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
This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication effic...This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication efficiency, an edge-based dynamic event-triggered mechanism is developed for the communication channels between neighboring QUAVs. However, this edge-based dynamic event-triggered communication(DETC) may cause discontinuities in the reference signals. To solve this problem, a distributed estimator is designed for each QUAV to obtain the leader's output signals. Considering the safety of QUAV formation flying, this paper designs a function transformation method that constrains the attitudes of the QUAVs to a strictly safe region. Furthermore, an inverse optimal control strategy is proposed based on the backstepping methodology. This scheme not only minimizes the cost function but also avoids the necessity of solving the Hamilton-Jacobi-Bellman equation. Finally, the stability of the QUAV systems is proven using Lyapunov theory, and the effectiveness of the proposed control method is verified through simulation.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
It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typica...It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.展开更多
This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater pene...This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.展开更多
Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a nove...Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions.First,the equations of motion for the aircraft are reformulated as a system of stochastic differential equations,which are subsequently transformed into a deterministic form.By modeling turbulence as a Gaussian random process and incorporating it directly into the control system,the proposed method proactively compensates for the adverse effects of turbulence.The transformation is achieved using semi-invariant techniques.Second,the control problem is formulated as an optimization task,aiming to minimize the deviation between the actual and desired turn characteristics,specifically the angular velocity.Finally,a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters.Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches,ensuring both stability and precision in turbulent wind conditions.展开更多
Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This stu...Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.展开更多
The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the ...The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.展开更多
This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state obs...This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.展开更多
The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)at...The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)attenuation behavior remain poorly understood.To address this gap,a thermodynamically controlled periodic coordination strategy is proposed to achieve precise modulation of magnetic nanoparticle spacing.This approach unveils the evolution of magnetic domain configurations,progressing from individual to coupled and ultimately to crosslinked domain configurations.A unique magnetic coupling phenomenon surpasses the Snoek limit in low-frequency range,which is observed through micromagnetic simulation.The crosslinked magnetic configuration achieves effective low-frequency EM wave absorption at 3.68 GHz,encompassing nearly the entire C-band.This exceptional magnetic interaction significantly enhances radar camouflage and thermal insulation properties.Additionally,a robust gradient metamaterial design extends coverage across the full band(2–40 GHz),effectively mitigating the impact of EM pollution on human health and environment.This comprehensive study elucidates the evolution mechanisms of magnetic domain configurations,addresses gaps in dynamic magnetic modulation,and provides novel insights for the development of high-performance,low-frequency EM wave absorption materials.展开更多
Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-me...Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.展开更多
An investigation and outline of MetaControl and DeControl in Metaverses for control intelligence and knowledge automation are presented.Prescriptive control with prescriptive knowledge and parallel philosophy is propo...An investigation and outline of MetaControl and DeControl in Metaverses for control intelligence and knowledge automation are presented.Prescriptive control with prescriptive knowledge and parallel philosophy is proposed as the starting point for the new control philosophy and technology,especially for computational control of metasystems in cyberphysical-social systems.We argue that circular causality,the generalized feedback mechanism for complex and purposive systems,should be adapted as the fundamental principle for control and management of metasystems with metacomplexity in metaverses.Particularly,an interdisciplinary approach is suggested for MetaControl and DeControl as a new form of intelligent control based on five control metaverses:MetaVerses,MultiVerses,InterVerses,TransVerse,and DeepVerses.展开更多
Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter us...Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.展开更多
Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectiv...Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.展开更多
The multi-agent controllability is intrinsically affected by the network topology and the selection of leaders.A focus of exploring this problem is to uncover the relationship between the eigenspace of Laplacian matri...The multi-agent controllability is intrinsically affected by the network topology and the selection of leaders.A focus of exploring this problem is to uncover the relationship between the eigenspace of Laplacian matrix and network topology.For strongly connected directed circle graphs,we elaborate how the zero entries in the left eigenvectors of Laplacian matrix L arise.The topologies arising from left eigenvectors with zero entries are filtered to construct essentially controllable directed circle graphs regardless of the choice of leaders.We propose two methods for constructing a substantial quantity of essentially controllable graphs,with a focus on utilizing essentially controllable circle graphs as the foundation.For a special directed graph-OT tree,the controllability is shown to be related with its substructure-paths.This promotes the establishment of a sufficient and necessary condition for controllability.Finally,a method is presented to check the controllable subspace by identifying the left eigenvectors and generalized left eigenvectors.展开更多
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 National Natural Science Foundation of China (Grant Nos.62573134,62473100,62433018)the Guangdong Basic and Applied Basic Research Foundation(Grant Nos.2025A1515060017,2025A1515011436,2025B1515020065,2025A1515011789)the Guangzhou Basic and Applied Basic Research Project (Grant No.2025A04J3534)。
文摘This paper investigates the edge-based dynamic event-triggered inverse optimal formation control problem for multiple quadrotor unmanned aerial vehicles(QUAVs) with attitude constraints. To improve communication efficiency, an edge-based dynamic event-triggered mechanism is developed for the communication channels between neighboring QUAVs. However, this edge-based dynamic event-triggered communication(DETC) may cause discontinuities in the reference signals. To solve this problem, a distributed estimator is designed for each QUAV to obtain the leader's output signals. Considering the safety of QUAV formation flying, this paper designs a function transformation method that constrains the attitudes of the QUAVs to a strictly safe region. Furthermore, an inverse optimal control strategy is proposed based on the backstepping methodology. This scheme not only minimizes the cost function but also avoids the necessity of solving the Hamilton-Jacobi-Bellman equation. Finally, the stability of the QUAV systems is proven using Lyapunov theory, and the effectiveness of the proposed control method is verified through simulation.
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.
基金the support from National Natural Science Foundation of China(No.52275153)the Frontier Technologies R&D Program of Jiangsu,China(No.BF2024068)+1 种基金The Fund of Prospective Layout of Scientific Research for Nanjing University of Aeronautics and Astronautics,ChinaResearch Fund of State Key Laboratory of Mechanics and Control for Aerospace Structures(Nanjing University of Aeronautics and Astronautics),China(Nos.MCAS-I-0425K01,MCAS-I-0423G01)。
文摘It is well recognized that Structural Health Monitoring(SHM)reliability evaluation is a key aspect that needs to be urgently addressed to promote the wide application of SHM methods.However,the existing studies typically transfer the Non-Destructive Testing/Evaluation(NDT/E)reliability metrics to SHM without a systematic analysis of where these metrics originated.Seldom attentions are paid to the evaluation conditions which are very important to apply these metrics.Aimed at this issue,a new condition control-based Dual-Reliability Evaluation(Dual-RE)method for SHM is proposed.This new method is proposed based on a systematic analysis of the whole framework of reliability evaluation from instrument to NDT,and emphasis is paid to the evaluation condition control.Based on these analyses,considering the special online application scenario of SHM,the proposed Dual-RE method contains two key components:Integrated Sensor-based SHM-RE(IS-SHM-RE)and Critical Service Condition-based SHM-RE(CSC-SHM-RE).ISSHM-RE evaluates the reliability of integrated SHM sensor and system themselves under approximate repeatability conditions,while CSC-SHM-RE assesses SHM reliability under the dominant uncertainties during service,namely intermediate conditions.To demonstrate the Dual-RE,crack monitoring by using the Guided Wave-based-SHM(GW-SHM)on aircraft lug structures is taken as a case study.Both the crack detection and sizing performance are evaluated from accuracy and uncertainty.
基金supported by the Natural Science Foundation of China No.62303126the project Major Scientific and Technological Special Project of Guizhou Province([2024]014).
