This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing th...This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.展开更多
The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the S...The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the STT missile is designed based on nonlinear model predictive control(NMPC)using Taylor series expansion,after which,via a neural network(NN),unknown functions are approximated.The present study also evaluates an adaptive optimal observer of a new strategy-based nonlinear system.Specifically,to estimate the missile states such as normal acceleration and its derivatives for the future,originally the Taylor series states expansion was gained to any specified order,based on their receding horizons.To address the problem of prediction error,an analytic solution was prepared that led to a closed form regarding the nonlinear optimal observer.Out of the gains resulting from the analytic solution,as developed for the problem of prediction error,the selection of the proposed observer gain was optimally conducted to meet the stability condition.Thus,combining the adaptive predictive autopilot and the adaptive optimal observer scheme was implemented to secure the performance,which needed only estimated normal acceleration and its derivatives.Meanwhile,no angular velocity measurement or wind angle estimation was required.Ultimately,the proposed technique was found effective,as confirmed by the qualitative simulation results.展开更多
This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external di...This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.展开更多
Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative con...Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.展开更多
This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loo...This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.展开更多
The augmented evolution equation is established under the framework of the Variation Evolving Method(VEM)that seeks optimal solutions by solving the transformed Initial-Value Problems(IVPs).To improve the numerical pe...The augmented evolution equation is established under the framework of the Variation Evolving Method(VEM)that seeks optimal solutions by solving the transformed Initial-Value Problems(IVPs).To improve the numerical performance,its compact form is developed herein.Through replacing the states and costates variation evolution with that of the controls,the dimension-reduced Evolution Partial Differential Equation(EPDE)only solves the control variables along the variation time to get the optimal solution,and the initial conditions for the definite solution may be arbitrary.With this equation,the scale of the resulting IVPs,obtained via the semi-discrete method,is significantly reduced and they may be solved with common Ordinary Differential Equation(ODE)integration methods conveniently.Meanwhile,the state and the costate dynamics share consistent stability in the numerical computation and this avoids the intrinsic numerical difficulty as in the indirect methods.Numerical examples are solved and it is shown that the compact form evolution equation outperforms the primary form in the precision,and the efficiency may be higher for the dense discretization.Actually,it is uncovered that the compact form of the augmented evolution equation is a continuous realization of the Newton type iteration mechanism.展开更多
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
In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typica...In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.展开更多
The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is...The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.展开更多
This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the ...This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the design process,we transform the studied system into the form of a fully actuated system through a state transformation.Then,to address the unknown nonlinear functions and actuator fault parameters,we employ neural networks and adaptive estimation techniques,respectively.Moreover,to reduce the control cost and improve the control efficiency,we introduce event-triggered inputs into the control strategy.It is proved by the Lyapunov stability analysis that all signals of the closed-loop system are bounded and the output of system eventually converge to a bounded region.The efficacy of the control approach is ultimately demonstrated via the simulation of an actual machine feeding system.展开更多
Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score ...Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.展开更多
This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consen...This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.展开更多
This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanis...This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanism is presented to structure the adaptive integral terminal sliding mode control(SMC)strategy.The control design consists of compensation control and nominal control,which improves the rapidity and accuracy of trajectory tracking.The smooth saturation model based on the error function is applied to approximate the voltage saturation phenomenon.Additionally,to deal with the adverse effects of various unknown disturbances,including model parameter uncertainties and unknown external load disturbances,an improved disturbance observer(DO)is proposed.This observer effectively suppresses the fluctuations caused by fixed gain during the starting period of the system.Finally,the experimental results under different conditions show that the proposed strategy has good tracking and disturbance suppression performances.展开更多
This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of vi...This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.展开更多
In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box id...In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only.The main challenge is how to convert the infinitely long PLC signals into an event sequence,which is the foundation for subsequent modeling.The current algorithms are confronted with a number of challenges,including an exponential increase in the number of transitions,high time complexity,and susceptibility to noisy signals.To solve these problems,this paper proposes a new method for converting PLC signals into a transition sequence.The method is based on the principles of Boolean absorption law,which filters out noise information in the I/O signals.Then firing functions representing input–output causality are constructed from the filtered signals.Finally,the original signal sequence is traversed to generate a transition sequence.The experimental results show that these methods can rapidly identify a transition sequence.Compared to traditional methods,the proposed algorithms have polynomial time complexity.展开更多
1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequen...1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequential design simplification:real-time estimation and online cancellation of the“total disturbance”conceived as the lumped effect of unknown internal dynamics and external inputs.The simplified design then proceeds in a customary fashion for the ideally remaining system model,which is devoid of the total disturbance.展开更多
The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results ar...The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results are illustrated by wave and beam equations with simulation.展开更多
In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial...In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.展开更多
Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of thr...Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.展开更多
This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems posses...This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.展开更多
基金supported in part by the National Natural Science Foundation of China under Grants 62073124 and U1804150.
