Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harve...Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.展开更多
A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source di...A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.展开更多
In the industrial roller kiln,the time-delay characteristic in heat transfer causes the temperature field to be affected by both the current and historical temperature states.It presents a poor control performance and...In the industrial roller kiln,the time-delay characteristic in heat transfer causes the temperature field to be affected by both the current and historical temperature states.It presents a poor control performance and brings a significant challenge to the process precise control.Considering high complexity of precise modeling,a data-driven time-delay optimal control method for temperature field of roller kiln is proposed based on a large amount of process data.First,the control challenges and problem description brought by time-delay are demonstrated,where the cost function for the time-delay partial differential equation system is constructed.To obtain the optimal control law,the policy iteration in adaptive dynamic programming is adopted to design the time-delay temperature field controller,and neural network is used for the critic network in policy iteration to approximate the optimal time-delay cost function.The closed-loop system stability is proved by designing the Lyapunov function which contains the time-delay information.Finally,through establishing the time-delay temperature field model for roller kiln,the effectiveness and convergence of the proposed method is verified and proved.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
Focusing on the rehabilitation training of hemiplegia patients,this paper proposes a gait-planning strategy based on a central pattern generator and an adaptive time-delay control scheme that utilizes recursive termin...Focusing on the rehabilitation training of hemiplegia patients,this paper proposes a gait-planning strategy based on a central pattern generator and an adaptive time-delay control scheme that utilizes recursive terminal sliding mode for lower limb rehabilitation exoskeleton robots.The central pattern generator network plans a reference gait trajectory for the affected leg,synchronized with the movement of the healthy leg.The proposed adaptive time-delay control scheme possesses a model-independent property due to the mechanism of time-delay estimation,with adaptive control gains that enhance the resilience against system perturbations and a recursive terminal sliding mode control component to achieve a fast convergence rate.According to the Lyapunov stability criterion,it is proved that the gait trajectory-tracking error is uniformly ultimately bounded.Experiments are conducted on a lower limb exoskeleton experimental platform,and the experimental results demonstrate the effectiveness and superiority of the proposed strategies.展开更多
This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mi...This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.展开更多
Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mos...Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mosquitoes through vaccination.Using Culex pipiens(C.pipiens)as a model,we demonstrated that polyclonal antibodies against C.pipiens abdominal protein extracts significantly impaired oviposition and increased mosquito mortality,primarily through the classical complement activation pathways.However,repeated exposure led to resistance,indicating potential adaptation.Proteomic analysis identified metabolic proteins as key targets,with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses highlighting their roles in carboxylic acid metabolism,tyrosine degradation,and the proteasome pathways.Notably,cross-species reactivity was revealed by Western blotting,showing strong binding of Culex-specific antibodies to Anopheles and Aedes abdominal proteins.This study provides mechanistic insights into antibody-based mosquito suppression,highlighting its potential as an innovative vector control strategy while underscoring the need for further research on resistance management and ecological impacts.展开更多
This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow con...This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.展开更多
Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybr...Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.展开更多
This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relativ...This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.展开更多
In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that globa...In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.展开更多
This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder ma...This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder may result in the performance degradation of the observer.In this paper,an improved predictor-based observer is designed to compensate for the influence of the unmeasurable states,sampling errors and output delay.In addition,a sampled-data output-feedback controller is also constructed using the gain scaling technique.By the Lyapunov-Krasovskii functional method,the global exponential stability of the resulting closed-loop system can be guaranteed under some sufficient conditions.The simulation results are provided to demonstrate the main results.展开更多
