Aiming at the actuator time delay caused by the drive-by-wire technology,a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles.Firstly,the future vehicle ...Aiming at the actuator time delay caused by the drive-by-wire technology,a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles.Firstly,the future vehicle dynamics are predicted by a twodegree-of-freedom vehicle model with input delay.Secondly,in order to prevent the vehicle from destabilizing due to excessive side slip angles,the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment.Moreover,in order to improve the trajectory tracking ability,a side slip angle constraint determined by phase plane stability boundaries is added to the cost function.The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases.Meanwhile,the trajectory tracking ability is improved obviously by compensating the time delay.展开更多
In order to effectively achieve torque demand in electric vehicles （EVs）, this paper presents a torque control strategy based on model predictive control （MPC） for permanent magnet synchronous motor （PMSM） drive...In order to effectively achieve torque demand in electric vehicles （EVs）, this paper presents a torque control strategy based on model predictive control （MPC） for permanent magnet synchronous motor （PMSM） driven by a two-level three-phase inverter. A centralized control strategy is established in the MPC framework to track the torque demand and reduce energy loss, by directly optimizing the switch states of inverter. To fast determine the optimal control sequence in predictive process, a searching tree is built to look for optimal inputs by dynamic programming （DP） algorithm on the basis of the principle of optimality. Then we design a pruning method to check the candidate inputs that can enter the next predictive loop in order to decrease the computational burden of evaluation of input sequences. Finally, the simulation results on different conditions indicate that the proposed strategy can achieve a tradeoff between control performance and computational efficiency.展开更多
Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource explorat...Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted.展开更多
In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering th...In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.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
This paper presents a PC-based automated control system operation of the Northern Grain Silo of Jordan. The system connects to a PLC (programmable logic controller) device, and combines operator interface, PLC program...This paper presents a PC-based automated control system operation of the Northern Grain Silo of Jordan. The system connects to a PLC (programmable logic controller) device, and combines operator interface, PLC programming and monitoring functions into one platform. The PLC portion handles direct operations control, while the PC portion handles interfacing and data intensive functions. A simulation package is developed. The package generates a graphical user interface for real-time graphic animations of the Grain Silo operation. We discuss anticipated benefits of such a system and phases of implementation.展开更多
Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from...Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from MPC-based algorithms involving both spectrahedron(represented by linear matrix inequalities) and polyhedral(represented by a set of inequalities) constraints. According to the geometrical meaning of the inner product of vectors, the maximum length of the projection vector from the feasible set to a unit spherical coordinates vector is computed and the optimal solution has been proved to be one of the vertices of the feasible set. After computing the vertices,the convex hull of these vertices is determined which equals the feasible set. The simulation results show that the proposed method is especially efficient for low dimensional feasible set computation and avoids the non-unicity problem of optimizers as well as the memory consumption problem that encountered by projection algorithms.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 paper addresses the anti-disturbance safety control problem in spacecraft inspection missions,considering multiple positional obstacle constraints and attitude restrictions,both forbidden and mandatory,with logic...This paper addresses the anti-disturbance safety control problem in spacecraft inspection missions,considering multiple positional obstacle constraints and attitude restrictions,both forbidden and mandatory,with logical relationships.To address this challenge,a novel Composite AntiDisturbance Safety Control(CADSC) method is proposed,which combines control barrier functions with disturbance observers.The proposed CADSC framework achieves guaranteed safety control under complex constraints while explicitly addressing external disturbances and model uncertainties.First,positional obstacles are modeled using quadratic surface equations.At the same time,attitude constraints are formulated with logical operators,incorporating the interactions among star trackers,optical cameras,solar panels,and space environment vectors.Then,safe velocity and angular velocity are computed by solving Quadratic Programming(QP) problems based on the spacecraft's kinematic equations.The simplicity and disturbance-free nature of the kinematic model allow for efficient and accurate solutions to the QP problem,ensuring real-time applicability in mission-critical scenarios.Furthermore,proportional-like position and attitude controllers are developed to track the computed safe velocities.These controllers incorporate disturbance estimation techniques to compensate for external disturbances and model uncertainties,thereby enhancing the spacecraft's robustness.Finally,numerical simulations are conducted to validate the effectiveness of the proposed control strategy.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