文摘This paper explores the algebraic essence of universal logic functions(ULFs)from an algebraic perspective.Under the framework of semi-tensor product of matrices,the“sequential nature”of ULFs is revealed.Utilizing the nature,a technique called universal transformation method is proposed,by which any ULF can be transformed into an equivalent expression with desired features that facilitate achieving specific objectives,such as modeling,analyzing and synthesizing universal logical systems.Furthermore,several useful logical operators are constructed in a mixed-dimensional situation,including power-raising operator,power-descending operator,erasure operator,and appending operator.Finally,these results are applied to model and analyze finite state machines and their networks,which demonstrate the practical value of the method and operators.
文摘The objective of the current study is to investigate an adaptive predictive observer-based autopilot for a skid-to-turn(STT)missile model with uncertainties and unknown dynamic equations.A predictive control for the STT missile is designed based on nonlinear model predictive control(NMPC)using Taylor series expansion,after which,via a neural network(NN),unknown functions are approximated.The present study also evaluates an adaptive optimal observer of a new strategy-based nonlinear system.Specifically,to estimate the missile states such as normal acceleration and its derivatives for the future,originally the Taylor series states expansion was gained to any specified order,based on their receding horizons.To address the problem of prediction error,an analytic solution was prepared that led to a closed form regarding the nonlinear optimal observer.Out of the gains resulting from the analytic solution,as developed for the problem of prediction error,the selection of the proposed observer gain was optimally conducted to meet the stability condition.Thus,combining the adaptive predictive autopilot and the adaptive optimal observer scheme was implemented to secure the performance,which needed only estimated normal acceleration and its derivatives.Meanwhile,no angular velocity measurement or wind angle estimation was required.Ultimately,the proposed technique was found effective,as confirmed by the qualitative simulation results.
基金supported in part by the Beijing Natural Science Foundation under Grant 4252050in part by the National Science Fund for Distinguished Young Scholars under Grant 62425304in part by the Basic Science Center Programs of NSFC under Grant 62088101.
文摘This paper investigates the consensus tracking control problem for high order nonlinear multi-agent systems subject to non-affine faults,partial measurable states,uncertain control coefficients,and unknown external disturbances.Under the directed topology conditions,an observer-based finite-time control strategy based on adaptive backstepping and is proposed,in which a neural network-based state observer is employed to approximate the unmeasurable system state variables.To address the complexity explosion problem associated with the backstepping method,a finite-time command filter is incorporated,with error compensation signals designed to mitigate the filter-induced errors.Additionally,the Butterworth low-pass filter is introduced to avoid the algebraic ring problem in the design of the controller.The finite-time stability of the closed-loop system is rigorously analyzed with the finite-time Lyapunov stability criterion,validating that all closed-loop signals of the system remain bounded within a finite time.Finally,the effectiveness of the proposed control strategy is verified through a simulation example.
基金supported by the Fundamental Research Funds for the Central Universities of China(FRF-TP-24-058A)with additional support from the National Key Laboratory of Helicopter Aeromechanics(2024-ZSJ-LB-02-02).
文摘Considering the impact of terminal impact time constraints and the state information of maneuvering targets on the guidance accuracy in multi-UAV cooperative guidance,this paper proposes an impact time cooperative control guidance law(ITCCG)that combines the optimal error dynamics with an improved adaptive cubature Kalman filter(IACKF)algorithm.First,a terminal impact time feedback term is introduced into proportional navigation guidance based on the relative virtual guidance model,and terminal time control is achieved through optimal error dynamics.Then,the Huber loss function is used to reduce the impact of measurement outliers,and the diagonal decomposition is applied to address the issue of non-positive definite matrices that cannot undergo Cholesky decomposition.Finally,the ITCCG and IACKF algorithms combined achieve multi-UAV time-cooperated guidance based on maneuvering target state estimation.Simulation results show that the proposed algorithm effectively reduces the target state estimation error and achieves cooperative guidance within the desired time frame.