文摘This paper investigates the detection and mitigation of coordinated cyberattacks on Load Frequency Control(LFC)systems integrated with Battery Energy Storage Systems(BESS).As renewable energy sources gain greater penetration,power grids are becoming increasingly vulnerable to cyber threats,potentially leading to frequency instability and widespread disruptions.We model two significant attack vectors:load-altering attacks(LAAs)and false data injection attacks(FDIAs)that corrupt frequency measurements.These are analyzed for their impact on grid frequency stability in both linear and nonlinear LFC models,incorporating generation rate constraints and nonlinear loads.A coordinated attack strategy is presented,combining LAAs and FDIAs to achieve stealthiness by concealing frequency deviations from system operators,thereby maximizing disruption while evading traditional detection.To counteract these threats,we propose an Unknown Input Observer(UIO)-based detection framework for linear and nonlinear LFCs.The UIO is designed using linear matrix inequalities(LMIs)to estimate system states while isolating unknown attack inputs,enabling attack detection through monitoring measurement residuals against a predefined threshold.For mitigation,we leverage BESS capabilities with two adaptive strategies:dynamic mitigation for dynamic LAAs,which tunes BESS parameters to enhance the system’s stability margin and accelerate convergence to equilibrium;and staticmitigation for static LAAs and FDIAs.Simulations show that the UIO achieves high detection accuracy,with residuals exceeding thresholds promptly under coordinated attacks,even in nonlinear models.Mitigation strategies reduce frequency deviations by up to 80%compared to unmitigated cases,restoring stability within seconds.
基金co-supported by the Fund of Robot Technology Used for Special Environment Key Laboratory of Sichuan Province(No.22kftk01)the Key Research and Development Program of Heilongjiang,China(No.2024ZXJ07B05)the National Natural Science Foundation of China(No.92471103)。
文摘Unmanned aircraft are highly vulnerable to crosswind-induced turbulence during complex maneuvers such as turning,which can significantly compromise control and reduce autopilot effectiveness.This paper presents a novel control strategy to improve the controllability of unmanned aircraft in challenging wind conditions.First,the equations of motion for the aircraft are reformulated as a system of stochastic differential equations,which are subsequently transformed into a deterministic form.By modeling turbulence as a Gaussian random process and incorporating it directly into the control system,the proposed method proactively compensates for the adverse effects of turbulence.The transformation is achieved using semi-invariant techniques.Second,the control problem is formulated as an optimization task,aiming to minimize the deviation between the actual and desired turn characteristics,specifically the angular velocity.Finally,a new numerical method with proven global convergence is employed to compute the optimal autopilot parameters.Simulation results using a medium-range unmanned aircraft model under continuous turbulent gusts demonstrate that the proposed method significantly outperforms existing approaches,ensuring both stability and precision in turbulent wind conditions.
基金supported by the Malaysia Ministry of Higher Education under Fundamental Research Grant Scheme with Project Code:FRGS/1/2024/TK07/USM/02/3.
文摘Mobile service robots(MSRs)in hospital environments require precise and robust trajectory tracking to ensure reliable operation under dynamic conditions,including model uncertainties and external disturbances.This study presents a cognitive control strategy that integrates a Numerical Feedforward Inverse Dynamic Controller(NFIDC)with a Feedback Radial Basis Function Neural Network(FRBFNN).The robot’s mechanical structure was designed in SolidWorks 2022 SP2.0 and validated under operational loads using finite element analysis in ANSYS 2022 R1.The NFIDC-FRBFNN framework merges proactive inverse dynamic compensation with adaptive neural learning to achieve smooth torque responses and accurate motion control.A two-stage simulation evaluation was conducted.In the first stage,the controller was tested in a simulated hospital environment under both ideal and non-ideal conditions.In the second,it was benchmarked against four established controllers-Neural Network Model Reference Adaptive(NNMRA),Z-number Fuzzy Logic(Z-FL),Adaptive Dynamic Controller(ADC),and Fuzzy Logic-PID(FL-PID)—using circular and lemniscate trajectories.Across ten runs,the proposed controller achieved the lowest tracking errors under all conditions.Under ideal conditions,it achieved average improvements of 55.24%,75.75%,and 55.20%in integral absolute error(IAE),integral squared error(ISE),and mean absolute error(MAE),respectively,with coefficient of variation(CV)reductions above 55%.Under non-ideal conditions,average improvements exceeded 64%in IAE,77%in ISE,and 66%in MAE,while maintaining CV reductions above 57%.These results confirm that the NFIDC-FRBFNN controller offers superior accuracy,robustness,and consistency for real-time path tracking in healthcare robotics.
