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An Integrated Control Framework for Torque Vectoring and Active Suspension System 被引量:1
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作者 Jiwei Feng Jinhao Liang +6 位作者 Yanbo Lu Weichao Zhuang Dawei Pi Guodong Yin Liwei Xu Pai Peng Chaobin Zhou 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第1期62-73,共12页
Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to e... Four-wheel independently driven electric vehicles(FWID-EV)endow a flexible and scalable control framework to improve vehicle performance.This paper integrates the torque vectoring and active suspension system(ASS)to enhance the vehicle’s longitudinal and vertical motion control performance.While the nonlinear characteristic of the tire model leads to a relatively heavier computational burden.To facilitate the controller design and ease the load,a half-vehicle dynamics system is built and simplified to the linear-time-varying(LTV)model.Then a model predictive controller is developed by formulating the objective function by comprehensively considering the safety,energy-saving and comfort requirements.The in-wheel motor efficiency and the power loss of tire slip are treated as optimization indices in this work to reduce energy consumption.Finally,the effectiveness of the proposed controller is verified through the rapid-control-prototype(RCP)test.The results demonstrate the enhancement of the energy-saving as well as comfort on the basis of vehicle stability. 展开更多
关键词 Four-wheel independently driven electric vehicles Tire nonlinearity Linear-time-varying(LTV)model Model predictive control Rapid control prototype
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Hybrid Dynamic Variables-Dependent Event-Triggered Fuzzy Model Predictive Control 被引量:1
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作者 Xiongbo Wan Chaoling Zhang +2 位作者 Fan Wei Chuan-Ke Zhang Min Wu 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第3期723-733,共11页
This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative ... This article focuses on dynamic event-triggered mechanism(DETM)-based model predictive control(MPC) for T-S fuzzy systems.A hybrid dynamic variables-dependent DETM is carefully devised,which includes a multiplicative dynamic variable and an additive dynamic variable.The addressed DETM-based fuzzy MPC issue is described as a “min-max” optimization problem(OP).To facilitate the co-design of the MPC controller and the weighting matrix of the DETM,an auxiliary OP is proposed based on a new Lyapunov function and a new robust positive invariant(RPI) set that contain the membership functions and the hybrid dynamic variables.A dynamic event-triggered fuzzy MPC algorithm is developed accordingly,whose recursive feasibility is analysed by employing the RPI set.With the designed controller,the involved fuzzy system is ensured to be asymptotically stable.Two examples show that the new DETM and DETM-based MPC algorithm have the advantages of reducing resource consumption while yielding the anticipated performance. 展开更多
关键词 Dynamic event-triggered mechanism(DETM) hybrid dynamic variables model predictive control(MPC) robust positive invariant(RPI)set T-S fuzzy systems
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Research on Mixed Logic Dynamic Modeling and Finite Control Set Model Predictive Control of Multi-Inverter Parallel System
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作者 Xiaojuan Lu Mengqiao Chen Qingbo Zhang 《Energy Engineering》 EI 2023年第3期649-664,共16页
Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop cont... Parallel connection of multiple inverters is an important means to solve the expansion,reserve and protection of distributed power generation,such as photovoltaics.In view of the shortcomings of traditional droop control methods such as weak anti-interference ability,low tracking accuracy of inverter output voltage and serious circulation phenomenon,a finite control set model predictive control(FCS-MPC)strategy of microgrid multiinverter parallel system based on Mixed Logical Dynamical(MLD)modeling is proposed.Firstly,the MLD modeling method is introduced logical variables,combining discrete events and continuous events to form an overall differential equation,which makes the modeling more accurate.Then a predictive controller is designed based on the model,and constraints are added to the objective function,which can not only solve the real-time changes of the control system by online optimization,but also effectively obtain a higher tracking accuracy of the inverter output voltage and lower total harmonic distortion rate(Total Harmonics Distortion,THD);and suppress the circulating current between the inverters,to obtain a good dynamic response.Finally,the simulation is carried out onMATLAB/Simulink to verify the correctness of the model and the rationality of the proposed strategy.This paper aims to provide guidance for the design and optimal control of multi-inverter parallel systems. 展开更多
关键词 Multiple inverters in parallel microgrid mixed logic dynamic model finite control set model predictive control circulation
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Optimization Control of Multi-Mode Coupling All-Wheel Drive System for Hybrid Vehicle
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作者 Lipeng Zhang Zijian Wang +1 位作者 Liandong Wang Changan Ren 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第2期340-355,共16页