文摘This paper proposes a robust control-oriented identification method for errors-in-variables(EIV)systems in output feedbacks using frequency-response(FR)experimental data.An important relation between such a closed-loop EIV system and its coprime factor(CF)uncertainty description is first derived,based on which the FR measurements suitable for plant CF identification are able to be generated.Different factorizations of a given controller in the closed-loop system can be made best use to adjust right coprime factors(RCFs)of the plant so as to realize an improvement on the signal-to-noise ratio of identification experimental data.Subsequently,a nominal RCF model is estimated by linear matrix inequalities from the applicable FR measurements and its associated worst-case errors are quantified from a priori and a posteriori information on the underlying system.A resulting RCF perturbation model set can then be described by the nominal RCF model and its worst-case error bounds.Such a model set capable of being stabilized by the given controller is ready for its robust stabilizing controller redesign and robust performance analysis.Finally,a numerical simulation is given to show the efficacy of the proposed identification method.
基金supported by the National Nature Science Foundation of China under Grant No.11902332。
文摘The augmented evolution equation is established under the framework of the Variation Evolving Method(VEM)that seeks optimal solutions by solving the transformed Initial-Value Problems(IVPs).To improve the numerical performance,its compact form is developed herein.Through replacing the states and costates variation evolution with that of the controls,the dimension-reduced Evolution Partial Differential Equation(EPDE)only solves the control variables along the variation time to get the optimal solution,and the initial conditions for the definite solution may be arbitrary.With this equation,the scale of the resulting IVPs,obtained via the semi-discrete method,is significantly reduced and they may be solved with common Ordinary Differential Equation(ODE)integration methods conveniently.Meanwhile,the state and the costate dynamics share consistent stability in the numerical computation and this avoids the intrinsic numerical difficulty as in the indirect methods.Numerical examples are solved and it is shown that the compact form evolution equation outperforms the primary form in the precision,and the efficiency may be higher for the dense discretization.Actually,it is uncovered that the compact form of the augmented evolution equation is a continuous realization of the Newton type iteration mechanism.
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 Natural Science Foundation of China(62373070 and 52272388)in part by the Chongqing Natural Science Foundation(CSTB2024NSCQ-QCXMX0054,CSTB2022NSCQ-MSX1225 and CSTC2024YCJH-BGZXM0042)in part by the Key Research and Development Project of Anhui Province(202304a05020060).
文摘In this paper,we consider a multiple-input single-output(MISO)Hammerstein system whose inputs and output are disturbed by unknown Gaussian white measurement noises.The parameter estimation of such a system is a typical errors-in-variables(EIV)nonlinear system identification problem.This paper proposes a bias-correction least squares(BCLS)identification methods to compute a consistent estimate of EIV MISO Hammerstein systems from noisy data.To obtain the unbiased parameter estimates of EIV MISO Hammerstein system,the analytical expression of estimated bias for the standard least squares(LS)algorithm is derived first,which is a function about the variances of noises.And then a recursive algorithm is proposed to estimate the unknown term of noises variances from noisy data.Finally,based on bias estimation scheme,the bias caused by the correlation between the input–output signals exciting the true system and the corresponding measurement noise,resulting in unbiased parameter estimates of the EIV MISO Hammerstein system.The performance of the proposed method is demonstrated through a simulation example and a chemical continuously stirred tank reactor(CSTR)system.
基金part supported by the National Natural Science Foundation(62203034,62273126,62203035)the Ling-Yan Research and Development Project of Zhejiang Province of China(2023C03185)。
文摘The focus of this paper is on distributed average tracking(DAT)in the context of external disturbances,utilizing an event-triggered control mechanism.First,an event-triggered anti-disturbance DAT(ETAD-DAT)algorithm is proposed to reduce communication load in networked control systems by redesigning existing anti-disturbance DAT algorithms and disturbance observers.Furthermore,a fully distributed event-triggering condition is employed to schedule event times for each agent.Simulation results demonstrate that the proposed ETAD-DAT algorithm is able to achieve accurate average tracking of multiple time-varying reference signals despite the presence of external disturbances,while the communication efficiency can be improved obviously.
基金supported by the Science Center Program of National Natural Science Foundation of China under Grant 62188101the National Natural Science Foundation of China under Grant 62573265.
文摘This study develops an event-triggered control strategy utilizing the fully actuated system approach for nonlinear interconnected large-scale systems containing actuator failures.First,to reduce the complexity of the design process,we transform the studied system into the form of a fully actuated system through a state transformation.Then,to address the unknown nonlinear functions and actuator fault parameters,we employ neural networks and adaptive estimation techniques,respectively.Moreover,to reduce the control cost and improve the control efficiency,we introduce event-triggered inputs into the control strategy.It is proved by the Lyapunov stability analysis that all signals of the closed-loop system are bounded and the output of system eventually converge to a bounded region.The efficacy of the control approach is ultimately demonstrated via the simulation of an actual machine feeding system.
