In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam....In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.展开更多
This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance ...This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance control scheme is proposed,which enables the lateral position error of the vehicle to be kept within the prescribed performance boundaries all the time.This is achieved by firstly introducing an improved performance function into the controller design such that the stringent initial condition requirements can be relaxed,which further allows the global prescribed performance control result,and then,developing a multivariable adaptive terminal sliding mode based controller such that both input saturation and parameter uncertainties are handled effectively,which further ensures the robust lane-keeping control.Finally,the proposed control strategy is validated through numerical simulations,demonstrating its effectiveness.展开更多
Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear syste...Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.展开更多
Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncerta...Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.展开更多
The Internet of Things(IoT)technology provides data acquisition,transmission,and analysis to control rehabilitation robots,encompassing sensor data from the robots as well as lidar signals for trajectory planning(desi...The Internet of Things(IoT)technology provides data acquisition,transmission,and analysis to control rehabilitation robots,encompassing sensor data from the robots as well as lidar signals for trajectory planning(desired trajectory).In IoT rehabilitation robot systems,managing nonvanishing uncertainties and input quantization is crucial for precise and reliable control performance.These challenges can cause instability and reduced effectiveness,particularly in adaptive networked control.This paper investigates networked control with guaranteed performance for IoT rehabilitation robots under nonvanishing uncertainties and input quantization.First,input quantization is managed via a quantization-aware control design,ensur stability and minimizing tracking errors,even with discrete control inputs,to avoid chattering.Second,the method handles nonvanishing uncertainties by adjusting control parameters via real-time neural network adaptation,maintaining consistent performance despite persistent disturbances.Third,the control scheme guarantees the desired tracking performance within a specified time,with all signals in the closed-loop system remaining uniformly bounded,offering a robust,reliable solution for IoT rehabilitation robot control.The simulation verifies the benefits and efficacy of the proposed control strategy.展开更多
Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over p...Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.展开更多
This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater pene...This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.展开更多
This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To imp...This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To improve the disturbance rejection capacity of the UAH system in actuator healthy case,an adaptive control method is adopted to cope with the external disturbances and a nominal controller is proposed to stabilize the system.Meanwhile,compensation control inputs are designed to reduce the negative effects derived from actuator faults and input saturation.Based on the backstepping control and inner-outer loop control technologies,a robust adaptive FTC scheme is developed to guarantee the tracking errors convergence.Under the presented FTC controller,the uniform ultimate boundedness of all closed-loop signals is ensured via Lyapunov stability analysis.Simulation results demonstrate the effectiveness of the proposed control algorithm.展开更多
The problem of fault-tolerant control is discussed for the longitudinal model of an airbreathing hypersonic vehicle （AHV） with actuator faults and external disturbances. Firstly, a fault-tolerant control strategy is...The problem of fault-tolerant control is discussed for the longitudinal model of an airbreathing hypersonic vehicle （AHV） with actuator faults and external disturbances. Firstly, a fault-tolerant control strategy is presented for the longitudinal model of an AHV, which guarantees that velocity and altitude track their reference trajectories at an exponential convergence rate. However, this method needs to know the minimum value of the actuator efficiency factor and the upper bound of the external disturbances, which makes it not easy to implement. Then an improved adaptive fault-tolerant control scheme is proposed, where two adaptive laws are employed to estimate the upper bound of the external disturbances and the minimum value of the actuator efficiency factor, respectively. Secondly, the problem of designing a control scheme with control constraints is further considered, and a new adaptive fault-tolerant control strategy with input saturation is designed to guarantee that velocity and altitude track their reference trajectories. Finally, simulation results are given to show the effectiveness of the proposed methods.展开更多
This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a...This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.展开更多
