Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and ev...Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.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
In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis...In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.展开更多
Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investig...Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.展开更多
This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we id...This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.展开更多
The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilit...The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilities of ATP systems.However,in practical applications,ATP systems face various design constraints and functional limitations,making it infeasible to indefinitely improve hardware performance to meet tracking requirements.As a result,tracking algorithms are required to execute increasingly complex tasks.This study introduces a multi-rate feedforward predictive controller to address issues such as low image feedback frequency and significant delays in ATP systems,which lead to tracking jitter,poor tracking performance,low precision,and target loss.At the same time,the pro-posed approach aims to improve the tracking capabilities of ATP systems for high-speed and highly maneuverable targets under conditions of low sampling feedback rates and high feedback delays.The method suggested is also characterized by its low order,fast response,and robustness to model parameter variations.In this study,an actual ATP system is built for target tracking test,and the proposed algorithm is fully validated in terms of simulation and actual system application verification.Results from both simulations and experiments demonstrate that the method effectively compensates for delays and low sampling rates.For targets with relative angular velocities ranging from 0 to 90°/s and angular accelerations between 0 and 470°/s^(2),the system improved tracking accuracy by 70.0%-89.9%at a sampling frequency of 50 Hz and a delay of 30 m s.Moreover,the compensation algorithm demonstrated consistent performance across actuators with varying characteristics,further confirming its robustness to model insensitivity.In summary,the proposed algorithm considerably enhances the tracking accuracy and capability of ATP systems for high-speed and highly maneuverable targets,reducing the probability of target loss from high speed.This approach offers a practical solution for future multi-target tracking across diverse operational scenarios.展开更多
This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired traje...This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.展开更多
Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate trackin...Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.展开更多
A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevaryin...A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.展开更多
This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a larg...This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.展开更多
This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind di...This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.展开更多
Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1250 TTE vid...Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAX GV).The videos were divided into development set(245 A4C,155 PLAX,225 PSAX GV),semi-automated training set(98 A4C,62 PLAX,90 PSAX GV)and test set(147 A4C,93 PLAX,135 PSAX GV)at the ratio of 5∶2∶3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33%,97.26%,97.26%and 97.26%to 99.73%,99.65%,99.77%and 99.71%,respectively,while the overall accuracy for assessing A4C,PLAX and PSAX GV TTE as standard views in test set improved from 89.12%,83.87%and 90.37%to 93.20%,90.32%and 93.33%,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.展开更多
In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and comp...In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.展开更多
In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LST...In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.展开更多
This paper mainly focuses on stability analysis of the nonlinear active disturbance rejection control(ADRC)-based control system and its applicability to real world engineering problems.Firstly,the nonlinear ADRC(NLAD...This paper mainly focuses on stability analysis of the nonlinear active disturbance rejection control(ADRC)-based control system and its applicability to real world engineering problems.Firstly,the nonlinear ADRC(NLADRC)-based control system is transformed into a multi-input multi-output(MIMO)Lurie-like system,then sufficient condition for absolute stability based on linear matrix inequality(LMI)is proposed.Since the absolute stability is a kind of global stability,Lyapunov stability is further considered.The local asymptotical stability can be deter-mined by whether a matrix is Hurwitz or not.Using the inverted pendulum as an example,the proposed methods are verified by simulation and experiment,which show the valuable guidance for engineers to design and analyze the NL ADRC-based control system.展开更多
This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only b...This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.展开更多
This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hype...This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.展开更多
This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters wh...This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.展开更多
[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infra...[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.展开更多
This paper presents a method of multicopter intercep-tion control based on visual servo and virtual tube in a cluttered environment.The proposed hybrid heuristic function improves the efficiency of the A*algorithm.The...This paper presents a method of multicopter intercep-tion control based on visual servo and virtual tube in a cluttered environment.The proposed hybrid heuristic function improves the efficiency of the A*algorithm.The revised objective function makes the virtual tube generating curve not only smooth but also close to the path points generated by the A*algorithm.In six dif-ferent simulation scenarios,the efficiency of the modified A*algorithm is 6.2%higher than that of the traditional A*algorithm.The efficiency of path planning and virtual tube planning is veri-fied by simulations.The effectiveness of interception control is verified by a software-in-loop(SIL)simulation.展开更多
基金Supported by the National Natural Science Foundation of China (11161027)。
文摘Projective synchronization problems of a drive system and a particular response network were investigated,where the drive system is an arbitrary system with n+1 dimensions;it may be a linear or nonlinear system,and even a chaotic or hyperchaotic system,the response network is complex system coupled by N nodes,and every node is showed by the approximately linear part of the drive system.Only controlling any one node of the response network by designed controller can achieve the projective synchronization.Some numerical examples were employed to verify the effectiveness and correctness of the designed controller.