Existing control systems for coiling temperature struggle with significant time lags and multi-objective synchronous control during cooling,limiting their temperature control accuracy.To overcome these drawbacks,an on...Existing control systems for coiling temperature struggle with significant time lags and multi-objective synchronous control during cooling,limiting their temperature control accuracy.To overcome these drawbacks,an online cooling system featuring multi-objective collaborative control is proposed.The proposed system achieves the synchronous control of the ultra-fast cooling temperature,middle temperature,and coiling temperature.First,the run-out table cooling zone is divided into multiple logical control zones,and traditional mechanism models are improved by introducing multiple heat flux adaptive coefficients.Then,a dynamic feedforward control method is developed to correct potential deviations in the calculation process.Finally,to enhance the proposed control system’s accuracy and self-learning capability,a multi-objective real-time adaptation strategy is introduced for dynamic heat flux adaptive coefficients adjustment.Analysis and application results show that the proposed multi-objective collaborative control system significantly improves the temperature control accuracy while ensuring the consistency of mechanical properties.Comparison results indicate that,under the proposed control system,the coiling temperature control accuracy within ±20℃ for segments located at 50 m from the strip head is improved by 26%,compared with the original control system.In addition,using the proposed system,the standard deviation of the yield strength is decreased by 38%,compared with the original control system.展开更多
The aircrafts have many structural components that withstand repeated impact loads,which may accumulate fatigue and potentially cause major accidents.To simulate repeated impact loads,it is imperative to design an imp...The aircrafts have many structural components that withstand repeated impact loads,which may accumulate fatigue and potentially cause major accidents.To simulate repeated impact loads,it is imperative to design an impact load cyclic fatigue simulator that applies repeated impact loads to structural components,such as landing gears.Furthermore,the impact load simulator must simulate various loads,and the identical set of parameters employed in conventional controllers are challenging to apply to varying operational conditions.Consequently,the controller must possess learning and adaptive capabilities.Based on the characteristics of repeated impact loads,an Adaptive Iterative Learning Control(AILC)based on the backstepping method is developed in this study.This AILC comprises backstepping control law,parameter adaptation law,iterative learning law,and robust dynamical control term.The adaptation law is not only utilized to estimate unknown system parameters,but also for online identification of system parameters.The iterative learning law can be utilized to learn the characteristics of the system under repeated operating conditions.The robust dynamical control term ensures the stability of the entire system.The experimental results indicate that the AILC can achieve tracking error convergence within a finite time and effectively achieve high-precision torque command tracking.展开更多
Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombinati...Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.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
基金the National Nature Science Foundation of China(Nos.61790564,U1664257)the National Key RD Program of China(No.2018YFB0104805)+1 种基金the Funds for Joint Project of Jilin Province and Jilin University(No.SXGJSF2017-2-1-1)the Funds of the Fundamental Research for the Central Universities.
文摘Aiming at the actuator time delay caused by the drive-by-wire technology,a novel manoeuvre stability controller based on model predictive control is proposed for full drive-by-wire vehicles.Firstly,the future vehicle dynamics are predicted by a twodegree-of-freedom vehicle model with input delay.Secondly,in order to prevent the vehicle from destabilizing due to excessive side slip angles,the determined ideal yaw rate and side slip angle are tracked simultaneously by optimizing the front wheel angle and additional yaw moment.Moreover,in order to improve the trajectory tracking ability,a side slip angle constraint determined by phase plane stability boundaries is added to the cost function.The results of Matlab and veDYNA co-simulation show that the regulated yaw rate can track the reference value well and the side slip angle decreases.Meanwhile,the trajectory tracking ability is improved obviously by compensating the time delay.
基金This work was supported by the NSFC Projects of International Cooperation and Exchanges （No. 61520106008）, the National Natural Science Foundation of China （Nos. 61503149, U1564207） and the Graduate Innovation Fund of Jilin University （No. 2016093）.
文摘In order to effectively achieve torque demand in electric vehicles （EVs）, this paper presents a torque control strategy based on model predictive control （MPC） for permanent magnet synchronous motor （PMSM） driven by a two-level three-phase inverter. A centralized control strategy is established in the MPC framework to track the torque demand and reduce energy loss, by directly optimizing the switch states of inverter. To fast determine the optimal control sequence in predictive process, a searching tree is built to look for optimal inputs by dynamic programming （DP） algorithm on the basis of the principle of optimality. Then we design a pruning method to check the candidate inputs that can enter the next predictive loop in order to decrease the computational burden of evaluation of input sequences. Finally, the simulation results on different conditions indicate that the proposed strategy can achieve a tradeoff between control performance and computational efficiency.