A constrained adaptive neural network control scheme is proposed for a multi-input and multi-output（MIMO） aeroelastic system in the presence of wind gust,system uncertainties,and input nonlinearities consisting of i...A constrained adaptive neural network control scheme is proposed for a multi-input and multi-output（MIMO） aeroelastic system in the presence of wind gust,system uncertainties,and input nonlinearities consisting of input saturation and dead-zone.In regard to the input nonlinearities,the right inverse function block of the dead-zone is added before the input nonlinearities,which simplifies the input nonlinearities into an equivalent input saturation.To deal with the equivalent input saturation,an auxiliary error system is designed to compensate for the impact of the input saturation.Meanwhile,uncertainties in pitch stiffness,plunge stiffness,and pitch damping are all considered,and radial basis function neural networks（RBFNNs） are applied to approximate the system uncertainties.In combination with the designed auxiliary error system and the backstepping control technique,a constrained adaptive neural network controller is designed,and it is proven that all the signals in the closed-loop system are semi-globally uniformly bounded via the Lyapunov stability analysis method.Finally,extensive digital simulation results demonstrate the effectiveness of the proposed control scheme towards flutter suppression in spite of the integrated effects of wind gust,system uncertainties,and input nonlinearities.展开更多
A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solvin...A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.展开更多
A new attitude controller is proposed for spacecraft whose actuator has variable input saturation limit. There are three identical flywheels orthogonally mounted on board. Each rotor is driven by a brushless DC motor ...A new attitude controller is proposed for spacecraft whose actuator has variable input saturation limit. There are three identical flywheels orthogonally mounted on board. Each rotor is driven by a brushless DC motor （BLDCM）. Models of spacecraft attitude dynamics and flywheel rotor driving motor electromechanics are discussed in detail. The controller design is similar to saturation limit linear assignment. An auxiliary parameter and a boundary coefficient are imported into the controller to guaran- tee system stability and improve control performance. A time-varying and state-dependent flywheel output torque saturation limit model is established. Stability of the closed-loop control system and asymptotic convergence of system states are proved via Lyapunov methods and LaSalle invariance principle. Boundedness of the auxiliary parameter ensures that the control objective can be achieved, while the boundary parameter＇s value makes a balance between system control performance and flywheel utilization efficiency. Compared with existing controllers, the newly developed controller with variable torque saturation limit can bring smoother control and faster system response. Numerical simulations validate the effectiveness of the controller.展开更多
In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and ...In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and input saturation constraints,an adaptive sliding-mode tracking control strategy for an ET is presented. Compared with the existing control strategies for an ET, input saturation constraints and parameter uncertainties are adequately considered in the proposed control strategy. At first, the nonlinear dynamic model for control of an ET is described. According to the dynamical model, the nonlinear adaptive sliding-mode tracking control method is presented,where parameter adaptive laws and auxiliary design system are employed. Parameter adaptive law is given to estimate the unknown parameter with an ET. An auxiliary system is designed,and its state is utilized in the tracking control method to handle the input saturation. Stability proof and analysis of the adaptive sliding-mode control method is performed by using Lyapunov stability theory. Finally, the reliability and feasibility of the proposed control strategy are evaluated by computer simulation.Simulation research shows that the proposed sliding-mode control strategy can provide good control performance for an ET.展开更多
In this paper, an adaptive neural networks(NNs)tracking controller is proposed for a class of single-input/singleoutput(SISO) non-affine pure-feedback non-linear systems with input saturation. In the proposed approach...In this paper, an adaptive neural networks(NNs)tracking controller is proposed for a class of single-input/singleoutput(SISO) non-affine pure-feedback non-linear systems with input saturation. In the proposed approach, the original input saturated nonlinear system is augmented by a low pass filter.Then, new system states are introduced to implement states transformation of the augmented model. The resulting new model in affine Brunovsky form permits direct and simpler controller design by avoiding back-stepping technique and its complexity growing as done in existing methods in the literature.In controller design of the proposed approach, a state observer,based on the strictly positive real(SPR) theory, is introduced and designed to estimate the new system states, and only two neural networks are used to approximate the uncertain nonlinearities and compensate for the saturation nonlinearity of actuator. The proposed approach can not only provide a simple and effective way for construction of the controller in adaptive neural networks control of non-affine systems with input saturation, but also guarantee the tracking performance and the boundedness of all the signals in the closed-loop system. The stability of the control system is investigated by using the Lyapunov theory. Simulation examples are presented to show the effectiveness of the proposed controller.展开更多