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.
文摘In order to enhance the control performance of piezo-positioning system,the influence of hysteresis characteristics and its compensation method are studied.Hammerstein model is used to represent the dynamic hysteresis nonlinear characteristics of piezo-positioning actuator.The static nonlinear part and dynamic linear part of the Hammerstein model are represented by models obtained through the Prandtl-Ishlinskii(PI)model and Hankel matrix system identification method,respectively.This model demonstrates good generalization capability for typical input frequencies below 200 Hz.A sliding mode inverse compensation tracking control strategy based on P-I inverse model and integral augmentation is proposed.Experimental results show that compared with PID inverse compensation control and sliding mode control without inverse compensation,the sliding mode inverse compensation control has a more ideal step response and no overshoot,moreover,the settling time is only 6.2 ms.In the frequency domain,the system closed-loop tracking bandwidth reaches 119.9 Hz,and the disturbance rejection bandwidth reaches 86.2 Hz.The proposed control strategy can effectively compensate the hysteresis nonlinearity,and improve the tracking accuracy and antidisturbance capability of piezo-positioning system.
文摘Recently,unmanned aerial vehicle(UAV)-aided free-space optical(FSO)communication has attracted widespread attentions.However,most of the existing research focuses on communication performance only.The authors investigate the integrated scheduling of communication,sensing,and control for UAV-aided FSO communication systems.Initially,a sensing-control model is established via the control theory.Moreover,an FSO communication channel model is established by considering the effects of atmospheric loss,atmospheric turbulence,geometrical loss,and angle-of-arrival fluctuation.Then,the relationship between the motion control of the UAV and radial displacement is obtained to link the control aspect and communication aspect.Assuming that the base station has instantaneous channel state information(CSI)or statistical CSI,the thresholds of the sensing-control pattern activation are designed,respectively.Finally,an integrated scheduling scheme for performing communication,sensing,and control is proposed.Numerical results indicate that,compared with conventional time-triggered scheme,the proposed integrated scheduling scheme obtains comparable communication and control performance,but reduces the sensing consumed power by 52.46%.
文摘This survey presents a comprehensive review of vari-ous methods and algorithms related to passing-through control of multi-robot systems in cluttered environments.Numerous studies have investigated this area,and we identify several avenues for enhancing existing methods.This survey describes some models of robots and commonly considered control objec-tives,followed by an in-depth analysis of four types of algo-rithms that can be employed for passing-through control:leader-follower formation control,multi-robot trajectory planning,con-trol-based methods,and virtual tube planning and control.Fur-thermore,we conduct a comparative analysis of these tech-niques and provide some subjective and general evaluations.
基金supported by the National Natural Science Foun-dation of China(Grant No.52275099).