基金Project(U2034211)supported by the National Natural Science Foundation of ChinaProject(20232ACE01013)supported by the Major Scientific and Technological Research and Development Special Project of Jiangxi Province,China。
文摘The safe driving and operation of trains is a necessary condition for ensuring the safe operation of trains.In particular,heavy-haul trains are characterized by the difficulty in driving and operation.Considering the uncertainties in train driving and operation,this paper analyzes the relationship between the safety of heavy-haul electric locomotive hauled trains and driving and operation.It studies the auxiliary intelligent driving safety operation control methods.Through K-means to identify the characteristics of drivers'driving manipulation,the hidden Markov model adaptively adjusts the train driving and operation sequence,and conducts auxiliary driving reconstruction for heavy-haul locomotive driving and operation.Based on the train running curve and the locomotive traction/braking characteristics,it smoothly controls the exertion of the traction/braking force of heavy-haul locomotives,thereby optimizing the driving safety control of heavy-haul trains in the vehicle-environment-track system.Finally,the train operation simulation and optimized driving verification are carried out by simulating some track sections.The results show that the proposed method can correct and pre-optimize driving operations,improving the smoothness of heavy-haul trains by approximately 10%.It verifies the effectiveness of the proposed train assisted driving control reconstruction method,facilitating the smooth and safe operation of heavy-haul trains.
基金supported by the National Natural Science Foundation of China(Grant Nos.62473344,92471204)the Natural Science Basic Research Program of Shaanxi(Grant No.2025JC-YBQN035)Ministry of Education's Industry School Cooperation Collaborative Education Project(Grant No.240704701190619)。
文摘This paper proposes an augmented reduced-order active disturbance rejection control(ARADRC)to address the control challenges in nonlinear systems with unknown disturbances.An augmented reduced-order extended state observer(ARESO)is constructed to estimate the unmeasured states,the total disturbance,and its derivatives.Compared to conventional ESOs,the proposed ARESO can enhance the estimation performance by actively estimating the derivatives of the total disturbance.In the time domain,by an inductive decoupling-based bound analysis method,this paper rigorously investigates the closed-loop transient performance without the prior assumption on the boundedness of derivatives of nonlinear uncertainties.In the frequency domain,a comparative analysis demonstrates the superiority of ARADRC in both disturbance estimation and rejection.Finally,the magnetic levitation experiments validate the effectiveness of the proposed method.
基金supported by the National Natural Science Foundation of China(22265021,52231007,and 12327804)the Aeronautical Science Foundation of China(2020Z056056003)Jiangxi Provincial Natural Science Foundation(20232BAB212004).
文摘The precise tuning of magnetic nanoparticle size and magnetic domains,thereby shaping magnetic properties.However,the dynamic evolution mechanisms of magnetic domain configurations in relation to electromagnetic(EM)attenuation behavior remain poorly understood.To address this gap,a thermodynamically controlled periodic coordination strategy is proposed to achieve precise modulation of magnetic nanoparticle spacing.This approach unveils the evolution of magnetic domain configurations,progressing from individual to coupled and ultimately to crosslinked domain configurations.A unique magnetic coupling phenomenon surpasses the Snoek limit in low-frequency range,which is observed through micromagnetic simulation.The crosslinked magnetic configuration achieves effective low-frequency EM wave absorption at 3.68 GHz,encompassing nearly the entire C-band.This exceptional magnetic interaction significantly enhances radar camouflage and thermal insulation properties.Additionally,a robust gradient metamaterial design extends coverage across the full band(2–40 GHz),effectively mitigating the impact of EM pollution on human health and environment.This comprehensive study elucidates the evolution mechanisms of magnetic domain configurations,addresses gaps in dynamic magnetic modulation,and provides novel insights for the development of high-performance,low-frequency EM wave absorption materials.
基金supported by Guangdong Basic and Applied Basic Research Foundation(Nos.2023A1515110824 and 2025A1515011839)Shenzhen Science and Technology Program(No.RCBS20231211090638066).