The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantl...The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantly affected by the hysteresis phenomenon in the wave compensation system.To address this issue,a ship heave motion prediction is proposed in this paper on the basis of the Gauss-DeepAR(AR stands for autoregressive recurrent)model and the Hilbert−Huang time-delay compensation control strategy.Initially,the zero upward traveling wave period of the level 4−6 sea state ship heave motion is analyzed,which serves as the input sliding window for the Gauss-DeepAR prediction model,and probability predictions at different wave direction angles are conducted.Next,considering the hysteresis characteristics of the ship heave motion compensation platform,the Hilbert−Huang transform is employed to analyze and calculate the hysteresis delay of the compensation platform.After the optimal control action value is subsequently calculated,simulations and hardware platform tests are conducted.The simulation results demonstrated that the Gauss-DeepAR model outperforms autoregressive integrated moving average model(ARIMA),support vector machine(SVM),and longshort-term memory(LSTM)in predicting non-independent identically distributed datasets at a 90°wave direction angle in the level 4−6 sea states.Furthermore,the model has good predictive performance and generalizability for non-independent and non-uniformly distributed datasets at a 180°wave direction angle.The hardware platform compensation test results revealed that the Hilbert–Huang method has an outstanding effect on determining the hysteretic delay and selecting the optimal control action value,and the compensation efficiency was higher than 90%in the level 4−6 sea states.展开更多
As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance reject...As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance rejection in the steady state for periodic signals with a fixed period.This characteristic is important not only for conventional technologies and conventional industries but also for advanced technologies and emerging industries.This paper first explains the concept of repetitive control from its original idea.Next,it describes the structure of a repetitive controller as an internal model and shows the respective points of continuous-and discrete-time repetitive control.It presents a categorized list of practical applications of repetitive control.Moreover,two concrete applications,namely the control of a robotic manipulator and a rotating system,demonstrate the validity of the method with experimental results.Several current studies in this field are also reviewed,and some challenges and future studies for repetitive control are provided.展开更多
This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper cons...This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.展开更多
Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion...Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.展开更多
To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction...To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.展开更多
Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space expl...Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space exploration.The kinematics model merely delineates the geometric relationship of the controlled objective,disregarding force feedback.This study investigates model predictive trajectory tracking control utilising the robot dynamic model(DRMPC)in the context of unpredictable interactions.The predictive tracking controller for the wheel-legged robot is introduced in the context of position tracking.A dynamic approximator is employed to address the uncertain interactions in the tracking process.Ultimately,cosimulation and empirical tests are conducted to demonstrate the efficacy of the devised control methodology,which achieves high precision and dependable robustness.This work can elucidate the technical and practical oversight of autonomous movement in complicated environments and enhance the manoeuverability and flexibility.展开更多
This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-tak...This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.展开更多
This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Consi...This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.展开更多
基金Project supported by the National Natural Science Foundation of China(Grant No.12002089)the Science and Technology Projects in Guangzhou(Grant No.2023A04J1323)UKRI Horizon Europe Guarantee(Marie SklodowskaCurie Fellowship)(Grant No.EP/Y016130/1)。
文摘Energy-regenerative suspension combined with piezoelectric and electromagnetic transduction has evolved into a core technological pathway in advancing automotive design paradigms.With the aim of improving energy harvesting performance,time-delayed feedback control is widely used in an energy-regenerative suspension system under different external disturbances in this paper.Meanwhile,limited research has addressed the stochastic dynamics of time-delayed nonlinear energy-regenerative suspension systems.Different from previous studies,this work studies the stochastic response and P-bifurcation of the nonlinear energy-regenerative suspension system with time-delayed feedback control.Firstly,an approximately equivalent dimension reduction system is established by the variable transformation method,and then the stationary probability density function of amplitude is obtained by the stochastic averaging method.Secondly,the precision of the method used in this work is verified by comparing the numerical solutions with the analytical results.Finally,based on the stationary probability density function,the influence of system parameters on stochastic P-bifurcation and the mean output power is discussed.