文摘Pull-ups are a very common fitness exercise that can be seen in many gyms.For athletes,it is very important to perform pull-ups correctly and scientifically.The pull-up scoring method designed in this paper can score the quality of pull-up movement scientifically and objectively,and provide guidance to help athletes better complete the pull-up movement.In this method,the OpenPose algorithm is used to identify the coordinates of skeleton points,and then the coordinate data are processed by a Kalman filter to obtain coordinates closer to the true values.Finally,the filtered data are input into the scoring algorithm designed based on the fuzzy comprehensive evaluation algorithm,and the results of the pull-up quality score and the corresponding guidance are obtained.
基金supported by the National Natural Science Foundation of China(62463007,62463005)the Natural Science Foundation of Hainan Province(625RC710,625MS047)+1 种基金the System Control and Information Processing Education Ministry Key Laboratory Open Funding,China(Scip20240119)the Science Research Funding of Hainan University,China(KYQD(ZR)22180,KYQD(ZR)23180).
文摘This paper focuses on the leader-following positive consensus problems of heterogeneous switched multi-agent systems.First,a state-feedback controller with dynamic compensation is introduced to achieve positive consensus under average dwell time switching.Then sufficient conditions are derived to guarantee the positive consensus.The gain matrices of the control protocol are described using a matrix decomposition approach and the corresponding computational complexity is reduced by resorting to linear programming and co-positive Lyapunov functions.Finally,two numerical examples are provided to illustrate the results obtained.
基金supported by the National Natural Science Foundation under Grant 62273189the Shandong Province Natural Science Foundation under Grant ZR2021MF005Systems Science Plus Joint Research Program of Qingdao University under Grant XT2024201 of China supporting this research work.
文摘This article investigates the anti-disturbance and stabilization problems for the nonlinear uncertain permanent magnet synchronous motor(PMSM)with stator voltage saturation and unknown load.A smooth switching mechanism is presented to structure the adaptive integral terminal sliding mode control(SMC)strategy.The control design consists of compensation control and nominal control,which improves the rapidity and accuracy of trajectory tracking.The smooth saturation model based on the error function is applied to approximate the voltage saturation phenomenon.Additionally,to deal with the adverse effects of various unknown disturbances,including model parameter uncertainties and unknown external load disturbances,an improved disturbance observer(DO)is proposed.This observer effectively suppresses the fluctuations caused by fixed gain during the starting period of the system.Finally,the experimental results under different conditions show that the proposed strategy has good tracking and disturbance suppression performances.
基金supported by the Artificial Intelligence Innovation and Development Special Fund of Shanghai(No.2019RGZN01041)the National Natural Science Foundation of China(No.92048205).
文摘This paper presents a robust finite-time visual servo control strategy for the tracking problem of omni-directional mobile manipulators(OMMs)subject to mismatched disturbances.First,the nonlinear kinematic model of visual servoing for OMMs with mismatched disturbances is explicitly presented to solve the whole-body inverse kinematic problem.Second,a sliding mode observer augmented with an integral terminal sliding mode controller is proposed to handle these uncertainties and ensure that the system converges to a small region around the equilibrium point.The boundary layer technique is employed to mitigate the chattering phenomenon.Furthermore,a strict finite-time Lyapunov stability analysis is conducted.An experimental comparison between the proposed algorithm and a traditional position-based visual servo controller is carried out,and the results demonstrate the superiority of the proposed control algorithm.
基金supported by the Science and Technology Planning Project of Fujian Province,China,under Grant No.2024H0014(2024H01010100).
文摘In industrial control systems,such as power transmission facilities and water treatment plants,Programmable Logic Controllers(PLCs)can work consistently and stably over long periods if there are no faults.Black-box identification aims to automatically construct Petri net models with the help of I/O signals from PLC devices only.The main challenge is how to convert the infinitely long PLC signals into an event sequence,which is the foundation for subsequent modeling.The current algorithms are confronted with a number of challenges,including an exponential increase in the number of transitions,high time complexity,and susceptibility to noisy signals.To solve these problems,this paper proposes a new method for converting PLC signals into a transition sequence.The method is based on the principles of Boolean absorption law,which filters out noise information in the I/O signals.Then firing functions representing input–output causality are constructed from the filtered signals.Finally,the original signal sequence is traversed to generate a transition sequence.The experimental results show that these methods can rapidly identify a transition sequence.Compared to traditional methods,the proposed algorithms have polynomial time complexity.