The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy... The all-wheel drive(AWD)hybrid system is a research focus on high-performance new energy vehicles that can meet the demands of dynamic performance and passing ability.Simultaneous optimization of the power and economy of hybrid vehicles becomes an issue.A unique multi-mode coupling(MMC)AWD hybrid system is presented to realize the distributed and centralized driving of the front and rear axles to achieve vectored distribution and full utilization of the system power between the axles of vehicles.Based on the parameters of the benchmarking model of a hybrid vehicle,the best model-predictive control-based energy management strategy is proposed.First,the drive system model was built after the analysis of the MMC-AWD’s drive modes.Next,three fundamental strategies were established to address power distribution adjustment and battery SOC maintenance when the SOC changed,which was followed by the design of a road driving force observer.Then,the energy consumption rate in the average time domain was processed before designing the minimum fuel consumption controller based on the equivalent fuel consumption coefficient.Finally,the advantage of the MMC-AWD was confirmed by comparison with the dynamic performance and economy of the BYD Song PLUS DMI-AWD.The findings indicate that,in comparison to the comparative hybrid system at road adhesion coefficients of 0.8 and 0.6,the MMC-AWD’s capacity to accelerate increases by 5.26%and 7.92%,respectively.When the road adhesion coefficient is 0.8,0.6,and 0.4,the maximum climbing ability increases by 14.22%,12.88%,and 4.55%,respectively.As a result,the dynamic performance is greatly enhanced,and the fuel savings rate per 100 km of mileage reaches 12.06%,which is also very economical.The proposed control strategies for the new hybrid AWD vehicle can optimize the power and economy simultaneously. 展开更多
关键词 Hybrid vehicle All-wheel drive Multi-mode coupling Energy management Model predictive control
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A Loss-model-based Efficiency Optimization Control Method for Induction Traction System of High-speed Train under Emergency Self-propelled Mode
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作者 Yutong Zhu Yaohua Li 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第2期227-239,共13页
Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link v... Increasing attention has been paid to the efficiency improvement of the induction traction system of high-speed trains due to the high demand for energy saving. In emergency self-propelled mode, however, the dc-link voltage and the traction power of the motor are significantly reduced, resulting in decreased traction efficiency due to the low load and low speed operations. Aiming to tackle this problem, a novel efficiency improved control method is introduced to the emergency mode of high-speed train traction system in this paper. In the proposed method, a total loss model of induction motor considering the behaviors of both iron and copper loss is established. An improved iterative algorithm with decreased computational burden is then introduced, resulting in a fast solving of the optimal flux reference for loss minimization at each control period. In addition, considering the parameter variation problem due to the low load and low speed operations, a parameter estimation method is integrated to improve the controller's robustness. The effectiveness of the proposed method on efficiency improvement at low voltage and low load conditions is demonstrated by simulated and experimental results. 展开更多
关键词 Efficiency optimization Induction motor Loss model control Motor drives Traction system
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Uncertainty and disturbance estimator-based model predictive control for wet flue gas desulphurization system
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作者 Shan Liu Wenqi Zhong +2 位作者 Li Sun Xi Chen Rafal Madonski 《Chinese Journal of Chemical Engineering》 SCIE EI CAS CSCD 2024年第3期182-194,共13页
Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal.The desulphurization control system,however,is subjected to complex reaction mechanis... Wet flue gas desulphurization technology is widely used in the industrial process for its capability of efficient pollution removal.The desulphurization control system,however,is subjected to complex reaction mechanisms and severe disturbances,which make for it difficult to achieve certain practically relevant control goals including emission and economic performances as well as system robustness.To address these challenges,a new robust control scheme based on uncertainty and disturbance estimator(UDE)and model predictive control(MPC)is proposed in this paper.The UDE is used to estimate and dynamically compensate acting disturbances,whereas MPC is deployed for optimal feedback regulation of the resultant dynamics.By viewing the system nonlinearities and unknown dynamics as disturbances,the proposed control framework allows to locally treat the considered nonlinear plant as a linear one.The obtained simulation results confirm that the utilization of UDE makes the tracking error negligibly small,even in the presence of unmodeled dynamics.In the conducted comparison study,the introduced control scheme outperforms both the standard MPC and PID(proportional-integral-derivative)control strategies in terms of transient performance and robustness.Furthermore,the results reveal that a lowpass-filter time constant has a significant effect on the robustness and the convergence range of the tracking error. 展开更多
