but studies on nonlinear cases are not sufficient. On the other hand, the extended Kalman filter （EKF） is wel...Unknown input observer is one of the most famous strategies for robust fault diagnosis of linear systems, but studies on nonlinear cases are not sufficient. On the other hand, the extended Kalman filter （EKF） is wellknown in nonlinear estimation, and its convergence as an observer of nonlinear deterministic system has been derived recently. By combining the EKF and the unknown input Kalman filter, we propose a robust nonlinear estimator called unknown input EKF （UIEKF） and prove its convergence as a nonlinear robust observer under some mild conditions using linear matrix inequality （LMI）. Simulation of a three-tank system “DTS200”, a benchmark in process control, demonstrates the robustness and effectiveness of the UIEKF as an observer for nonlinear systems with uncertainty, and the fault diagnosis based on the UIEKF is found successful.展开更多
A unknown input observer （UIO） design for a class of linear time-delay systems when the observer error can＇t completely decouple from unknown input is dealt with. A sufficient condition to its existence is presente...A unknown input observer （UIO） design for a class of linear time-delay systems when the observer error can＇t completely decouple from unknown input is dealt with. A sufficient condition to its existence is presented based on Lyapunov stability method. Design problem of the proposed observer is formulated in term of linear matrix inequalities. Two design problems of the observer with internal delay and without internal delay are formulated. Based on H∞ control theory in time-delay systems, the proposed observer is designed in term of linear matrix inequalities （LMI）. A design algorithm is proposed. The effective of the proposed approach is illustrated by a numerical example.展开更多
This work proposes a robust fault detection and isolation scheme for discrete-time systems subject to actuator faults,in which a bank of H_/H∞fault detection unknown input observers(UIOs)and a zonotopic threshold ana...This work proposes a robust fault detection and isolation scheme for discrete-time systems subject to actuator faults,in which a bank of H_/H∞fault detection unknown input observers(UIOs)and a zonotopic threshold analysis strategy are considered.In observer design,finite-frequency H_index based on the generalized Kalman-Yakubovich-Popov lemma and H∞technique are utilized to evaluate worst-case fault sensitivity and disturbance attenuation performance,respectively.The proposed H_/H∞fault detection observers are designed to be insensitive to the corresponding actuator fault only,but sensitive to others.Then,to overcome the weakness of predefining threshold for FDI decision-making,this work proposes a zonotopic threshold analysis method to evaluate the generated residuals.The FDI decision-making relies on the evaluation with a dynamical zonotopic threshold.Finally,numerical simulations are provided to show the feasibility of the proposed scheme.展开更多
In recent years, cyber attacks have posed great challenges to the development of cyber-physical systems. It is of great significance to study secure state estimation methods to ensure the safe and stable operation of ...In recent years, cyber attacks have posed great challenges to the development of cyber-physical systems. It is of great significance to study secure state estimation methods to ensure the safe and stable operation of the system. This paper proposes a secure state estimation for multi-input and multi-output continuous-time linear cyber-physical systems with sparse actuator and sensor attacks. First, for sparse sensor attacks, we propose an adaptive switching mechanism to mitigate the impact of sparse sensor attacks by filtering out their attack modes. Second, an unknown input sliding mode observer is designed to not only observe the system states, sensor attack signals, and measurement noise present in the system but also counteract the effects of sparse actuator attacks through an unknown input matrix. Finally, for the design of an unknown input sliding mode state observer, the feasibility of the observing system is demonstrated by means of Lyapunov functions. Additionally, simulation experiments are conducted to show the effectiveness of this method.展开更多
In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condit...In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condition is removed. The procedure of calculating the parameter matrices of the full-order observer is also presented. Compared with the existing auxiliary outputs based sliding-mode observers, the designed observer has a simpler design procedure, which is systematic and does not involve solving linear matrix inequalities. The simulation results show that the proposed method is effective.展开更多