In this paper, we mainly address the position control problem for one-degree of freedom(DOF) link manipulator despite uncertainties and the input saturation via the backstepping technique, active disturbance rejection...In this paper, we mainly address the position control problem for one-degree of freedom(DOF) link manipulator despite uncertainties and the input saturation via the backstepping technique, active disturbance rejection control(ADRC) as well as predefined tracking performance functions. The extended state observer(ESO) is employed to compensate uncertain dynamics and disturbances, and it does not rely on the accurate model of systems. The tracking differentiator(TD) is utilized to substitute the derivative of the virtual control signals, and the explosion of complexity caused by repeated differentiations of nonlinear functions is removed. The auxiliary system is used to deal with the control input limitation, and the tracking accuracy and speed are improved by predefined tracking performance functions.With the help of the input-to-state stability(ISS) and Lyapunov stability theories, it is proven that the tracking error can be gradually converged into arbitrarily small neighborhood of the origin, and the tracking error is adjusted by suitable choice of control parameters. The simulation results are presented for the verification of the theoretical claims.展开更多
In this paper, we study the consensus problem for a class of linear multi-agent systems(MASs) with consideration of input saturation under the self-triggered mechanism. In the context of discrete-time systems, a self-...In this paper, we study the consensus problem for a class of linear multi-agent systems(MASs) with consideration of input saturation under the self-triggered mechanism. In the context of discrete-time systems, a self-triggered strategy is developed to determine the time interval between the adjacent triggers. The triggering condition is designed by using the current sampled consensus error. Furthermore, the consensus control protocol is designed by means of a state feedback approach. It is shown that the considered multi-agent systems can reach consensus with the presented algorithm. Some sufficient conditions are proposed in the form of linear matrix inequalities(LMIs) to show the positively invariant property of the domain of attraction(DOA). Moreover, some sufficient conditions of controller synthesis are provided to enlarge the volume of the DOA and obtain the control gain matrix. A numerical example is simulated to demonstrate the effectiveness of the theoretical analysis results.展开更多
In this paper, the attitude control algorithm of flexible spacecraft with unknown measurement delay and input delay based on disturbance observer is designed. The influence of measurement delay and input delay on the ...In this paper, the attitude control algorithm of flexible spacecraft with unknown measurement delay and input delay based on disturbance observer is designed. The influence of measurement delay and input delay on the attitude control system and disturbance observer is analyzed. The disturbance estimation error equation is transformed into a differential system with a pure delay. Then, the observer gain is chosen based on the 3/2 stability theorem to ensure the stability and disturbance attenuation performance of the pure delay system. Next, the controller gain is designed based on the Linear Matrix Inequality(LMI) approach to guarantee the stability of the composite system and achieve H_∞ performance with two additive delays. The simulation results show that the proposed method can improve the anti-disturbance ability of the attitude control system.展开更多
This paper addresses control for the synchronization of Chen chaotic systems via sector nonlinear inputs. Feedback control, adaptive control, fast sliding mode and robust control approaches based on single state feedb...This paper addresses control for the synchronization of Chen chaotic systems via sector nonlinear inputs. Feedback control, adaptive control, fast sliding mode and robust control approaches based on single state feedback controller are investigated. In these cases, sufficient conditions for the synchronization are obtained analytically. Numerical simulations verify the control performances.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
基金supported in part by the National Natural Science Fundation of China under Grant Nos.62403263 and 62373207in part by the Natural Science Fundation of Qingdao,China under Grant No.24-4-4-zrjj-88-jch+1 种基金in part by the Team Plan for Youth Innovation of Universities in Shandong Province under Grant No.2024KJH148in part by the Foundation of Key Laboratory of Autonomous Systems and Networked Control(South China University of Technology),Ministry of Education under Grant No.2024A01.
文摘In this paper,we study the issue of controlling a rotating flexible body-beam system(RFBBS)which consists of a tip mass attached to the free-end and a rigid disk attached to the clamped-end of an Euler-Bernoulli beam.The boundary control input is affected by both unknown disturbance and nonlinear input backlash.First,the input backlash is considered as desired control input combined with a nonlinear input error,converting it to an external disturbance,and then,the control signal is designed through the energy-based control method.Next,the closed-loop system’s stability is analysed through Lyapunov direct method.Finally,the efficacy of the proposed control scheme is tested through numerical simulations utilizing the finite difference method.