基金co-supported by the National Key R&D Program of China(No.2023YFB4704400)the Zhejiang Provincial Natural Science Foundation of China(No.LQ24F030012)the National Natural Science Foundation of China General Project(No.62373033)。
文摘A composite anti-disturbance predictive control strategy employing a Multi-dimensional Taylor Network(MTN)is presented for unmanned systems subject to time-delay and multi-source disturbances.First,the multi-source disturbances are addressed according to their specific characteristics as follows:(A)an MTN data-driven model,which is used for uncertainty description,is designed accompanied with the mechanism model to represent the unmanned systems;(B)an adaptive MTN filter is used to remove the influence of the internal disturbance;(C)an MTN disturbance observer is constructed to estimate and compensate for the influence of the external disturbance;(D)the Extended Kalman Filter(EKF)algorithm is utilized as the learning mechanism for MTNs.Second,to address the time-delay effect,a recursiveτstep-ahead MTN predictive model is designed utilizing recursive technology,aiming to mitigate the impact of time-delay,and the EKF algorithm is employed as its learning mechanism.Then,the MTN predictive control law is designed based on the quadratic performance index.By implementing the proposed composite controller to unmanned systems,simultaneous feedforward compensation and feedback suppression to the multi-source disturbances are conducted.Finally,the convergence of the MTN and the stability of the closed-loop system are established utilizing the Lyapunov theorem.Two exemplary applications of unmanned systems involving unmanned vehicle and rigid spacecraft are presented to validate the effectiveness of the proposed approach.
基金supported in part by the Key Program of National Natural Science Foundation of China(62033014)the Application Projects of Integrated Standardization and New Paradigm for Intelligent Manufacturing from the Ministry of Industry and Information Technology of China in 2016the Fundamental Research Funds for the Central Universities of Central South University(2021zzts0700).
文摘In the industrial roller kiln,the time-delay characteristic in heat transfer causes the temperature field to be affected by both the current and historical temperature states.It presents a poor control performance and brings a significant challenge to the process precise control.Considering high complexity of precise modeling,a data-driven time-delay optimal control method for temperature field of roller kiln is proposed based on a large amount of process data.First,the control challenges and problem description brought by time-delay are demonstrated,where the cost function for the time-delay partial differential equation system is constructed.To obtain the optimal control law,the policy iteration in adaptive dynamic programming is adopted to design the time-delay temperature field controller,and neural network is used for the critic network in policy iteration to approximate the optimal time-delay cost function.The closed-loop system stability is proved by designing the Lyapunov function which contains the time-delay information.Finally,through establishing the time-delay temperature field model for roller kiln,the effectiveness and convergence of the proposed method is verified and proved.
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.
基金supported by the National Natural Science Foundation of China(62473337,62003305)the Key Research and Development Program of Zhejiang Province(2024C03040,2022C03029)the funding of Leading Innovative and Entrepreneur Team Introduction Program of Zhejiang Province(2023R01006).
文摘Focusing on the rehabilitation training of hemiplegia patients,this paper proposes a gait-planning strategy based on a central pattern generator and an adaptive time-delay control scheme that utilizes recursive terminal sliding mode for lower limb rehabilitation exoskeleton robots.The central pattern generator network plans a reference gait trajectory for the affected leg,synchronized with the movement of the healthy leg.The proposed adaptive time-delay control scheme possesses a model-independent property due to the mechanism of time-delay estimation,with adaptive control gains that enhance the resilience against system perturbations and a recursive terminal sliding mode control component to achieve a fast convergence rate.According to the Lyapunov stability criterion,it is proved that the gait trajectory-tracking error is uniformly ultimately bounded.Experiments are conducted on a lower limb exoskeleton experimental platform,and the experimental results demonstrate the effectiveness and superiority of the proposed strategies.
基金supported by the National Natural Science Foundation of China(No.12372045)the National Key Research and the Development Program of China(Nos.2023YFC2205900,2023YFC2205901)。
文摘This paper solves the problem of model-free dual-arm space robot maneuvering after non-cooperative target capture under high control quality requirements.The explicit system model is unavailable,and the maneuvering mission is disturbed by the measurement noise and the target adversarial behavior.To address these problems,a model-free Combined Adaptive-length Datadriven Predictive Controller(CADPC)is proposed.It consists of a separated subsystem identification method and a combined predictive control strategy.The subsystem identification method is composed of an adaptive data length,thereby reducing sensitivity to undetermined measurement noises and disturbances.Based on the subsystem identification,the combined predictive controller is established,reducing calculating resource.The stability of the CADPC is rigorously proven using the Input-to-State Stable(ISS)theorem and the small-gain theorem.Simulations demonstrate that CADPC effectively handles the model-free space robot post operation in the presence of significant disturbances,state measurement noise,and control input errors.It achieves improved steady-state accuracy,reduced steady-state control consumption,and minimized control input chattering.