基金supported by the Natural Sciences and Engineering Research Council of Canada(NSERC)。
文摘Autonomous marine vehicles(AMVs)have received considerable attention in the past few decades,mainly because they play essential roles in broad marine applications such as environmental monitoring and resource exploration.Recent advances in the field of communication technologies,perception capability,computational power and advanced optimization algorithms have stimulated new interest in the development of AMVs.In order to deploy the constrained AMVs in the complex dynamic maritime environment,it is crucial to enhance the guidance and control capabilities through effective and practical planning,and control algorithms.Model predictive control(MPC)has been exceptionally successful in different fields due to its ability to systematically handle constraints while optimizing control performance.This paper aims to provide a review of recent progress in the context of motion planning and control for AMVs from the perceptive of MPC.Finally,future research trends and directions in this substantial research area of AMVs are highlighted.
基金Project(20180608005600843855-19)supported by the International Graduate Exchange Program of Beijing Institute of Technology,China。
文摘In order to track the desired path as fast as possible,a novel autonomous vehicle path tracking based on model predictive control(MPC)and PID speed control was proposed for high-speed automated vehicles considering the constraints of vehicle physical limits,in which a forward-backward integration scheme was introduced to generate a time-optimal speed profile subject to the tire-road friction limit.Moreover,this scheme was further extended along one moving prediction window.In the MPC controller,the prediction model was an 8-degree-of-freedom(DOF)vehicle model,while the plant was a 14-DOF vehicle model.For lateral control,a sequence of optimal wheel steering angles was generated from the MPC controller;for longitudinal control,the total wheel torque was generated from the PID speed controller embedded in the MPC framework.The proposed controller was implemented in MATLAB considering arbitrary curves of continuously varying curvature as the reference trajectory.The simulation test results show that the tracking errors are small for vehicle lateral and longitudinal positions and the tracking performances for trajectory and speed are good using the proposed controller.Additionally,the case of extended implementation in one moving prediction window requires shorter travel time than the case implemented along the entire path.
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.
文摘This paper presents a PC-based automated control system operation of the Northern Grain Silo of Jordan. The system connects to a PLC (programmable logic controller) device, and combines operator interface, PLC programming and monitoring functions into one platform. The PLC portion handles direct operations control, while the PC portion handles interfacing and data intensive functions. A simulation package is developed. The package generates a graphical user interface for real-time graphic animations of the Grain Silo operation. We discuss anticipated benefits of such a system and phases of implementation.
基金supported by the Natural Science Foundation of Zhejiang Province(LR17F030002)the Science Fund for Creative Research Groups of the National Natural Science Foundation of China(61621002)
文摘Feasible sets play an important role in model predictive control(MPC) optimal control problems(OCPs). This paper proposes a multi-parametric programming-based algorithm to compute the feasible set for OCP derived from MPC-based algorithms involving both spectrahedron(represented by linear matrix inequalities) and polyhedral(represented by a set of inequalities) constraints. According to the geometrical meaning of the inner product of vectors, the maximum length of the projection vector from the feasible set to a unit spherical coordinates vector is computed and the optimal solution has been proved to be one of the vertices of the feasible set. After computing the vertices,the convex hull of these vertices is determined which equals the feasible set. The simulation results show that the proposed method is especially efficient for low dimensional feasible set computation and avoids the non-unicity problem of optimizers as well as the memory consumption problem that encountered by projection algorithms.
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 National Natural Science Foundation of China(Nos.62403041,62403042,62203033)the Zhejiang Province Natural Science Foundation of China(No.LQ23F030020)the China Postdoctoral Science Foundation(No.2025M774251)。
文摘This paper addresses the anti-disturbance safety control problem in spacecraft inspection missions,considering multiple positional obstacle constraints and attitude restrictions,both forbidden and mandatory,with logical relationships.To address this challenge,a novel Composite AntiDisturbance Safety Control(CADSC) method is proposed,which combines control barrier functions with disturbance observers.The proposed CADSC framework achieves guaranteed safety control under complex constraints while explicitly addressing external disturbances and model uncertainties.First,positional obstacles are modeled using quadratic surface equations.At the same time,attitude constraints are formulated with logical operators,incorporating the interactions among star trackers,optical cameras,solar panels,and space environment vectors.Then,safe velocity and angular velocity are computed by solving Quadratic Programming(QP) problems based on the spacecraft's kinematic equations.The simplicity and disturbance-free nature of the kinematic model allow for efficient and accurate solutions to the QP problem,ensuring real-time applicability in mission-critical scenarios.Furthermore,proportional-like position and attitude controllers are developed to track the computed safe velocities.These controllers incorporate disturbance estimation techniques to compensate for external disturbances and model uncertainties,thereby enhancing the spacecraft's robustness.Finally,numerical simulations are conducted to validate the effectiveness of the proposed control strategy.