文摘The acquisition,tracking,and pointing(ATP)system is widely used in target tracking,counter-UAV operations,and other related fields.As UAV technology develops,there is a growing demand to enhance the tracking capabilities of ATP systems.However,in practical applications,ATP systems face various design constraints and functional limitations,making it infeasible to indefinitely improve hardware performance to meet tracking requirements.As a result,tracking algorithms are required to execute increasingly complex tasks.This study introduces a multi-rate feedforward predictive controller to address issues such as low image feedback frequency and significant delays in ATP systems,which lead to tracking jitter,poor tracking performance,low precision,and target loss.At the same time,the pro-posed approach aims to improve the tracking capabilities of ATP systems for high-speed and highly maneuverable targets under conditions of low sampling feedback rates and high feedback delays.The method suggested is also characterized by its low order,fast response,and robustness to model parameter variations.In this study,an actual ATP system is built for target tracking test,and the proposed algorithm is fully validated in terms of simulation and actual system application verification.Results from both simulations and experiments demonstrate that the method effectively compensates for delays and low sampling rates.For targets with relative angular velocities ranging from 0 to 90°/s and angular accelerations between 0 and 470°/s^(2),the system improved tracking accuracy by 70.0%-89.9%at a sampling frequency of 50 Hz and a delay of 30 m s.Moreover,the compensation algorithm demonstrated consistent performance across actuators with varying characteristics,further confirming its robustness to model insensitivity.In summary,the proposed algorithm considerably enhances the tracking accuracy and capability of ATP systems for high-speed and highly maneuverable targets,reducing the probability of target loss from high speed.This approach offers a practical solution for future multi-target tracking across diverse operational scenarios.
文摘This paper addresses the time-varying formation-containment(FC) problem for nonholonomic multi-agent systems with a desired trajectory constraint, where only the leaders can acquire information about the desired trajectory. Input the fixed time-varying formation template to the leader and start executing, this process also needs to track the desired trajectory, and the follower needs to converge to the convex hull that the leader crosses. Firstly, the dynamic models of nonholonomic systems are linearized to second-order dynamics. Then, based on the desired trajectory and formation template, the FC control protocols are proposed. Sufficient conditions to achieve FC are introduced and an algorithm is proposed to resolve the control parameters by solving an algebraic Riccati equation. The system is demonstrated to achieve FC, with the average position and velocity of the leaders converging asymptotically to the desired trajectory. Finally, the theoretical achievements are verified in simulations by a multi-agent system composed of virtual human individuals.
基金the National Natural Science Foundation of China(No.52275062)and(No.52075262).
文摘Since backlash nonlinearity is inevitably existing in actuators for bidirectional stabilization system of allelectric tank,it behaves more drastically in high maneuvering environments.In this work,the accurate tracking control for bidirectional stabilization system of moving all-electric tank with actuator backlash and unmodeled disturbance is solved.By utilizing the smooth adaptive backlash inverse model,a nonlinear robust adaptive feedback control scheme is presented.The unknown parameters and unmodelled disturbance are addressed separately through the derived parametric adaptive function and the continuous nonlinear robust term.Because the unknown backlash parameters are updated via adaptive function and the backlash effect can be suppressed successfully by inverse operation,which ensures the system stability.Meanwhile,the system disturbance in the high maneuverable environment can be estimated with the constructed adaptive law online improving the engineering practicality.Finally,Lyapunov-based analysis proves that the developed controller can ensure the tracking error asymptotically converges to zero even with unmodeled disturbance and unknown actuator backlash.Contrast co-simulations and experiments illustrate the advantages of the proposed approach.
基金supported in part by the Nation Natural Science Foundation of China under Grant No.52175099China Postdoctoral Science Foundation under Grant No.2020M671494Jiangsu Planned Projects for Postdoctoral Research Funds under Grant No.2020Z179。
文摘A tracking stability control problem for the vertical electric stabilization system of moving tank based on adaptive robust servo control is addressed.This paper mainly focuses on two types of possibly fast timevarying but bounded uncertainty within the vertical electric stabilization system:model parameter uncertainty and uncertain nonlinearity.First,the vertical electric stabilization system is constructed as an uncertain nonlinear dynamic system that can reflect the practical mechanics transfer process of the system.Second,the dynamical equation in the form of state space is established by designing the angular tracking error.Third,the comprehensive parameter of system uncertainty is designed to estimate the most conservative effects of uncertainty.Finally,an adaptive robust servo control which can effectively handle the combined effects of complex nonlinearity and uncertainty is proposed.The feasibility of the proposed control strategy under the practical physical condition is validated through the tests on the experimental platform.This paper pioneers the introduction of the internal nonlinearity and uncertainty of the vertical electric stabilization system into the settlement of the tracking stability control problem,and validates the advanced servo control strategy through experiment for the first time.