基金supported by the National Natural Science Foundation of China(Grant No.82472312).
文摘Mosquito-borne diseases pose a significant global health threat,necessitating the development of innovative vector control strategies.In this study,we investigated the potential of harnessing host immunity against mosquitoes through vaccination.Using Culex pipiens(C.pipiens)as a model,we demonstrated that polyclonal antibodies against C.pipiens abdominal protein extracts significantly impaired oviposition and increased mosquito mortality,primarily through the classical complement activation pathways.However,repeated exposure led to resistance,indicating potential adaptation.Proteomic analysis identified metabolic proteins as key targets,with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analyses highlighting their roles in carboxylic acid metabolism,tyrosine degradation,and the proteasome pathways.Notably,cross-species reactivity was revealed by Western blotting,showing strong binding of Culex-specific antibodies to Anopheles and Aedes abdominal proteins.This study provides mechanistic insights into antibody-based mosquito suppression,highlighting its potential as an innovative vector control strategy while underscoring the need for further research on resistance management and ecological impacts.
基金the Scientific Research Projects Unit of Erciyes University under contract no:FDS-2022-11532 and FOA-2025-14773.
文摘This paper examines a model that combines vortex generators and leading-edge tubercles for controlling the laminar separation bubble(LSB)over an airfoil at low Reynolds numbers(Re).This new concept of passive flow control technique utilizing a tubercle and vortex generator(VG)close to the leading edge was analyzed numerically for a NACA0015 airfoil.In this study,the Shear Stress Transport(SST)turbulence model was employed in the numerical modelling.Numerical modelling was completed using the ANSYS-Fluent 18.2 solver.Analyses were conducted to investigate the flow pattern and understand the underlying LSB control phenomena that enabled the new passive flow control method to provide this significant performance benefit.The findings indicated that the new concept of passive flow control technique suppressed the formation of an LSB at the suction surface of the NACA0015 airfoil,resulting in a higher lift coefficient and improved aerodynamic performance.Improvements in LSB dynamics and aerodynamic performance through the passive flow control method lead to increased energy output and enhanced stability.
文摘Steady speed control of agricultural machinery can improve operating quality and efficiency.To address the impact of farmland slope variations on the speed stability of unmanned operation agricultural machinery,a hybrid control method was proposed.This method included a hybrid controller composed of a slope-based controller and a proportional-integral-derivative(PID)controller.The speed of agricultural machinery was influenced by longitudinal forces,which were divided into two parts:one part was slope-related forces and conventional resistance,and the other was hard-to-estimate forces,such as sliding friction.For the first part,a slope-based controller was designed;for the second part,a PID controller was implemented.By combining these two controllers,the system can dynamically adjust the throttle opening and the brake master cylinder pressure,ensuring steady speed travel on sloping farmland.Simulation tests at a target speed of 7 km/h demonstrated that the proposed controller maintained a stable speed,achieving a root mean square error of 0.13 km/h and a mean absolute percentage error of 1.6%.Field tests on a practical experimental platform validated the method’s effectiveness,with results showing consistent control performance across varying slope conditions.The proposed controller demonstrated superior control performance.Experimental data verified that this method can achieve precise control of the agricultural machinery’s movement speed,meeting the stability requirements for agricultural operations.
文摘This study investigates prescribed-time position tracking control for electromagnetic satellite formations subject to model uncertainties and external disturbances.Using the Clohessy-Wiltshire equations as the relative motion dynamics model,a prescribed time output feedback control strategy is proposed.A prescribed-time extended state observer is designed to estimate the relative velocity and external disturbances.The disturbance estimates are then used as the feedforward component of the controller.Building on this framework,a novel prescribed-time active disturbance rejection control strategy for position tracking is developed via a backstepping control design.The convergence of the extended state observer and the stability of the closed-loop system are rigorously analyzed using Lyapunov stability theory.Numerical simulations are performed to validate the effectiveness of the proposed controller.