基金supported in part by the National Key Research and Development Program of China under Grant 2023YFA1011803in part by Natural Science Foundation of Chongqing,China under Grant CSTB2023NSCQ-MSX0588+2 种基金in part by the Fundamental Research Funds for the Central Universities,China under Grant 2023CDJKYJH047in part by the National Natural Science Foundation of China under Grant 62273064,Grant 61991400,Grant 61991403,Grant 61933012,Grant 62250710167,Grant 62203078in part by Innovation Support Program for International Students Returning to China under Grant cx2022016.
文摘This paper addresses the lane-keeping control problem for autonomous ground vehicles subject to input saturation and uncertain system parameters.An enhanced adaptive terminal sliding mode based prescribed performance control scheme is proposed,which enables the lateral position error of the vehicle to be kept within the prescribed performance boundaries all the time.This is achieved by firstly introducing an improved performance function into the controller design such that the stringent initial condition requirements can be relaxed,which further allows the global prescribed performance control result,and then,developing a multivariable adaptive terminal sliding mode based controller such that both input saturation and parameter uncertainties are handled effectively,which further ensures the robust lane-keeping control.Finally,the proposed control strategy is validated through numerical simulations,demonstrating its effectiveness.
文摘Dear Editor,It is well known that event-triggered control(ETC)is an effective approach in addressing networked control problems for Industry 5.0.Its feasibility,however,is still restricted to canonical nonlinear systems so far.Considering this,a gradient-based adaptive ETC scheme for noncanonical nonlinear systems is newly developed in this letter,where the hysteresis input constraints are considered also.By proper decomposition,the technical issue of handling ETC-induced measurement errors and hysteresis inputs can be transformed into the robustness problem to bounded disturbance-like terms,which is then addressed by integrating a switching modification strategy in adaptive design and developing a novel augmented error-based analysis framework.Experimental results based on a practical piezoactuator confirm the effectiveness of the proposed scheme.
基金National Natural Science Foundation of China(62373102)Jiangsu Natural Science Foundation(BK20221455)Anhui Provincial Key Research and Development Project(2022i01020013)。
文摘Enhancing the stability and performance of practical control systems in the presence of nonlinearity,time delay,and uncertainty remains a significant challenge.Particularly,a class of strict-feedback nonlinear uncertain systems characterized by unknown control directions and time-varying input delay lacks comprehensive solutions.In this paper,we propose an observerbased adaptive tracking controller to address this gap.Neural networks are utilized to handle uncertainty,and a unique coordinate transformation is employed to untangle the coupling between input delay and unknown control directions.Subsequently,a new auxiliary signal counters the impact of time-varying input delay,while a Nussbaum function is introduced to solve the problem of unknown control directions.The leverage of an advanced dynamic surface control technique avoids the“complexity explosion”and reduces boundary layer errors.Synthesizing these techniques ensures that all the closed-loop signals are semi-globally uniformly ultimately bounded(SGUUB),and the tracking error converges to a small region around the origin by selecting suitable parameters.Simulation examples are provided to demonstrate the feasibility of the proposed approach.
基金supported in part by the National Natural Science Foundation of China under Grant 62302475in part by the Research Funds of Centre for Leading Medicine and Advanced Technologies of IHM under Grant 2023IHM01081 and 2023IHM01085+1 种基金in part by the Hefei Municipal Natural Science Foundation under Grant 202328partly by the Anhui Science and Technology Innovation Tackling Plan Project under Grant 202423k09020044。
文摘The Internet of Things(IoT)technology provides data acquisition,transmission,and analysis to control rehabilitation robots,encompassing sensor data from the robots as well as lidar signals for trajectory planning(desired trajectory).In IoT rehabilitation robot systems,managing nonvanishing uncertainties and input quantization is crucial for precise and reliable control performance.These challenges can cause instability and reduced effectiveness,particularly in adaptive networked control.This paper investigates networked control with guaranteed performance for IoT rehabilitation robots under nonvanishing uncertainties and input quantization.First,input quantization is managed via a quantization-aware control design,ensur stability and minimizing tracking errors,even with discrete control inputs,to avoid chattering.Second,the method handles nonvanishing uncertainties by adjusting control parameters via real-time neural network adaptation,maintaining consistent performance despite persistent disturbances.Third,the control scheme guarantees the desired tracking performance within a specified time,with all signals in the closed-loop system remaining uniformly bounded,offering a robust,reliable solution for IoT rehabilitation robot control.The simulation verifies the benefits and efficacy of the proposed control strategy.