基金supported in part by the National Key R&D Program of China under Grant 2021YFB2011300the National Natural Science Foundation of China under Grant 52075262。
文摘This paper mainly focuses on the development of a learning-based controller for a class of uncertain mechanical systems modeled by the Euler-Lagrange formulation.The considered system can depict the behavior of a large class of engineering systems,such as vehicular systems,robot manipulators and satellites.All these systems are often characterized by highly nonlinear characteristics,heavy modeling uncertainties and unknown perturbations,therefore,accurate-model-based nonlinear control approaches become unavailable.Motivated by the challenge,a reinforcement learning(RL)adaptive control methodology based on the actor-critic framework is investigated to compensate the uncertain mechanical dynamics.The approximation inaccuracies caused by RL and the exogenous unknown disturbances are circumvented via a continuous robust integral of the sign of the error(RISE)control approach.Different from a classical RISE control law,a tanh(·)function is utilized instead of a sign(·)function to acquire a more smooth control signal.The developed controller requires very little prior knowledge of the dynamic model,is robust to unknown dynamics and exogenous disturbances,and can achieve asymptotic output tracking.Eventually,co-simulations through ADAMS and MATLAB/Simulink on a three degrees-of-freedom(3-DOF)manipulator and experiments on a real-time electromechanical servo system are performed to verify the performance of the proposed approach.
基金supported by National Natural Science Foundation of China (Grant Nos.52072309 and 62303379)Beijing Institute of Spacecraft System Engineering Research Project (Grant NO.JSZL2020203B004)+1 种基金Natural Science Foundation of Shaanxi Province,Chinese (Grant NOs.2023-JC-QN-0003 and 2023-JC-QN-0665)Industry-University-Research Innovation Fund of Ministry of Education for Chinese Universities (Grant NO.2022IT189)。
文摘This paper investigates the attitude tracking control problem for the cruise mode of a dual-system convertible unmanned aerial vehicle(UAV)in the presence of parameter uncertainties,unmodeled uncertainties and wind disturbances.First,a fixed-time disturbance observer(FXDO)based on the bi-limit homogeneity theory is designed to estimate the lumped disturbance of the convertible UAV model.Then,a fixed-time integral sliding mode control(FXISMC)is combined with the FXDO to achieve strong robustness and chattering reduction.Bi-limit homogeneity theory and Lyapunov theory are applied to provide detailed proof of the fixed-time stability.Finally,numerical simulation experimental results verify the robustness of the proposed algorithm to model parameter uncertainties and wind disturbances.In addition,the proposed algorithm is deployed in a open-source UAV autopilot and its effectiveness is further demonstrated by hardware-in-the-loop experimental results.
文摘Objective To explore the value of deep learning(DL)models semi-automatic training system for automatic optimization of clinical image quality control of transthoracic echocardiography(TTE).Methods Totally 1250 TTE videos from 402 patients were retrospectively collected,including 490 apical four chamber(A4C),310 parasternal long axis view of left ventricle(PLAX)and 450 parasternal short axis view of great vessel(PSAX GV).The videos were divided into development set(245 A4C,155 PLAX,225 PSAX GV),semi-automated training set(98 A4C,62 PLAX,90 PSAX GV)and test set(147 A4C,93 PLAX,135 PSAX GV)at the ratio of 5∶2∶3.Based on development set and semi-automatic training set,DL model of quality control was semi-automatically iteratively optimized,and a semi-automatic training system was constructed,then the efficacy of DL models for recognizing TTE views and assessing imaging quality of TTE were verified in test set.Results After optimization,the overall accuracy,precision,recall,and F1 score of DL models for recognizing TTE views in test set improved from 97.33%,97.26%,97.26%and 97.26%to 99.73%,99.65%,99.77%and 99.71%,respectively,while the overall accuracy for assessing A4C,PLAX and PSAX GV TTE as standard views in test set improved from 89.12%,83.87%and 90.37%to 93.20%,90.32%and 93.33%,respectively.Conclusion The developed DL models semi-automatic training system could improve the efficiency of clinical imaging quality control of TTE and increase iteration speed.
基金supported by the National Natural Science Foundation of China(62273176)the Aeronautical Science Foundation of China(20200007018001)the China Scholarship Council(202306830096).