Presents a systematic design method of reduced order dynamical compensator via the parametric representations of eigenstructure assignment for linear system, which provides maximum degree of freedom, and can be easily...Presents a systematic design method of reduced order dynamical compensator via the parametric representations of eigenstructure assignment for linear system, which provides maximum degree of freedom, and can be easily used for the design of a linear system with unknown inputs under some conditions. Even when these conditions are not satisfied, the lower order dynamical compensator can also be designed under some relaxed conditions. Some examples illustrate that the method is neat, simple and effective.展开更多
A robust delay compensator has been developed for a class of uncertain nonlinear systems with an unknown constant input delay.The control law consists of feedback terms based on the integral of past control values and...A robust delay compensator has been developed for a class of uncertain nonlinear systems with an unknown constant input delay.The control law consists of feedback terms based on the integral of past control values and a novel filtered tracking error,capable of compensating for input delays.Suitable Lyapunov-Krasovskii functionals are used to prove global uniformly ultimately bounded(GUUB)tracking,provided certain sufficient gain conditions,dependent on the bound of the delay,are satisfied.Simulation results illustrate the performance and robustness of the controller for different values of input delay.展开更多
Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information exchanges.The purpose of this paper is to develop a joint recur...Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information exchanges.The purpose of this paper is to develop a joint recursive filtering scheme that estimates both unknown inputs and system states for multi-rate CPSs with unknown inputs.In cyberspace,the information transmission between the local joint filter and the sensors is governed by an adaptive event-triggered strategy.Furthermore,the desired parameters of joint filters are determined by a set of algebraic matrix equations in a recursive way,and a sufficient condition verifying the boundedness of filtering error covariance is found by resorting to some algebraic operation.A state fusion estimation scheme that uses local state estimation is proposed based on the covariance intersection(CI)based fusion conception.Lastly,an illustrative example demonstrates the effectiveness of the proposed adaptive event-triggered recursive filtering algorithm.展开更多
Dynamic state estimation(DSE)accurately tracks the dynamics of power systems and demonstrates the evolution of the system state in real time.This paper proposes a DSE approach for a doubly-fed induction generator(DFIG...Dynamic state estimation(DSE)accurately tracks the dynamics of power systems and demonstrates the evolution of the system state in real time.This paper proposes a DSE approach for a doubly-fed induction generator(DFIG)with unknown inputs based on adaptive interpolation and cubature Kalman filter(AICKF-UI).DFIGs adopt different control strategies in normal and fault conditions;thus,the existing DSE approaches based on the conventional control model of DFIG are not applicable in all cases.Consequently,the DSE model of DFIGs is reformulated to consider the converter controller outputs as unknown inputs,which are estimated together with the DFIG dynamic states by an exponential smoothing model and augmented-state cubature Kalman filter.Furthermore,as the reporting rate of existing synchro-phasor data is not sufficiently high to capture the fast dynamics of DFIGs,a large estimation error may occur or the DSE approach may diverge.To this end,in this paper,a local-truncation-error-guided adaptive interpolation approach is developed.Extensive simulations conducted on a wind farm and the modified IEEE 39-bus test system show that the proposed AICKF-UI can(1)effectively address the divergence issues of existing cubature Kalman filters while being computationally more efficient;(2)accurately track the dynamic states and unknown inputs of the DFIG;and(3)deal with various types of system operating conditions such as time-varying wind and different system faults.展开更多
The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected vehicles.This paper presents a solution to estimate sensor and actuator c...The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected vehicles.This paper presents a solution to estimate sensor and actuator cyber-attacks in CVSs.A novel method is proposed that utilizes an augmented system representation technique and a nonlinear unknown input observer(UIO)to achieve asymptotic estimation of both CVS dynamics and cyber-attacks.The nonlinear CVS dynamics is represented in a Takagi–Sugeno(TS)fuzzy form with nonlinear consequents,which allows for the effective use of the differential mean value theorem to handle unmeasured premise variables.Furthermore,via Lyapunov stability theory sufficient conditions are proposed,expressed in terms of linear matrix inequalities,to design TS fuzzy UIO.Several test scenarios are performed with high-fidelity Simulink-CarSim co-simulations to show the effectiveness of the proposed cyber-attack estimation method.展开更多
