In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm ...In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.展开更多
针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小...针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小化油耗的优化问题;然后,利用MATLAB/Simulink仿真平台,在2种标准循环工况下对本文所提出的能量管理控制策略进行仿真验证,并与基于规则的能量管理控制策略进行了对比分析。结果表明,相对于基于规则的控制策略,采用基于MPC的控制策略在2种循环工况下的车辆百公里油耗分别降低了5.6%和5.2%,可有效提升燃油经济性。展开更多
Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each...Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame,resulting in degradation of synchronization performance.To address this challenge,this paper proposes a tube-based model predictive control(tube-MPC)approach for synchronization in lithography machines.First,the proposed modeling method accurately characterizes the coupling disturbances and synchronization dynamics.Subsequently,a tube-MPC approach is developed to ensure that the states of the nominal system are constrained within the terminal constraint set.To reduce the complexity of online computations,an approach is employed to transform online optimization problems into offline problems by creating an online lookup table.This enables the determination of optimal control inputs via a simplified online optimization algorithm.The robustness and trajectory tracking performance of the proposed approach are verified through simulation experiments,demonstrating its effectiveness in enhancing the synchronization performance of multiple motion systems.展开更多
Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature ...Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.展开更多
The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper pre...The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved 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
The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achiev...The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.展开更多
基金Jiangsu Provincial College Student Innovation and Entrepreneurship Program(Grant No.SJCX25_2184)—“Multi-energy Complementary Optimization and Vehicle-Storage Bidirectional Interaction Technology Driven by Novel 5E Framework”(Principal Investigator:Yuan-Yuan ShiFunding Agency:Jiangsu Provincial Education Department)+3 种基金Huaian Natural Science Research Project(Grant No.HAB2024046)—“Optimal Control of Flexible Cold-Heat-Power Integrated System with Source-Grid-Load-Storage Coordination”(Principal Investigator:Jie JiFunding Agency:Huaian Science and Technology Bureau)Huaiyin Institute of TechnologyUniversity-funded Project(GrantNo.HGYK202511)—“Data-driven CooperativeOptimization Dispatch for Source-Grid-Load Systems”(Principal Investigator:Chu-Tong ZhangFunding Agency:Huaiyin Institute of Technology).
文摘In order to solve the problems of slow dynamic response and difficult multi-source coordination of solar electric vehicle charging stations under intermittent renewable energy,this paper proposes a hardware-algorithm co-design framework:the T-type three-level bidirectional converter(100 kHz switching frequency)based on silicon carbide(SiC)MOSFET is deeply integrated with fuzzy model predictive control(Fuzzy-MPC).At the hardware level,the switching trajectory and resonance suppression circuit(attenuation resonance peak 18 dB)are optimized,and the total loss is reduced by 23%compared with the traditional silicon-based IGBT.At the algorithm level,the adaptive parameter update mechanism and multi-objective rolling optimization are adopted,and the 5 ms level dynamic power allocation is realized by relying on edge computing.Experiments on 800 V DC microgrid(including 600 kW photovoltaic and 150 A·h energy storage)built based on MATLAB/Simulink hardware-in-the-loop(HIL)platform show that the system shortens the battery charging time from 42 to 28 min(the charging speed is increased by 33%).Through the 78%valley power utilization rate,the power purchase cost of high-priced power grids was significantly reduced,and the levelized electricity price decreased by 10.3%;Under the irradiation fluctuation,the renewable energy consumption rate increases by 10.1%,and the DC bus voltage fluctuation is stable within±10 V when the load step is±30%.The co-design provides an economically feasible and dynamically robust solution for the efficient integration of PV-ESG-EV in the smart grid.
文摘针对P1P3构型混联式混合动力汽车(hybrid electric vehicles,HEVs)的能量管理问题,本文提出一种基于模型预测控制(model predictive control,MPC)的能量管理策略。首先,根据控制算法构建系统预测模型,使用二次规划算法优化求解车辆最小化油耗的优化问题;然后,利用MATLAB/Simulink仿真平台,在2种标准循环工况下对本文所提出的能量管理控制策略进行仿真验证,并与基于规则的能量管理控制策略进行了对比分析。结果表明,相对于基于规则的控制策略,采用基于MPC的控制策略在2种循环工况下的车辆百公里油耗分别降低了5.6%和5.2%,可有效提升燃油经济性。
基金supported by National Natural Science Foundation of China(52375530,52075132)Natural Science Foundation of Heilongjiang Province(YQ2022E025)+2 种基金State Key Laboratory of Precision Electronic Manufacturing Technology and Equipment(Guangdong University of Technology)(JMDZ202312)Fundamental Research Funds for the Central Universities(HIT.OCEF.2024034)Space Drive and Manipulation Mechanism Laboratory of BICE and National Key Laboratory of Space Intelligent Control(BICE-SDMM-2024-01).