基金supported by the National Natural Science Foundation of China(62433014,62373287,62573324,62333005,62273255)in part by the International Exchange Program for Graduate Students of Tongji University(4360143306)+3 种基金in part by the Fundamental Research Funds for Central Universities(22120230311)supported by DeutscheForschungsgemeinschaft(DFG,German Research Foundation)under Germany’s Excellence Strategy(EXC 2075390740016,468094890)support by the Stuttgart Center for Simulation Science(SimTech)the International Max Planck Research School for Intelligent Systems(IMPRS-IS)for supporting Y.Xie。
文摘Dear Editor,This letter proposes a reinforcement learning-based predictive learning algorithm for unknown continuous-time nonlinear systems with observation loss.Firstly,we construct a temporal nonzero-sum game over predictive control input sequences,deriving multiple optimal predictive control input sequences from its solution.
基金supported by the Natural Science Foundation of China No.62303126the project Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.
基金supported in part by the National Natural Science Foundation of China(Nos.61825302,61573184)in part by the Jiangsu Natural Science Foundation of China(No.BK20171417)in part by the Aeronautical Science Foundation of China(No.20165752049)
文摘This paper studies a robust adaptive compensation Fault Tolerant Control(FTC)for the medium-scale Unmanned Autonomous Helicopter(UAH)in the presence of external disturbances,actuator faults and input saturation.To improve the disturbance rejection capacity of the UAH system in actuator healthy case,an adaptive control method is adopted to cope with the external disturbances and a nominal controller is proposed to stabilize the system.Meanwhile,compensation control inputs are designed to reduce the negative effects derived from actuator faults and input saturation.Based on the backstepping control and inner-outer loop control technologies,a robust adaptive FTC scheme is developed to guarantee the tracking errors convergence.Under the presented FTC controller,the uniform ultimate boundedness of all closed-loop signals is ensured via Lyapunov stability analysis.Simulation results demonstrate the effectiveness of the proposed control algorithm.
基金supported by the National Natural Science Foundation of China(9101600461125306+2 种基金61203011)the Program for New Century Excellent Talents in University (NCET-10-0328)the Natural Science Foundation of Jiangsu Province(BK2012327)
文摘The problem of fault-tolerant control is discussed for the longitudinal model of an airbreathing hypersonic vehicle （AHV） with actuator faults and external disturbances. Firstly, a fault-tolerant control strategy is presented for the longitudinal model of an AHV, which guarantees that velocity and altitude track their reference trajectories at an exponential convergence rate. However, this method needs to know the minimum value of the actuator efficiency factor and the upper bound of the external disturbances, which makes it not easy to implement. Then an improved adaptive fault-tolerant control scheme is proposed, where two adaptive laws are employed to estimate the upper bound of the external disturbances and the minimum value of the actuator efficiency factor, respectively. Secondly, the problem of designing a control scheme with control constraints is further considered, and a new adaptive fault-tolerant control strategy with input saturation is designed to guarantee that velocity and altitude track their reference trajectories. Finally, simulation results are given to show the effectiveness of the proposed methods.
基金supported by National Natural Science Foundation of China(Nos.61603114,61673135)the Fundamental Research Funds for the Central Universities of China(No.HIT.NSRIF.201826)
文摘This study presents an improved data-driven Model-Free Adaptive Control(MFAC)strategy for attitude stabilization of a partially constrained combined spacecraft with external disturbances and input saturation. First, a novel dynamic linearization data model for the partially constrained combined spacecraft with external disturbances is established. The generalized disturbances composed of external disturbances and dynamic linearization errors are then reconstructed by a Discrete Extended State Observer(DESO). With the dynamic linearization data model and reconstructed information, a DESO-MFAC strategy for the combined spacecraft is proposed based only on input and output data. Next, the input saturation is overcome by introducing an antiwindup compensator. Finally, numerical simulations are carried out to demonstrate the effectiveness and feasibility of the proposed controller when the dynamic properties of the partially constrained combined spacecraft are completely unknown.