关键词 Desulphurization system Disturbance rejection Model predictive control Uncertainty and disturbance estimator Nonlinear system
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Finite-Time Stabilization for Constrained Discrete-time Systems by Using Model Predictive Control
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作者 Bing Zhu Xiaozhuoer Yuan +1 位作者 Li Dai Zhiwen Qiang 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第7期1656-1666,共11页
In this paper, a model predictive control(MPC)framework is proposed for finite-time stabilization of linear and nonlinear discrete-time systems subject to state and control constraints. The proposed MPC framework guar... In this paper, a model predictive control(MPC)framework is proposed for finite-time stabilization of linear and nonlinear discrete-time systems subject to state and control constraints. The proposed MPC framework guarantees the finite-time convergence property by assigning the control horizon equal to the dimension of the overall system, and only penalizing the terminal cost in the optimization, where the stage costs are not penalized explicitly. A terminal inequality constraint is added to guarantee the feasibility and stability of the closed-loop system.Initial feasibility can be improved via augmentation. The finite-time convergence of the proposed MPC is proved theoretically,and is supported by simulation examples. 展开更多
关键词 CONSTRAINTS deadbeat control finite-time stabilization model predictive control(MPC)
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Path Tracking Controller Design of Automated Parking Systems via NMPC with an Instructible Solution
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作者 Liang Chen Zhaobo Qin +2 位作者 Manjiang Hu Yougang Bian Xiaoyan Peng 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第3期353-367,共15页
Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking acc... Parking difficulties have become a social issue that people have to solve.Automated parking system is practicable for quick par operations without a driver which can also greatly reduces the probability of parking accidents.The paper proposes a Lyapunov-based nonlinear model predictive controller embedding an instructable solution which is generated by the modified rear-wheel feedback method(RF-LNMPC)in order to improve the overall path tracking accuracy in parking conditions.Firstly,A discrete-time RF-LNMPC considering the position and attitude of the parking vehicle is proposed to increase the success rate of automated parking effectively.Secondly,the RF-LNMPC problem with a multi-objective cost function is solved by the Interior-Point Optimization,of which the iterative initial values are described as the instructable solutions calculated by combining modified rear-wheel feedback to improve the performance of local optimal solution.Thirdly,the details on the computation of the terminal constraint and terminal cost for the linear time-varying case is presented.The closed-loop stability is verified via Lyapunov techniques by considering the terminal constraint and terminal cost theoretically.Finally,the proposed RF-LNMPC is implemented on a selfdriving Lincoln MKZ platform and the experiment results have shown improved performance in parallel and vertical parking conditions.The Monte Carlo analysis also demonstrates good stability and repeatability of the proposed method which can be applied in practical use in the near future. 展开更多
关键词 Automated parking Path tracking controller Nonlinear model predictive control Monte Carlo analysis
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Real-Time Co-optimization of Gear Shifting and Engine Torque for Predictive Cruise Control of Heavy-Duty Trucks
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作者 Hongqing Chu Xiaoxiang Na +4 位作者 Huan Liu Yuhai Wang Zhuo Yang Lin Zhang Hong Chen 《Chinese Journal of Mechanical Engineering》 SCIE EI CAS CSCD 2024年第2期294-317,共24页
Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a rea... Fuel consumption is one of the main concerns for heavy-duty trucks.Predictive cruise control(PCC)provides an intriguing opportunity to reduce fuel consumption by using the upcoming road information.In this study,a real-time implementable PCC,which simultaneously optimizes engine torque and gear shifting,is proposed for heavy-duty trucks.To minimize fuel consumption,the problem of the PCC is formulated as a nonlinear model predictive control(MPC),in which the upcoming road elevation information is used.Finding the solution of the nonlinear MPC is time consuming;thus,a real-time implementable solver is developed based on Pontryagin’s maximum principle and indirect shooting method.Dynamic programming(DP)algorithm,as a global optimization algorithm,is used as a performance benchmark for the proposed solver.Simulation,hardware-in-the-loop and real-truck experiments are conducted to verify the performance of the proposed controller.The results demonstrate that the MPC-based solution performs nearly as well as the DP-based solution,with less than 1%deviation for testing roads.Moreover,the proposed co-optimization controller is implementable in a real-truck,and the proposed MPC-based PCC algorithm achieves a fuel-saving rate of 7.9%without compromising the truck’s travel time. 展开更多