基金supported by the Zhejiang Provincial Natural Science Foundation(LY24F030011,LY23F030005)the National Natural Science Foundation of China(62373131).
文摘In this paper,a pair of dynamic high-gain observer and output feedback controller is proposed for nonlinear systems with multiple unknown time delays.By constructing Lyapunov-Krasovskii functionals,it shows that global state asymptotic regulation can be ensured by introducing a single dynamic gain;furthermore,global asymptotic stabilization can be achieved by choosing a sufficiently large static scaling gain when the upper bounds of all system parameters are known.Especially,the output coefficient is allowed to be non-differentiable with unknown upper bound.This paper proposes a generalized Lyapunov matrix inequality based dynamic-gain scaling method,which significantly simplifies the design computational complexity by comparing with the classic backstepping method.
基金supported by the Autonomous Innovation Team Foundation for“20 Items of the New University”of Jinan City(202228087)the National Natural Science Foundation of China(62073190).
文摘This paper studies global stabilization via predictor-based sampled-data output feedback for a class of feedforward nonlinear time-delay systems.Note that the traditional sampled-data observer via zero-order holder may result in the performance degradation of the observer.In this paper,an improved predictor-based observer is designed to compensate for the influence of the unmeasurable states,sampling errors and output delay.In addition,a sampled-data output-feedback controller is also constructed using the gain scaling technique.By the Lyapunov-Krasovskii functional method,the global exponential stability of the resulting closed-loop system can be guaranteed under some sufficient conditions.The simulation results are provided to demonstrate the main results.
基金supported by the National Natural Science Foundation of China(Grant No.52105466).
文摘The prediction and compensation control of marine ship motion is crucial for ensuring the safety of offshore wind turbine loading and unloading operations.However,the accuracy of prediction and control is significantly affected by the hysteresis phenomenon in the wave compensation system.To address this issue,a ship heave motion prediction is proposed in this paper on the basis of the Gauss-DeepAR(AR stands for autoregressive recurrent)model and the Hilbert−Huang time-delay compensation control strategy.Initially,the zero upward traveling wave period of the level 4−6 sea state ship heave motion is analyzed,which serves as the input sliding window for the Gauss-DeepAR prediction model,and probability predictions at different wave direction angles are conducted.Next,considering the hysteresis characteristics of the ship heave motion compensation platform,the Hilbert−Huang transform is employed to analyze and calculate the hysteresis delay of the compensation platform.After the optimal control action value is subsequently calculated,simulations and hardware platform tests are conducted.The simulation results demonstrated that the Gauss-DeepAR model outperforms autoregressive integrated moving average model(ARIMA),support vector machine(SVM),and longshort-term memory(LSTM)in predicting non-independent identically distributed datasets at a 90°wave direction angle in the level 4−6 sea states.Furthermore,the model has good predictive performance and generalizability for non-independent and non-uniformly distributed datasets at a 180°wave direction angle.The hardware platform compensation test results revealed that the Hilbert–Huang method has an outstanding effect on determining the hysteretic delay and selecting the optimal control action value,and the compensation efficiency was higher than 90%in the level 4−6 sea states.
基金supported in part by the Japan Society for the Promotion of Science Grants-in-Aid for Scientific Research(B)(23K25252,24K03325)the National Natural Science Foundation of China(61873348)the Natural Science Foundation of Hubei Province,China(2020CFA031)。
文摘As a closed-loop learning control method,repetitive control has been widely used in a variety of areas from appliances to aviation.A repetitive control system features perfect reference tracking and disturbance rejection in the steady state for periodic signals with a fixed period.This characteristic is important not only for conventional technologies and conventional industries but also for advanced technologies and emerging industries.This paper first explains the concept of repetitive control from its original idea.Next,it describes the structure of a repetitive controller as an internal model and shows the respective points of continuous-and discrete-time repetitive control.It presents a categorized list of practical applications of repetitive control.Moreover,two concrete applications,namely the control of a robotic manipulator and a rotating system,demonstrate the validity of the method with experimental results.Several current studies in this field are also reviewed,and some challenges and future studies for repetitive control are provided.