文摘Understanding water chemistry in karst regions is crucial for improving global water resource management and deepening our knowledge of the biogeochemical cycles shaping these sensitive environments.Despite advance-ments in karst hydrology,significant gaps remain in long-term trends,underlying processes,and quantitative effects of environmental changes.This is especially true in areas like the Wujiang River(WJ)in China,where human activities such as reservoir construction and land use/cover changes have accelerated hydrochemical changes.We combined recent and historical monitoring data to provide a detailed analysis of the spatial and temporal characteristics,evolution,and controlling factors of major ions in WJ.These findings are important for local water management and contribute to global efforts to manage similar karst systems facing human-induced pressures.Our research shows clear seasonal differences in solute concentrations,with higher levels during the dry season.WJ’s water is rich in calcium,with Ca-HCO_(3) ion pairs being the most common.Reservoir monitor-ing stations show much higher levels of NO_(3)^(−)and SO_(4)^(2−)compared to river-type stations,likely due to longer hydraulic retention time and increased acid deposition.The study confirms the significant role of pH and water temperature in rock weathering processes.Land use/cover changes were identified as the primary drivers of solute variations(46.37%),followed by lithology(13.92%)and temperature(8.35%).Over the past two decades,in-tense carbonate weathering has been observed,especially during wet seasons.Among karstic provinces,Guizhou Province stands out with the highest ion concentrations,indicative of its extensive karst coverage and heightened weathering processes.
文摘An investigation and outline of MetaControl and DeControl in Metaverses for control intelligence and knowledge automation are presented.Prescriptive control with prescriptive knowledge and parallel philosophy is proposed as the starting point for the new control philosophy and technology,especially for computational control of metasystems in cyberphysical-social systems.We argue that circular causality,the generalized feedback mechanism for complex and purposive systems,should be adapted as the fundamental principle for control and management of metasystems with metacomplexity in metaverses.Particularly,an interdisciplinary approach is suggested for MetaControl and DeControl as a new form of intelligent control based on five control metaverses:MetaVerses,MultiVerses,InterVerses,TransVerse,and DeepVerses.
基金supported in part by the National Natural Science Foundation of China(61873348,6230 3266,62273200)JSPS(Japan Society for the Promotion of Science) KAKENHI(22H03998,23K25252)
文摘Dear Editor,This letter presents an improved repetitive controller(IRC) that uses a complex-coefficient filter to enhance the tracking performance of a system for periodic signals. Compared with the low-pass filter used in the conventional repetitive controller(CRC), the complex-coefficient filter causes less change in the phase and amplitude of a signal at the frequencies of the periodic signal, especially at the fundamental frequency, when the two filters have the same cutofffrequency.
基金supported in part by the National Natural Science Foundation of China(62173255,62188101)Shenzhen Key Laboratory of Control Theory and Intelligent Systems(ZDSYS20220330161800001)
文摘Dear Editor,In this letter,a constrained networked predictive control strategy is proposed for the optimal control problem of complex nonlinear highorder fully actuated(HOFA)systems with noises.The method can effectively deal with nonlinearities,constraints,and noises in the system,optimize the performance metric,and present an upper bound on the stable output of the system.
基金supported by the National Natural Science Foundation of China(62373205,62033007)Taishan Scholars Climbing Program of Shandong Province of China,and Taishan Scholars Project of Shandong Province of China(tstp20230624,ts20190930).
文摘The multi-agent controllability is intrinsically affected by the network topology and the selection of leaders.A focus of exploring this problem is to uncover the relationship between the eigenspace of Laplacian matrix and network topology.For strongly connected directed circle graphs,we elaborate how the zero entries in the left eigenvectors of Laplacian matrix L arise.The topologies arising from left eigenvectors with zero entries are filtered to construct essentially controllable directed circle graphs regardless of the choice of leaders.We propose two methods for constructing a substantial quantity of essentially controllable graphs,with a focus on utilizing essentially controllable circle graphs as the foundation.For a special directed graph-OT tree,the controllability is shown to be related with its substructure-paths.This promotes the establishment of a sufficient and necessary condition for controllability.Finally,a method is presented to check the controllable subspace by identifying the left eigenvectors and generalized left eigenvectors.