基金supported by the National Natural Science Foundation of China(Nos.61473307 and 61304120)the Aeronautical Science Foundation of China(No. 20155896026)
文摘A constrained adaptive neural network control scheme is proposed for a multi-input and multi-output（MIMO） aeroelastic system in the presence of wind gust,system uncertainties,and input nonlinearities consisting of input saturation and dead-zone.In regard to the input nonlinearities,the right inverse function block of the dead-zone is added before the input nonlinearities,which simplifies the input nonlinearities into an equivalent input saturation.To deal with the equivalent input saturation,an auxiliary error system is designed to compensate for the impact of the input saturation.Meanwhile,uncertainties in pitch stiffness,plunge stiffness,and pitch damping are all considered,and radial basis function neural networks（RBFNNs） are applied to approximate the system uncertainties.In combination with the designed auxiliary error system and the backstepping control technique,a constrained adaptive neural network controller is designed,and it is proven that all the signals in the closed-loop system are semi-globally uniformly bounded via the Lyapunov stability analysis method.Finally,extensive digital simulation results demonstrate the effectiveness of the proposed control scheme towards flutter suppression in spite of the integrated effects of wind gust,system uncertainties,and input nonlinearities.
基金Supported by the National Natural Science Foundation of China (No.60374037, No.60574036), the Program for New Century Excellent Talents in University of China (NCET), and the Specialized Research Fund for the Doctoral Program of Higher Edu-cation of China (No.20050055013).
文摘A constrained decoupling (generalized predictive control) GPC algorithm is proposed for MIMO (malti-input multi-output) system. This algorithm takes account of all constraints of inputs and their increments. By solving matrix equations, the multi-step predictive decoupling controllers are realized. This algorithm need not solve Diophantine functions, and weakens the cross-coupling of the variables. At last the simulation results demon- strate the effectiveness of this proposed strategy.
基金National Natural Science Foundation of China(10902003)
文摘A new attitude controller is proposed for spacecraft whose actuator has variable input saturation limit. There are three identical flywheels orthogonally mounted on board. Each rotor is driven by a brushless DC motor （BLDCM）. Models of spacecraft attitude dynamics and flywheel rotor driving motor electromechanics are discussed in detail. The controller design is similar to saturation limit linear assignment. An auxiliary parameter and a boundary coefficient are imported into the controller to guaran- tee system stability and improve control performance. A time-varying and state-dependent flywheel output torque saturation limit model is established. Stability of the closed-loop control system and asymptotic convergence of system states are proved via Lyapunov methods and LaSalle invariance principle. Boundedness of the auxiliary parameter ensures that the control objective can be achieved, while the boundary parameter＇s value makes a balance between system control performance and flywheel utilization efficiency. Compared with existing controllers, the newly developed controller with variable torque saturation limit can bring smoother control and faster system response. Numerical simulations validate the effectiveness of the controller.
基金partially supported by the National Natural Science Foundation of China(61773189)Natural Science Fundamental of Liaoning Province(20170540443)the Program for Liaoning Innovative Research Team in University(LT2016006)
文摘In modern vehicles, electronic throttle(ET) has been widely utilized to control the airflow into gasoline engine. To solve the control difficulties with an ET, such as strong nonlinearity,unknown model parameters and input saturation constraints,an adaptive sliding-mode tracking control strategy for an ET is presented. Compared with the existing control strategies for an ET, input saturation constraints and parameter uncertainties are adequately considered in the proposed control strategy. At first, the nonlinear dynamic model for control of an ET is described. According to the dynamical model, the nonlinear adaptive sliding-mode tracking control method is presented,where parameter adaptive laws and auxiliary design system are employed. Parameter adaptive law is given to estimate the unknown parameter with an ET. An auxiliary system is designed,and its state is utilized in the tracking control method to handle the input saturation. Stability proof and analysis of the adaptive sliding-mode control method is performed by using Lyapunov stability theory. Finally, the reliability and feasibility of the proposed control strategy are evaluated by computer simulation.Simulation research shows that the proposed sliding-mode control strategy can provide good control performance for an ET.