In this note,we consider a new unknown input observer design for nonlinear systems.The main idea consists in determining the estimation error and mean value theorem parameters(β)to introduce them into proposed observ...In this note,we consider a new unknown input observer design for nonlinear systems.The main idea consists in determining the estimation error and mean value theorem parameters(β)to introduce them into proposed observer structure.This process is designed on the basis of mean value theorem and genetic algorithm.The stability study relies on the use of a classical quadratic Lyapunov function.The observer’s gains are determined systematically.For the validation of theoretical development proposed in this paper,we consider two practical realizations that deals with the secure communication problem.展开更多
Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly...Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input,and the state model and the measurement model are both with the same unknown interference input.State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs(dual-UI)with different physical meanings and mathematical definitions is concerned here.Firstly,the decoupling condition with the Unknown Interference input in the State model(S-UI)is shown,which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs(M-UI)appearing in the state model and the measurement model.Then,through defining the Differential term of the adjacent M-UI(M-UID),the equivalent system with only M-UID in the state model is obtained.Finally,considering the design freedom of the equivalent system,the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate,respectively.Two simulation cases verify the effectiveness and superiority compared with the traditional methods.展开更多
For a class of discrete switched systems with unknown input, an unknown input observer design method is proposed under the premise of changes along time axis but no changes along iteration axis. This method applies th...For a class of discrete switched systems with unknown input, an unknown input observer design method is proposed under the premise of changes along time axis but no changes along iteration axis. This method applies the iterative learning control thought to the design of unknown input observer, construets the unknown input observer by introducing virtual input signal, and uses the error signal generated from the actual system output and the observer output to correct repetitively the virtual input, which gradually approxima tes the actual unknown input as the it erations increase. Moreover, the convergence of the observer is strictly proved based on contraction mapping theory, as well as the convergence condition is given. The theoretical analysis indicates that designed unknown input observer can accurately estimate the state and unknown input of the system simultaneously. Simulation example further verifies the effectiveness of the proposed algorithm.展开更多
Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,whic...Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.展开更多
This paper investigates the problem of state estimation for discrete-time stochastic linear systems, where additional knowledge on the unknown inputs is available at an aggregate level and the knowledge on the missing...This paper investigates the problem of state estimation for discrete-time stochastic linear systems, where additional knowledge on the unknown inputs is available at an aggregate level and the knowledge on the missing measurements can be described by a known stochastic distribution. Firstly, the available knowledge on the unknown inputs and the state equation is used to form the prior distribution of the state vector at each time step. Secondly, to obtain an analytically tractable likelihood function, the effect of missing measurements is broken down into a systematic part and a random part, and the latter is modeled as part of the observation noise. Then, a recursive filter is obtained based on Bayesian inference. Finally, a numerical example is provided to evaluate the performance of the proposed methods.展开更多
Gyroscopes are one of the most interesting and everlasting nonlinear nonautonomous dynamical systems that exhibit very complex dynamical behavior such as chaos. In this paper, the problem of robust stabilization of th...Gyroscopes are one of the most interesting and everlasting nonlinear nonautonomous dynamical systems that exhibit very complex dynamical behavior such as chaos. In this paper, the problem of robust stabilization of the nonlinear non-autonomous gyroscopes in a given finite time is studied. It is assumed that the gyroscope system is perturbed by model uncertainties, external disturbances, and unknown parameters. Besides, the effects of input nonlinearities are taken into account. Appropriate adaptive laws are proposed to tackle the unknown parameters. Based on the adaptive laws and the finite-time control theory, discontinuous finite-time control laws are proposed to ensure the finite-time stability of the system. The finite-time stability and convergence of the closed-loop system are analytically proved. Some numerical simulations are presented to show the efficiency of the proposed finite-time control scheme and to validate the theoretical results.展开更多
基金co-supported by the National Natural Science Foundation of China (Nos. 51620105010, 51575019 and 51675019)National Basic Research Program of China (No. 2014CB046400)111 Program of China