文摘1 Active Disturbance Rejection Control(ADRC):a brief survey Since its inception,Active Disturbance Rejection Control(ADRC)has re-centered feedback controller design around two fundamental ideas—along with a consequential design simplification:real-time estimation and online cancellation of the“total disturbance”conceived as the lumped effect of unknown internal dynamics and external inputs.The simplified design then proceeds in a customary fashion for the ideally remaining system model,which is devoid of the total disturbance.
文摘The stabilization problem of second-order bilinear systems with time delay is investigated.Feedback controls are chosen so that the strong and exponential stabilization of the system is ensured.The obtained results are illustrated by wave and beam equations with simulation.
文摘In this paper, a bearing-based three-dimensional self-localization and distributed circumnavigation with connectivity preservation and collision avoidance are investigated for a group of quadrotor-type unmanned aerial vehicles (UAVs). A leader–follower structure is adopted, wherein the leader moves with reference dynamics (a target). Different from the existing approaches that necessitate full knowledge of the time-varying reference trajectory, in this paper, it is assumed that only some vehicles (at least one) have access to the bearing relative to the target, and all other vehicles are equipped with sensors capable of measuring the bearings relative to neighboring vehicles. In this paper, a consensus estimator is proposed to estimate the global position for each vehicle using relative bearing measurements and an estimate of neighboring vehicles received from a direct communication network. Then, a continuous robust integral of the sign of the error (RISE) control approach is effectively integrated with the distributed vector field approach to ensure UAV formation orbiting around the moving target while avoiding obstacles and maintaining network links within available communication ranges. In contrast to the classical RISE control rule, a \(\tanh (\cdot )\) function is used instead of the \(\text {sgn}(\cdot )\) function to further decrease the high-gain feedback and to obtain a smoother control signal. Furthermore, by using the localized radial basis function (RBF) neural networks (NNs) in a cooperative way, deterministic learning theory is employed to accurately identify/learn model uncertainties resulting from the attitude dynamics. The convergence of the entire closed-loop system is illustrated using the Lyapunov theory and is shown to be uniformly ultimately bounded. Finally, numerical simulations show the effectiveness of the proposed approach.
文摘Mason Reset(MR),a groundbreaking invention by Clesson E.Mason in 1930 that later became a part of“the universal approach to process control instrumentation”,is revisited in this paper and is shown to consists of three actions:fast(errorcorrection),medium(negative feedback for expanded proportional band)and slow(reset for zero steady-state error).The focus of the paper is on the reset action,generated from a positive feedback loop,and its underlying principles with profound implications to our understanding and practice of automatic control,both basic and advanced.For example,we note that reset control and integral control,contrary to common belief,differ fundamentally in design principle and in practicality.Such difference comes to a head in the event of integrator windup:while reset windup is a problem of actuator saturation,the integrator windup is a runaway situation due to controller instability.In fact,there is no advantage gained in replacing MR with an integrator.In other words,one should not integrate the error directly as in standard PID,since doing so makes the closed-loop system internally unstable.With MR-based control formulated in this paper,there is no such threat of instability and,therefore,no need for any anti-windup mechanisms.Furthermore,the integral control is made scalable in this framework as a tradeoff between the steady-state accuracy and the controller stability.This leads to a novel MR-based control design,scalable in gain and in time to accommodate various process characteristics and design specifications.Simple in construction and transparent in principle,this MR-based control,as a basic framework of design,is readily deployable in scale.
基金supported by the fund of Beijing Municipal Commission of Education(KM202210017001 and 22019821001)the Natural Science Foundation of Henan Province(222300420253).
文摘This paper discusses the design of event-triggered output-feedback controller for a class of nonlinear time-delay systems with multiple uncertainties. In sharp contrast to previous works, the considered systems possess two important characteristics: (i) The uncertain nonlinear terms meet the linearly unmeasurable-states dependent growth with the growth rate being an unknown function of the input and output. (ii) There exist input matching uncertainty and unknown measurement sensitivity. By introducing a single dynamic gain and employing a cleverly devised event-triggering mechanism (ETM), we design a new gain-based event-triggered output-feedback controller, which globally regulates all states of the considered systems and maintains global boundedness of the closed-loop system. Furthermore, the estimation of input matching uncertainty achieves convergence towards its actual value, and Zeno behavior does not happen. Two simulation examples including a practical one show that the proposed approach is effective.