关键词 Heavy-duty truck Predictive cruise control Model predictive control Pontryagin’s maximum principle Real-truck implementation
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Autonomous Vehicle Platoons In Urban Road Networks:A Joint Distributed Reinforcement Learning and Model Predictive Control Approach
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作者 Luigi D’Alfonso Francesco Giannini +3 位作者 Giuseppe Franzè Giuseppe Fedele Francesco Pupo Giancarlo Fortino 《IEEE/CAA Journal of Automatica Sinica》 SCIE EI CSCD 2024年第1期141-156,共16页
In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory... In this paper, platoons of autonomous vehicles operating in urban road networks are considered. From a methodological point of view, the problem of interest consists of formally characterizing vehicle state trajectory tubes by means of routing decisions complying with traffic congestion criteria. To this end, a novel distributed control architecture is conceived by taking advantage of two methodologies: deep reinforcement learning and model predictive control. On one hand, the routing decisions are obtained by using a distributed reinforcement learning algorithm that exploits available traffic data at each road junction. On the other hand, a bank of model predictive controllers is in charge of computing the more adequate control action for each involved vehicle. Such tasks are here combined into a single framework:the deep reinforcement learning output(action) is translated into a set-point to be tracked by the model predictive controller;conversely, the current vehicle position, resulting from the application of the control move, is exploited by the deep reinforcement learning unit for improving its reliability. The main novelty of the proposed solution lies in its hybrid nature: on one hand it fully exploits deep reinforcement learning capabilities for decisionmaking purposes;on the other hand, time-varying hard constraints are always satisfied during the dynamical platoon evolution imposed by the computed routing decisions. To efficiently evaluate the performance of the proposed control architecture, a co-design procedure, involving the SUMO and MATLAB platforms, is implemented so that complex operating environments can be used, and the information coming from road maps(links,junctions, obstacles, semaphores, etc.) and vehicle state trajectories can be shared and exchanged. Finally by considering as operating scenario a real entire city block and a platoon of eleven vehicles described by double-integrator models, several simulations have been performed with the aim to put in light the main f eatures of the proposed approach. Moreover, it is important to underline that in different operating scenarios the proposed reinforcement learning scheme is capable of significantly reducing traffic congestion phenomena when compared with well-reputed competitors. 展开更多
关键词 Distributed model predictive control distributed reinforcement learning routing decisions urban road networks
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Review of Field Weakening Control Strategies of Permanent Magnet Synchronous Motors
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作者 Runze Jing Gaolin Wang +1 位作者 Guoqiang Zhang Dianguo Xu 《CES Transactions on Electrical Machines and Systems》 EI CSCD 2024年第3期319-331,共13页
Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the s... Due to high power density,high efficiency,and accurate control performance,permanent magnet synchronous motors(PMSMs)have been widely adopted in equipment manufacturing and energy transformation fields.To expand the speed range under finite DC-bus voltage,extensive research on field weakening(FW)control strategies has been conducted.This paper summarizes the major FW control strategies of PMSMs,which are categorized into calculation-based methods,voltage closed-loop control methods,and model predictive control related methods.The existing strategies are analyzed and compared according to performance,robustness,and execution difficulty,which can facilitate the implementation of FW control. 展开更多
关键词 Calculation-based methods Field weakening control Model predictive control Permanent magnet synchronous motor OVERMODULATION Voltage closed-loop control
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Enhancing Safety in Autonomous Vehicle Navigation:An Optimized Path Planning Approach Leveraging Model Predictive Control
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作者 Shih-Lin Lin Bo-Chen Lin 《Computers, Materials & Continua》 SCIE EI 2024年第9期3555-3572,共18页