文摘Hydraulic piston pumps are commonly used in aircraft. In order to improve the viability of aircraft and energy efficiency, intelligent variable pressure pump systems have been used in aircraft hydraulic systems more and more widely. Efficient fault diagnosis plays an important role in improving the reliability and performance of hydraulic systems. In this paper, a fault diagnosis method of an intelligent hydraulic pump system（IHPS） based on a nonlinear unknown input observer（NUIO） is proposed. Different from factors of a full-order Luenberger-type unknown input observer, nonlinear factors of the IHPS are considered in the NUIO. Firstly, a new type of intelligent pump is presented, the mathematical model of which is established to describe the IHPS. Taking into account the real-time requirements of the IHPS and the special structure of the pump, the mechanism of the intelligent pump and failure modes are analyzed and two typical failure modes are obtained. Furthermore, a NUIO of the IHPS is performed based on the output pressure and swashplate angle signals. With the residual error signals produced by the NUIO, online intelligent pump failure occurring in real-time can be detected. Lastly, through analysis and simulation, it is confirmed that this diagnostic method could accurately diagnose and isolate those typical failure modes of the nonlinear IHPS. The method proposed in this paper is of great significance in improving the reliability of the IHPS.
文摘This paper deals with the simultaneous estimation of states and unknown inputs for a class of Lipschitz nonlinear systems using only the measured outputs. The system is assumed to have bounded uncertainties that appear on both the state and output matrices. The observer design problem is formulated as a set of linear constraints which can be easily solved using linear matrix inequalities (LMI) technique. An application based on manipulator arm actuated by a direct current (DC) motor is presented to evaluate the performance of the proposed observer. The observer is applied to estimate both state and faults.
基金Supported by the National Natural Science Foundation of China (No. 60234010, 60574084)the Field Bus Technology & Automation Key Lab of Beijing at North China and the National 973 Program of China (No. 2002CB312200).
文摘Unknown input observer is one of the most famous strategies for robust fault diagnosis of linear systems, but studies on nonlinear cases are not sufficient. On the other hand, the extended Kalman filter （EKF） is wellknown in nonlinear estimation, and its convergence as an observer of nonlinear deterministic system has been derived recently. By combining the EKF and the unknown input Kalman filter, we propose a robust nonlinear estimator called unknown input EKF （UIEKF） and prove its convergence as a nonlinear robust observer under some mild conditions using linear matrix inequality （LMI）. Simulation of a three-tank system “DTS200”, a benchmark in process control, demonstrates the robustness and effectiveness of the UIEKF as an observer for nonlinear systems with uncertainty, and the fault diagnosis based on the UIEKF is found successful.
基金This project was supported by the National Natural Science Foundation of China(60374024)
文摘A unknown input observer （UIO） design for a class of linear time-delay systems when the observer error can＇t completely decouple from unknown input is dealt with. A sufficient condition to its existence is presented based on Lyapunov stability method. Design problem of the proposed observer is formulated in term of linear matrix inequalities. Two design problems of the observer with internal delay and without internal delay are formulated. Based on H∞ control theory in time-delay systems, the proposed observer is designed in term of linear matrix inequalities （LMI）. A design algorithm is proposed. The effective of the proposed approach is illustrated by a numerical example.
基金partially supported by National Key R&D Program of China(2018YFB1304600)National Natural Science Foundation of China(51805021,U1813220)+1 种基金China Postdoctoral Science Foundation Grant(2018M631311)the Fundamental Research Funds for the Central Universities(XK1802-4)
文摘This work proposes a robust fault detection and isolation scheme for discrete-time systems subject to actuator faults,in which a bank of H_/H∞fault detection unknown input observers(UIOs)and a zonotopic threshold analysis strategy are considered.In observer design,finite-frequency H_index based on the generalized Kalman-Yakubovich-Popov lemma and H∞technique are utilized to evaluate worst-case fault sensitivity and disturbance attenuation performance,respectively.The proposed H_/H∞fault detection observers are designed to be insensitive to the corresponding actuator fault only,but sensitive to others.Then,to overcome the weakness of predefining threshold for FDI decision-making,this work proposes a zonotopic threshold analysis method to evaluate the generated residuals.The FDI decision-making relies on the evaluation with a dynamical zonotopic threshold.Finally,numerical simulations are provided to show the feasibility of the proposed scheme.