文摘Lithography machines operate in scanning mode for the fabrication of large-scale integrated circuits(ICs),requiring high-precision synchronous motion between the reticle and wafer stages.Disturbances generated by each stage during high-acceleration movements are transmitted through the base frame,resulting in degradation of synchronization performance.To address this challenge,this paper proposes a tube-based model predictive control(tube-MPC)approach for synchronization in lithography machines.First,the proposed modeling method accurately characterizes the coupling disturbances and synchronization dynamics.Subsequently,a tube-MPC approach is developed to ensure that the states of the nominal system are constrained within the terminal constraint set.To reduce the complexity of online computations,an approach is employed to transform online optimization problems into offline problems by creating an online lookup table.This enables the determination of optimal control inputs via a simplified online optimization algorithm.The robustness and trajectory tracking performance of the proposed approach are verified through simulation experiments,demonstrating its effectiveness in enhancing the synchronization performance of multiple motion systems.
基金Supported by Qinghai University Youth Research Fund,China(Grant No.2023-QGY-15)。
文摘Due to errors in vehicle dynamics modeling,uncertainty in model parameters,and disturbances from curvature,the performance of the path tracking controller is poor or even unstable under high-speed and large-curvature conditions.Therefore,a path tracking robust control strategy based on force-driven H_(∞)and MPC is proposed.To fully exploit the nonlinear dynamics characteristics of tires,a force-driven state space model of a path tracking system based on a linear time-varying tire model is established;the H_(∞)and MPC methods are used to design a robust controller.Considering disturbance and system state constraints,the robust control constraint model based on LMI is established.Finally,the proposed controller is validated through joint simulations using CarSim and MATLAB.The results show that the maximum lateral deviation is reduced by 17.07%,and the maximum course angle deviation is reduced by 13.04%under large curvature disturbance conditions.The maximum lateral deviation is reduced by 27.85%,and the maximum course angle deviation is reduced by 31.17%under conditions of uncertain road adhesion coefficients.Based on the controller’s performance,the proposed controller effectively mitigates modeling errors,parameter uncertainties,and curvature disturbances.
基金supported in part by the National Natural Science Foundation of China under Grant 52575004the Beijing Natural Science Foundation under Grant L243004the National Natural Science Foundation of China under Grant 62403060.
文摘The problem of disturbance rejection in humanoid robots has been properly studied,with most prior work focusing on hip-ankle-stepping compliance control strategies or whole-body inverse dynamics control.This paper presents an adaptive disturbance rejection balance controller based on a Variable-inertia Centroidal Model Predictive Control(ViC-MPC)approach,designed to address both minor disturbances that affect standing balance and major disturbances requiring stepping adjustments.The controller also facilitates reliable balance recovery after stepping adjustments.The humanoid robot is modeled as a spatial variable-inertia ellipsoid,representing the distribution of centroidal dynamics,with the contact wrenches optimized in real-time through a customized MPC formulation.Inspired by capturability-based constraints,we propose an adaptive dynamic stability transition strategy.This strategy is activated based on the Retrospective Horizon Average Centroidal Velocity(RHACV)and the Capture Point(CP),ensuring effective stepping adjustments and disturbance rejection.With the torque-controlled humanoid robot BHR8P,extensive simulation and experimental results demonstrate the effectiveness of the proposed method,highlighting its capability to adapt to and recover from various disturbances with improved 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 National Natural Science Foundation of China(Grant Nos.52225212,52272418,U22A20100)National Key Research and Development Program of China(Grant No.2022YFB2503302).
文摘The development of chassis active safety control technology has improved vehicle stability under extreme conditions.However,its cross-system and multi-functional characteristics make the controller difficult to achieve cooperative goals.In addition,the chassis system,which has high complexity,numerous subsystems,and strong coupling,will also lead to low computing efficiency and poor control effect of the controller.Therefore,this paper proposes a scenario-driven hybrid distributed model predictive control algorithm with variable control topology.This algorithm divides multiple stability regions based on the vehicle’s β−γ phase plane,forming a mapping relationship between the control structure and the vehicle’s state.A control input fusion mechanism within the transition domain is designed to mitigate the problems of system state oscillation and control input jitter caused by switching control structures.Then,a distributed state-space equation with state coupling and input coupling characteristics is constructed,and a weighted local agent cost function in quadratic programming is derived.Through cost coupling,local agents can coordinate global performance goals.Finally,through Simulink/CarSim joint simulation and hardware-in-the-loop(HIL)test,the proposed algorithm is validated to improve vehicle stability while ensuring trajectory tracking accuracy and has good applicability for multi-objective coordinated control.This paper combines the advantages of distributed MPC and decentralized MPC,achieving a balance between approximating the global optimal results and the solution’s efficiency.