文摘In the aircraft control system,sensor networks are used to sample the attitude and environmental data.As a result of the external and internal factors(e.g.,environmental and task complexity,inaccurate sensing and complex structure),the aircraft control system contains several uncertainties,such as imprecision,incompleteness,redundancy and randomness.The information fusion technology is usually used to solve the uncertainty issue,thus improving the sampled data reliability,which can further effectively increase the performance of the fault diagnosis decision-making in the aircraft control system.In this work,we first analyze the uncertainties in the aircraft control system,and also compare different uncertainty quantitative methods.Since the information fusion can eliminate the effects of the uncertainties,it is widely used in the fault diagnosis.Thus,this paper summarizes the recent work in this aera.Furthermore,we analyze the application of information fusion methods in the fault diagnosis of the aircraft control system.Finally,this work identifies existing problems in the use of information fusion for diagnosis and outlines future trends.
文摘In this paper, a filtering method is presented to estimate time-varying parameters of a missile dual control system with tail fins and reaction jets as control variables. In this method, the long-short-term memory(LSTM) neural network is nested into the extended Kalman filter(EKF) to modify the Kalman gain such that the filtering performance is improved in the presence of large model uncertainties. To avoid the unstable network output caused by the abrupt changes of system states,an adaptive correction factor is introduced to correct the network output online. In the process of training the network, a multi-gradient descent learning mode is proposed to better fit the internal state of the system, and a rolling training is used to implement an online prediction logic. Based on the Lyapunov second method, we discuss the stability of the system, the result shows that when the training error of neural network is sufficiently small, the system is asymptotically stable. With its application to the estimation of time-varying parameters of a missile dual control system, the LSTM-EKF shows better filtering performance than the EKF and adaptive EKF(AEKF) when there exist large uncertainties in the system model.
基金supported by the National Natural Science Foundation of China(61836001).
文摘This paper mainly focuses on stability analysis of the nonlinear active disturbance rejection control(ADRC)-based control system and its applicability to real world engineering problems.Firstly,the nonlinear ADRC(NLADRC)-based control system is transformed into a multi-input multi-output(MIMO)Lurie-like system,then sufficient condition for absolute stability based on linear matrix inequality(LMI)is proposed.Since the absolute stability is a kind of global stability,Lyapunov stability is further considered.The local asymptotical stability can be deter-mined by whether a matrix is Hurwitz or not.Using the inverted pendulum as an example,the proposed methods are verified by simulation and experiment,which show the valuable guidance for engineers to design and analyze the NL ADRC-based control system.
文摘This paper presents an investigation on the target-guided coordinated control(TACC)of unmanned surface vehicles(USVs).In the scenario of tracking non-cooperative targets,the status information of the target can only be obtained by some USVs.In order to achieve semi-encirclement tracking of noncooperative targets under maritime security conditions,a fixed-time tracking control method based on dynamic surface control(DSC)is proposed in this paper.Firstly,a novel TACC architecture with decoupled kinematic control law and decoupled kinetic control law was designed to reduce the complexity of control system design.Secondly,the proposed DSC-based target-guided kinematic control law including tracking points pre-allocation strategy and sigmoid artificial potential functions(SigAPFs)can avoid collisions during tracking process and optimize kinematic control output.Finally,a fixed-time TACC system was proposed to achieve fast convergence of kinematic and kinetics errors.The effectiveness of the proposed TACC approach in improving target tracking safety and reducing control output chattering was verified by simulation comparison results.
基金supported by the National Natural Science Foundation of China(12072090).
文摘This work proposes the application of an iterative learning model predictive control(ILMPC)approach based on an adaptive fault observer(FOBILMPC)for fault-tolerant control and trajectory tracking in air-breathing hypersonic vehicles.In order to increase the control amount,this online control legislation makes use of model predictive control(MPC)that is based on the concept of iterative learning control(ILC).By using offline data to decrease the linearized model’s faults,the strategy may effectively increase the robustness of the control system and guarantee that disturbances can be suppressed.An adaptive fault observer is created based on the suggested ILMPC approach in order to enhance overall fault tolerance by estimating and compensating for actuator disturbance and fault degree.During the derivation process,a linearized model of longitudinal dynamics is established.The suggested ILMPC approach is likely to be used in the design of hypersonic vehicle control systems since numerical simulations have demonstrated that it can decrease tracking error and speed up convergence when compared to the offline controller.