基金supported by the National Science Foundation of China(Nos.62271293,61903238)the Natural Science Foundation of Shandong Province,China(No.ZR2021MF035)the Social Science Planning Project of Shandong Province,China(No.22CYYJ13).
文摘In recent years, cyber attacks have posed great challenges to the development of cyber-physical systems. It is of great significance to study secure state estimation methods to ensure the safe and stable operation of the system. This paper proposes a secure state estimation for multi-input and multi-output continuous-time linear cyber-physical systems with sparse actuator and sensor attacks. First, for sparse sensor attacks, we propose an adaptive switching mechanism to mitigate the impact of sparse sensor attacks by filtering out their attack modes. Second, an unknown input sliding mode observer is designed to not only observe the system states, sensor attack signals, and measurement noise present in the system but also counteract the effects of sparse actuator attacks through an unknown input matrix. Finally, for the design of an unknown input sliding mode state observer, the feasibility of the observing system is demonstrated by means of Lyapunov functions. Additionally, simulation experiments are conducted to show the effectiveness of this method.
基金Supported by the National Natural Science Foundation of China(No.61203299)
文摘In this paper, a full-order observer which can be fully decoupled from the unknown inputs as the conventional full-order observer does is designed by using auxiliary outputs, but the requirement of the matching condition is removed. The procedure of calculating the parameter matrices of the full-order observer is also presented. Compared with the existing auxiliary outputs based sliding-mode observers, the designed observer has a simpler design procedure, which is systematic and does not involve solving linear matrix inequalities. The simulation results show that the proposed method is effective.
文摘Presents a systematic design method of reduced order dynamical compensator via the parametric representations of eigenstructure assignment for linear system, which provides maximum degree of freedom, and can be easily used for the design of a linear system with unknown inputs under some conditions. Even when these conditions are not satisfied, the lower order dynamical compensator can also be designed under some relaxed conditions. Some examples illustrate that the method is neat, simple and effective.
文摘A robust delay compensator has been developed for a class of uncertain nonlinear systems with an unknown constant input delay.The control law consists of feedback terms based on the integral of past control values and a novel filtered tracking error,capable of compensating for input delays.Suitable Lyapunov-Krasovskii functionals are used to prove global uniformly ultimately bounded(GUUB)tracking,provided certain sufficient gain conditions,dependent on the bound of the delay,are satisfied.Simulation results illustrate the performance and robustness of the controller for different values of input delay.
基金Project supported by the National Natural Science Foundation of China(Nos.62203306 and 61933007)the Shanghai Pujiang Program,China(No.22PJ1412600)the China Postdoctoral Science Foundation(No.2021M702195)。
文摘Cyber-physical systems(CPSs)take on the characteristics of both multiple rates of information collection and processing and the dependency on information exchanges.The purpose of this paper is to develop a joint recursive filtering scheme that estimates both unknown inputs and system states for multi-rate CPSs with unknown inputs.In cyberspace,the information transmission between the local joint filter and the sensors is governed by an adaptive event-triggered strategy.Furthermore,the desired parameters of joint filters are determined by a set of algebraic matrix equations in a recursive way,and a sufficient condition verifying the boundedness of filtering error covariance is found by resorting to some algebraic operation.A state fusion estimation scheme that uses local state estimation is proposed based on the covariance intersection(CI)based fusion conception.Lastly,an illustrative example demonstrates the effectiveness of the proposed adaptive event-triggered recursive filtering algorithm.