文摘In this paper, an adaptive neural networks(NNs)tracking controller is proposed for a class of single-input/singleoutput(SISO) non-affine pure-feedback non-linear systems with input saturation. In the proposed approach, the original input saturated nonlinear system is augmented by a low pass filter.Then, new system states are introduced to implement states transformation of the augmented model. The resulting new model in affine Brunovsky form permits direct and simpler controller design by avoiding back-stepping technique and its complexity growing as done in existing methods in the literature.In controller design of the proposed approach, a state observer,based on the strictly positive real(SPR) theory, is introduced and designed to estimate the new system states, and only two neural networks are used to approximate the uncertain nonlinearities and compensate for the saturation nonlinearity of actuator. The proposed approach can not only provide a simple and effective way for construction of the controller in adaptive neural networks control of non-affine systems with input saturation, but also guarantee the tracking performance and the boundedness of all the signals in the closed-loop system. The stability of the control system is investigated by using the Lyapunov theory. Simulation examples are presented to show the effectiveness of the proposed controller.
基金supported in part by the National Natural Science Foundation of China (61873130,61533010,61503194,61633016)the Natural Science Foundation of Jiangsu Province (BK20140877)+2 种基金the Research and Development Program of Jiangsu (BE2016184)the Jiangsu Government Scholarship for Overseas Studies (2017-037)1311 Talent Project of Nanjing University of Posts and Telecommunications
文摘In this paper, we mainly address the position control problem for one-degree of freedom(DOF) link manipulator despite uncertainties and the input saturation via the backstepping technique, active disturbance rejection control(ADRC) as well as predefined tracking performance functions. The extended state observer(ESO) is employed to compensate uncertain dynamics and disturbances, and it does not rely on the accurate model of systems. The tracking differentiator(TD) is utilized to substitute the derivative of the virtual control signals, and the explosion of complexity caused by repeated differentiations of nonlinear functions is removed. The auxiliary system is used to deal with the control input limitation, and the tracking accuracy and speed are improved by predefined tracking performance functions.With the help of the input-to-state stability(ISS) and Lyapunov stability theories, it is proven that the tracking error can be gradually converged into arbitrarily small neighborhood of the origin, and the tracking error is adjusted by suitable choice of control parameters. The simulation results are presented for the verification of the theoretical claims.
基金supported by the National Natural Science Foundation of China(61921004,61520106009,U1713209,61973074)the Project Funded by the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘In this paper, we study the consensus problem for a class of linear multi-agent systems(MASs) with consideration of input saturation under the self-triggered mechanism. In the context of discrete-time systems, a self-triggered strategy is developed to determine the time interval between the adjacent triggers. The triggering condition is designed by using the current sampled consensus error. Furthermore, the consensus control protocol is designed by means of a state feedback approach. It is shown that the considered multi-agent systems can reach consensus with the presented algorithm. Some sufficient conditions are proposed in the form of linear matrix inequalities(LMIs) to show the positively invariant property of the domain of attraction(DOA). Moreover, some sufficient conditions of controller synthesis are provided to enlarge the volume of the DOA and obtain the control gain matrix. A numerical example is simulated to demonstrate the effectiveness of the theoretical analysis results.
基金supported by the National Natural Science Foundation of China (Nos. 61627810, 61320106010, 61633003, 61661136007 and 61603021)the Program for Changjiang Scholars and Innovative Research Team, China (No. IRT_16R03)Innovative Research Team of National Natural Science Foundation of China (No. 61421063)
文摘In this paper, the attitude control algorithm of flexible spacecraft with unknown measurement delay and input delay based on disturbance observer is designed. The influence of measurement delay and input delay on the attitude control system and disturbance observer is analyzed. The disturbance estimation error equation is transformed into a differential system with a pure delay. Then, the observer gain is chosen based on the 3/2 stability theorem to ensure the stability and disturbance attenuation performance of the pure delay system. Next, the controller gain is designed based on the Linear Matrix Inequality(LMI) approach to guarantee the stability of the composite system and achieve H_∞ performance with two additive delays. The simulation results show that the proposed method can improve the anti-disturbance ability of the attitude control system.
基金This work was partially supported by Nature Science Foundation of China (No. 60374037, 60574036)the Specialized Research Fund for the Doctoral Program of Higher Education of China (No. 20050055013)the Program for New Century Excellent Talents of China (NCET)
文摘This paper addresses control for the synchronization of Chen chaotic systems via sector nonlinear inputs. Feedback control, adaptive control, fast sliding mode and robust control approaches based on single state feedback controller are investigated. In these cases, sufficient conditions for the synchronization are obtained analytically. Numerical simulations verify the control performances.
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.