基金Supported by the Fundamental Research Funds for the Central Universities(2024ZYGXZR047)the National Natural Science Foundation of China(62373156)the Guangdong Basic and Applied Basic Research Foundation(2024A1515011736)。
文摘This article investigates the robust current tracking control problem of three-phase grid-connected inverters with LCL filter under external disturbance by a dynamic state feedback control method.First,this paper constructs an internal model to learn the information of the states and input of the grid-connected inverter under steady state.Second,by utilizing the internal model principle,the paper turns the tracking control problem into the robust stabilization control problem based on some appropriate coordinate transformations.Then,The paper designs a dynamics state feedback control law to deal with this robust stabilization problem,and thus the solution of the robust current tracking control problem of three-phase grid-connected inverters can be obtained.This control method can ensure the asymptotic stability of the closedloop system.Finally,the paper illustrates the effectiveness of the proposed control approach through several groups of simulations,and compares it with the feedforward control method to verify the robustness of the proposed control method to uncertain parameters.
文摘Aiming to solve the steering instability and hysteresis of agricultural robots in the process of movement,a fusion PID control method of particle swarm optimization(PSO)and genetic algorithm(GA)was proposed.The fusion algorithm took advantage of the fast optimization ability of PSO to optimize the population screening link of GA.The Simulink simulation results showed that the convergence of the fitness function of the fusion algorithm was accelerated,the system response adjustment time was reduced,and the overshoot was almost zero.Then the algorithm was applied to the steering test of agricultural robot in various scenes.After modeling the steering system of agricultural robot,the steering test results in the unloaded suspended state showed that the PID control based on fusion algorithm reduced the rise time,response adjustment time and overshoot of the system,and improved the response speed and stability of the system,compared with the artificial trial and error PID control and the PID control based on GA.The actual road steering test results showed that the PID control response rise time based on the fusion algorithm was the shortest,about 4.43 s.When the target pulse number was set to 100,the actual mean value in the steady-state regulation stage was about 102.9,which was the closest to the target value among the three control methods,and the overshoot was reduced at the same time.The steering test results under various scene states showed that the PID control based on the proposed fusion algorithm had good anti-interference ability,it can adapt to the changes of environment and load and improve the performance of the control system.It was effective in the steering control of agricultural robot.This method can provide a reference for the precise steering control of other robots.
基金supported in part by National Natural Science Foundation of China(Nos.62373188,62003162)the Natural Science Foundation of Jiangsu Province of China(Nos.BK20240182,BK20222012)+2 种基金the Industry-University Research Innovation Foundation for the Chinese Ministry of Education(No.2021ZYA02005)the Aeronautical Science Foundation of China(Nos.20220007052003,20200007018001)the Fundamental Research Funds for the Central Universities,China(Nos.NE2024004,NI2024001)。
文摘To solve the problem of in-flight actuator faults and parameter uncertainties for multiple Unmanned Aerial Vehicles(UAVs),and reduce the communication and computational resource consumption of multiple UAVs,a Fraction-Order(FO)sliding-mode Fault-Tolerant Cooperative Control(FTCC)strategy is proposed for multiple UAVs based on Event-Triggered Communication Mechanism(ET-COM-M)and Event-Triggered Control Mechanism(ET-CON-M).First,by considering the limited communication bandwidth of multiple UAVs in formation,an ET-COM-M is designed to significantly reduce communication times.Then,a distributed observer is skillfully constructed to estimate the reference signals for follower UAVs.Moreover,the adaptive strategy is incorporated into the Radial Basis Function Neural Network(RBFNN)to learn the lumped unknown terms for handling bias actuator faults and parameter uncertainties.Besides,the Nussbaum method is used to deal with the loss-of-effectiveness faults.To further achieve the refined control performance against faults,FO calculus is artfully integrated into the sliding-mode control protocol with ET-CON-M.Finally,Zeno behavior is excluded by rigorous theoretical analysis and Lyapunov stability is proved to show the effectiveness of the designed FTCC strategy.Simulation results show that the designed FTCC strategy with Event-Triggered Mechanism(ETM)can guarantee the safety of multiple UAVs and simultaneously reduce the communication and control frequencies,making the developed control scheme applicable in engineering.