基金supported by the National Natural Science Foundation of China(No.51725702)。
文摘Dynamic state estimation(DSE)accurately tracks the dynamics of power systems and demonstrates the evolution of the system state in real time.This paper proposes a DSE approach for a doubly-fed induction generator(DFIG)with unknown inputs based on adaptive interpolation and cubature Kalman filter(AICKF-UI).DFIGs adopt different control strategies in normal and fault conditions;thus,the existing DSE approaches based on the conventional control model of DFIG are not applicable in all cases.Consequently,the DSE model of DFIGs is reformulated to consider the converter controller outputs as unknown inputs,which are estimated together with the DFIG dynamic states by an exponential smoothing model and augmented-state cubature Kalman filter.Furthermore,as the reporting rate of existing synchro-phasor data is not sufficiently high to capture the fast dynamics of DFIGs,a large estimation error may occur or the DSE approach may diverge.To this end,in this paper,a local-truncation-error-guided adaptive interpolation approach is developed.Extensive simulations conducted on a wind farm and the modified IEEE 39-bus test system show that the proposed AICKF-UI can(1)effectively address the divergence issues of existing cubature Kalman filters while being computationally more efficient;(2)accurately track the dynamic states and unknown inputs of the DFIG;and(3)deal with various types of system operating conditions such as time-varying wind and different system faults.
基金supported in part by the Key Research Project of North Minzu University under Grant 2021JCYJ09in part by the French Ministry of Higher Education and Research,in part by the National Center for Scientific Research(CNRS)+5 种基金in part by the ANR CoCoVeIA project(ANR-19-CE22-0009)in part by the ANR HM-Science project(ANR-21-CE48-0021)in part by the Hauts-de-France Region under the project RITMEA CPER 2021-2027in part by the National Natural Science Foundation of China under Grant 62163002in part by the Natural Science Foundation of Ningxia Hui Autonomous Region under Grant 2021AAC05011in part by the Advanced Intelligent Perception and Control Technology Innovative Team of Ningxia.
文摘The detection and mitigation of cyber-attacks in connected vehicle systems(CVSs)are critical for ensuring the security of intelligent connected vehicles.This paper presents a solution to estimate sensor and actuator cyber-attacks in CVSs.A novel method is proposed that utilizes an augmented system representation technique and a nonlinear unknown input observer(UIO)to achieve asymptotic estimation of both CVS dynamics and cyber-attacks.The nonlinear CVS dynamics is represented in a Takagi–Sugeno(TS)fuzzy form with nonlinear consequents,which allows for the effective use of the differential mean value theorem to handle unmeasured premise variables.Furthermore,via Lyapunov stability theory sufficient conditions are proposed,expressed in terms of linear matrix inequalities,to design TS fuzzy UIO.Several test scenarios are performed with high-fidelity Simulink-CarSim co-simulations to show the effectiveness of the proposed cyber-attack estimation method.
文摘In this note,we consider a new unknown input observer design for nonlinear systems.The main idea consists in determining the estimation error and mean value theorem parameters(β)to introduce them into proposed observer structure.This process is designed on the basis of mean value theorem and genetic algorithm.The stability study relies on the use of a classical quadratic Lyapunov function.The observer’s gains are determined systematically.For the validation of theoretical development proposed in this paper,we consider two practical realizations that deals with the secure communication problem.
基金supported by the National Natural Science Foundation of China(Nos.61603040 and 61433003)Yunnan Applied Basic Research Project of China(No.201701CF00037)+1 种基金Guangdong Province Science and Technology Innovation Strategy Special Fund Project,China(No.skjtdzxrwqd2018001)Yunnan Provincial Science and Technology Department Key Research Program(Engineering),China(No.2018BA070)。
文摘Stochastic system state estimation subject to the unknown interference input widely exists in many fields,such as the control,communication,signal processing,and fault diagnosis.However,the research results are mostly limited to the stochastic system in which only the dynamic state model or the measurement model concerns the individual unknown interference input,and the state model and the measurement model are both with the same unknown interference input.State estimate of the stochastic systems where the state model and the measurement model contain dual Unknown Interference inputs(dual-UI)with different physical meanings and mathematical definitions is concerned here.Firstly,the decoupling condition with the Unknown Interference input in the State model(S-UI)is shown,which introduces the decoupled system with the adjacent Measurement concerned Unknown Interference inputs(M-UI)appearing in the state model and the measurement model.Then,through defining the Differential term of the adjacent M-UI(M-UID),the equivalent system with only M-UID in the state model is obtained.Finally,considering the design freedom of the equivalent system,the decoupling filter in the minimum mean square error sense and the adaptive minimum upper filter with different applicable conditions are represented to obtain the optimal and sub-optimal state estimate,respectively.Two simulation cases verify the effectiveness and superiority compared with the traditional methods.