文摘This paper proposes a distributed event-triggered control(ETC)framework to address cooperative target fencing challenges in UAV swarm.The proposed architecture eliminates the reliance on preset formation parameters while achieving multi-objective cooperative control for target fencing,network connectivity preservation,collision avoidance,and communication efficiency optimization.Firstly,a differential state observer is constructed to obtain the target's unmeasurable states.Secondly,leveraging swarm selforganization principles,a geometric-constraint-free distributed fencing controller is designed by integrating potential field methods with consensus theory.The controller dynamically adjusts inter-UAV distances via single potential function,enabling coordinated optimization of persistent network connectivity and collision-free motion during target fencing.Thirdly,a dual-threshold ETC mechanism based on velocity consensus deviation and fencing error is proposed,which can be triggered based on task features to dynamically adjust the communication frequency,significantly reduce the communication burden and exclude Zeno behavior.Theoretical analysis demonstrates the stability of closed-loop systems.Multi-scenario simulations show that the proposed method can achieve robust fencing under target maneuverability,partial UAV failures,and communication disturbances.
文摘[Objective]Under the combined impact of climate change and urbanization,urban rainstorm flood disasters occur frequently,seriously restricting urban safety and sustainable development.Relying on traditional grey infrastructure such as pipe networks for urban stormwater management is not enough to deal with urban rainstorm flood disasters under extreme rainfall events.The integration of green,grey and blue systems(GGB-integrated system)is gradually gaining recognition in the field of global flood prevention.It is necessary to further clarify the connotation,technical and engineering implementation strategies of the GGB-integrated system,to provide support for the resilient city construction.[Methods]Through literature retrieval and analysis,the relevant research and progress related to the layout optimization and joint scheduling optimization of the GGBintegrated system were systematically reviewed.In response to existing limitations and future engineering application requirements,key supporting technologies including the utilization of overground emergency storage spaces,safety protection of underground important infrastructure and multi-departmental collaboration,were proposed.A layout optimization framework and a joint scheduling framework for the GGB-integrated system were also developed.[Results]Current research on layout optimization predominantly focuses on the integration of green system and grey system,with relatively fewer studies incorporating blue system infrastructure into the optimization process.Moreover,these studies tend to be on a smaller scale with simpler scenarios,which do not fully capture the complexity of real-world systems.Additionally,optimization objective tend to prioritize environmental and economic goals,while social and ecological factors are less frequently considered.Current research on joint scheduling optimization is often limited to small-scale plots,with insufficient attention paid to the entire system.There is a deficiency in method for real-time,automated determination of optimal control strategies for combinations of multiple system facilities based on actual rainfall-runoff processes.Additionally,the application of emergency facilities during extreme conditions is not sufficiently addressed.Furthermore,both layout optimization and joint scheduling optimization lack consideration of the mute feed effect of flood and waterlogging in urban,watershed and regional scales.[Conclusion]Future research needs to improve the theoretical framework for layout optimization and joint scheduling optimization of GGB-integrated system.Through the comprehensive application of the Internet of things,artificial intelligence,coupling model development,multi-scale analysis,multi-scenario simulation,and the establishment of multi-departmental collaboration mechanisms,it can enhance the flood resilience of urban areas in response to rainfall events of varying intensities,particularly extreme rainfall events.
基金supported by the National Natural Science Foundation of China(62303350).
文摘This paper presents a method of multicopter intercep-tion control based on visual servo and virtual tube in a cluttered environment.The proposed hybrid heuristic function improves the efficiency of the A*algorithm.The revised objective function makes the virtual tube generating curve not only smooth but also close to the path points generated by the A*algorithm.In six dif-ferent simulation scenarios,the efficiency of the modified A*algorithm is 6.2%higher than that of the traditional A*algorithm.The efficiency of path planning and virtual tube planning is veri-fied by simulations.The effectiveness of interception control is verified by a software-in-loop(SIL)simulation.