基金supported by the National Natural Science Foundation of China(62203176,62173038)Guangzhou Key Research and Development Program(2025B03J0072)+5 种基金Guangdong High-Level Talents Special Support Programme(2024TQ08Z107)Anhui Province Natural Science Funds for Distinguished Young Scholar(2308085J02)State Key Laboratory of Intelligent Vehicle Safety Technology(IVSTSKL-202402,IVSTSKL-202430,IVSTSKL-202508,IVSTSKL-202520)State Key Laboratory of Intelligent Green Vehicle and Mobility(KFY2417)State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body(32215010),Wuhu Major Scientific and Technological Achievements Engineering Project(2021zc04).
文摘Mobile wheel-legged robots exhibiting mobility,stability and reliability have garnered heightened research attention in demanding real-world scenarios,especially in material transport,emergency response and space exploration.The kinematics model merely delineates the geometric relationship of the controlled objective,disregarding force feedback.This study investigates model predictive trajectory tracking control utilising the robot dynamic model(DRMPC)in the context of unpredictable interactions.The predictive tracking controller for the wheel-legged robot is introduced in the context of position tracking.A dynamic approximator is employed to address the uncertain interactions in the tracking process.Ultimately,cosimulation and empirical tests are conducted to demonstrate the efficacy of the devised control methodology,which achieves high precision and dependable robustness.This work can elucidate the technical and practical oversight of autonomous movement in complicated environments and enhance the manoeuverability and flexibility.
基金supported by the National Natural Science Foundation of China(624B2140).
文摘This paper presents an adaptive formation control method for a heterogeneous robot swarm,utilising a multilevel formation task tree to model various types of formation tasks and a single-state distributed k-winner-take-all(S-DKWTA)algorithm to address the MRTA problem.In addition,we propose an enhanced load reassignment algorithm to resolve conflicts when using S-DKWTA.The S-DKWTA algorithm demonstrates the capability to manage multiple objectives and dynamically select leaders in real-time,thereby optimising formation efficiency and reducing energy consumption.The proposed approach integrates an enhanced artificial potential field(APF)to govern the motion of heterogeneous robot systems which encompasses both unmanned ground vehicles(UGVs)and unmanned aerial vehicles(UAVs),thereby achieving collision and obstacle avoidance.Simulations employing UGVs and UAVs swarm to achieve formation movement demonstrate the efficacy of this approach.The amalgamation of S-DKWTA and improved APF ensures stable and adaptable formation control,underscoring its potential for diverse multirobot applications.
基金supported by the National Natural Science Foundation of China(62333011,62020106003)the Natural Science Foundation of Jiangsu Province of China(BK20222012)+1 种基金the Fundamental Research Funds for the Central Universities(NE2024005)the Postgraduate Research&Practice Innovation Program of Jiangsu Province(KYCX24_0594)。
文摘This paper is concerned with adaptive consensus tracking control of nonlinear multi-agent systems with actuator faults and unknown nonidentical control directions under double semi-Markovian switching topologies.Considering the complex working environment and the stability differences in communication links between leaders and followers,a double semi-Markov process is first introduced to describe the random switching of communication topologies in the leader-follower structure.In order to address challenges from the unknown nonidentical control directions and partial loss of effectiveness actuator faults,a completely independent parameter is introduced into the Nussbaum function to overcome the inherent obstacle of mutual cancellation and avoid the rapid growth rate.Considering only the state information of agents is transmitted among the agents,an adaptive distributed fault-tolerant consensus tracking control is proposed based on the double semi-Markovian switching topologies using the designed Nussbaum function.Furthermore,the stability of the closed-loop nonlinear multi-agent systems is analyzed using contradiction argument and Lyapunov theorem,from which the asymptotic consensus tracking in mean square sense can be obtained.A numerical simulation example is provided to verify the effectiveness of the proposed algorithm.