基金supported by the National Natural Science Foundation of China under Grant No.61672304Qiqihar Science and Technology Industrial Projects under Grant No.GYGG-201620the Fundamental Research Funds in Heilongjiang Provincial Universities under Grant Nos.135109240 and 135209527
文摘For a class of discrete switched systems with unknown input, an unknown input observer design method is proposed under the premise of changes along time axis but no changes along iteration axis. This method applies the iterative learning control thought to the design of unknown input observer, construets the unknown input observer by introducing virtual input signal, and uses the error signal generated from the actual system output and the observer output to correct repetitively the virtual input, which gradually approxima tes the actual unknown input as the it erations increase. Moreover, the convergence of the observer is strictly proved based on contraction mapping theory, as well as the convergence condition is given. The theoretical analysis indicates that designed unknown input observer can accurately estimate the state and unknown input of the system simultaneously. Simulation example further verifies the effectiveness of the proposed algorithm.
基金Supported by the National Natural Science Foundation of China （21006127）, the National Basic Research Program of China （2012CB720500） and the Science Foundation of China University of Petroleum, Beijing （KYJJ2012-05-28）.
文摘Chemical processes are usually nonlinear singular systems.In this study,a soft sensor using nonlinear singular state observer is established for unknown inputs and uncertain model parameters in chemical processes,which are augmented as state variables.Based on the observability of the singular system,this paper presents a simplified observability criterion under certain conditions for unknown inputs and uncertain model parameters.When the observability is satisfied,the unknown inputs and the uncertain model parameters are estimated online by the soft sensor using augmented nonlinear singular state observer.The riser reactor of fluid catalytic cracking unit is used as an example for analysis and simulation.With the catalyst circulation rate as the only unknown input without model error,one temperature sensor at the riser reactor outlet will ensure the correct estimation for the catalyst circulation rate.However,when uncertain model parameters also exist,additional temperature sensors must be used to ensure correct estimation for unknown inputs and uncertain model parameters of chemical processes.
基金jointly funded by UK Engineering and Physical Sciences Research Council(EPSRC)and BAE System(EP/H501401/1)
文摘This paper investigates the problem of state estimation for discrete-time stochastic linear systems, where additional knowledge on the unknown inputs is available at an aggregate level and the knowledge on the missing measurements can be described by a known stochastic distribution. Firstly, the available knowledge on the unknown inputs and the state equation is used to form the prior distribution of the state vector at each time step. Secondly, to obtain an analytically tractable likelihood function, the effect of missing measurements is broken down into a systematic part and a random part, and the latter is modeled as part of the observation noise. Then, a recursive filter is obtained based on Bayesian inference. Finally, a numerical example is provided to evaluate the performance of the proposed methods.
文摘Gyroscopes are one of the most interesting and everlasting nonlinear nonautonomous dynamical systems that exhibit very complex dynamical behavior such as chaos. In this paper, the problem of robust stabilization of the nonlinear non-autonomous gyroscopes in a given finite time is studied. It is assumed that the gyroscope system is perturbed by model uncertainties, external disturbances, and unknown parameters. Besides, the effects of input nonlinearities are taken into account. Appropriate adaptive laws are proposed to tackle the unknown parameters. Based on the adaptive laws and the finite-time control theory, discontinuous finite-time control laws are proposed to ensure the finite-time stability of the system. The finite-time stability and convergence of the closed-loop system are analytically proved. Some numerical simulations are presented to show the efficiency of the proposed finite-time control scheme and to validate the theoretical results.