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financially supported by the National Key Research and Development Program of China(2022YFB3304800)the National Natural Science Foundation of China(Nos.52074085 and U21A20117).
文摘Existing control systems for coiling temperature struggle with significant time lags and multi-objective synchronous control during cooling,limiting their temperature control accuracy.To overcome these drawbacks,an online cooling system featuring multi-objective collaborative control is proposed.The proposed system achieves the synchronous control of the ultra-fast cooling temperature,middle temperature,and coiling temperature.First,the run-out table cooling zone is divided into multiple logical control zones,and traditional mechanism models are improved by introducing multiple heat flux adaptive coefficients.Then,a dynamic feedforward control method is developed to correct potential deviations in the calculation process.Finally,to enhance the proposed control system’s accuracy and self-learning capability,a multi-objective real-time adaptation strategy is introduced for dynamic heat flux adaptive coefficients adjustment.Analysis and application results show that the proposed multi-objective collaborative control system significantly improves the temperature control accuracy while ensuring the consistency of mechanical properties.Comparison results indicate that,under the proposed control system,the coiling temperature control accuracy within ±20℃ for segments located at 50 m from the strip head is improved by 26%,compared with the original control system.In addition,using the proposed system,the standard deviation of the yield strength is decreased by 38%,compared with the original control system.
基金supported by the National Natural Science Foundation of China(No.52275045)。
文摘The aircrafts have many structural components that withstand repeated impact loads,which may accumulate fatigue and potentially cause major accidents.To simulate repeated impact loads,it is imperative to design an impact load cyclic fatigue simulator that applies repeated impact loads to structural components,such as landing gears.Furthermore,the impact load simulator must simulate various loads,and the identical set of parameters employed in conventional controllers are challenging to apply to varying operational conditions.Consequently,the controller must possess learning and adaptive capabilities.Based on the characteristics of repeated impact loads,an Adaptive Iterative Learning Control(AILC)based on the backstepping method is developed in this study.This AILC comprises backstepping control law,parameter adaptation law,iterative learning law,and robust dynamical control term.The adaptation law is not only utilized to estimate unknown system parameters,but also for online identification of system parameters.The iterative learning law can be utilized to learn the characteristics of the system under repeated operating conditions.The robust dynamical control term ensures the stability of the entire system.The experimental results indicate that the AILC can achieve tracking error convergence within a finite time and effectively achieve high-precision torque command tracking.
基金Supported by National Natural Science Foundation of China(Grant Nos.52005039,51575043,51975048,U1764257).
文摘Mode shift is a special mechanism for a power-split hybrid electric vehicle(HEV)to realise electrically variable transmission,but the sudden change of equivalent inertia caused by topological configuration recombination during mode shift induces a significant torque shock.Therefore,a smooth transient process,among other concerns,typically associated with this category of vehicles,is of great importance.The present research aims to introduce a novel control strategy to manage the dynamic torque of multiple power sources and therefore im-prove ride comfort.To this end,a dynamic model of the objective power-split HEV is first built.To resolve the contention between vehicle jerk and clutch friction loss,a model predictive control(MPC)combined with control allocation(CA)is then designed for the clutch-engaged phase.To reduce the torque fluctuation caused by the inertia torques of multiple power sources,a dynamic compensation control strategy(DCcs)that coordinates motorgenerator torque to compensate for the transition torque is proposed for the brake-disengaged phase.Finally,the proposed control strategy is validated by simulation and bench test,and results show great potential in reducing shift duration,torque variation,vehicle jerk and friction loss(the simulation results show decreases of 22%,39%,83%and 53%,and the experimental results show decreases of 21%,74%,77%,and 59%,re-spectively),thereby improving shift quality.
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.