This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed ra... This paper explores the application of Model Predictive Control(MPC)to enhance safety and efficiency in autonomous vehicle(AV)navigation through optimized path planning.The evolution of AV technology has progressed rapidly,moving from basic driver-assistance systems(Level 1)to fully autonomous capabilities(Level 5).Central to this advancement are two key functionalities:Lane-Change Maneuvers(LCM)and Adaptive Cruise Control(ACC).In this study,a detailed simulation environment is created to replicate the road network between Nantun andWuri on National Freeway No.1 in Taiwan.The MPC controller is deployed to optimize vehicle trajectories,ensuring safe and efficient navigation.Simulated onboard sensors,including vehicle cameras and millimeterwave radar,are used to detect and respond to dynamic changes in the surrounding environment,enabling real-time decision-making for LCM and ACC.The simulation resultshighlight the superiority of the MPC-based approach in maintaining safe distances,executing controlled lane changes,and optimizing fuel efficiency.Specifically,the MPC controller effectively manages collision avoidance,reduces travel time,and contributes to smoother traffic flow compared to traditional path planning methods.These findings underscore the potential of MPC to enhance the reliability and safety of autonomous driving in complex traffic scenarios.Future research will focus on validating these results through real-world testing,addressing computational challenges for real-time implementation,and exploring the adaptability of MPC under various environmental conditions.This study provides a significant step towards achieving safer and more efficient autonomous vehicle navigation,paving the way for broader adoption of MPC in AV systems. 展开更多
关键词 Autonomous driving model predictive control(MPC) lane change maneuver(LCM) adaptive cruise control(ACC)
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Multi-Time Scale Optimal Scheduling of a Photovoltaic Energy Storage Building System Based on Model Predictive Control
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作者 Ximin Cao Xinglong Chen +2 位作者 He Huang Yanchi Zhang Qifan Huang 《Energy Engineering》 EI 2024年第4期1067-1089,共23页
Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a ... Building emission reduction is an important way to achieve China’s carbon peaking and carbon neutrality goals.Aiming at the problem of low carbon economic operation of a photovoltaic energy storage building system,a multi-time scale optimal scheduling strategy based on model predictive control(MPC)is proposed under the consideration of load optimization.First,load optimization is achieved by controlling the charging time of electric vehicles as well as adjusting the air conditioning operation temperature,and the photovoltaic energy storage building system model is constructed to propose a day-ahead scheduling strategy with the lowest daily operation cost.Second,considering inter-day to intra-day source-load prediction error,an intraday rolling optimal scheduling strategy based on MPC is proposed that dynamically corrects the day-ahead dispatch results to stabilize system power fluctuations and promote photovoltaic consumption.Finally,taking an office building on a summer work day as an example,the effectiveness of the proposed scheduling strategy is verified.The results of the example show that the strategy reduces the total operating cost of the photovoltaic energy storage building system by 17.11%,improves the carbon emission reduction by 7.99%,and the photovoltaic consumption rate reaches 98.57%,improving the system’s low-carbon and economic performance. 展开更多
关键词 Load optimization model predictive control multi-time scale optimal scheduling photovoltaic consumption photovoltaic energy storage building
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Multi-Time Scale Operation and Simulation Strategy of the Park Based on Model Predictive Control
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作者 Jun Zhao Chaoying Yang +1 位作者 Ran Li Jinge Song 《Energy Engineering》 EI 2024年第3期747-767,共21页
Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve... Due to the impact of source-load prediction power errors and uncertainties,the actual operation of the park will have a wide range of fluctuations compared with the expected state,resulting in its inability to achieve the expected economy.This paper constructs an operating simulation model of the park power grid operation considering demand response and proposes a multi-time scale operating simulation method that combines day-ahead optimization and model predictive control(MPC).In the day-ahead stage,an operating simulation plan that comprehensively considers the user’s side comfort and operating costs is proposed with a long-term time scale of 15 min.In order to cope with power fluctuations of photovoltaic,wind turbine and conventional load,MPC is used to track and roll correct the day-ahead operating simulation plan in the intra-day stage to meet the actual operating operation status of the park.Finally,the validity and economy of the operating simulation strategy are verified through the analysis of arithmetic examples. 展开更多
关键词 Demand response model predictive control multiple time scales operating simulation
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Evaluation of the Impact of Refined Quality Control Management Model on the Qualified Rate of Disinfection and Sterilization of Surgical Instruments in the Sterilization Supply Center 被引量:1
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作者 Qin Liu 《Journal of Clinical and Nursing Research》 2024年第1期168-173,共6页
Objective:To evaluate the application value of a refined quality control management model for a sterilization supply center.Methods:A retrospective analysis was conducted on the work situation of the sterilization sup... Objective:To evaluate the application value of a refined quality control management model for a sterilization supply center.Methods:A retrospective analysis was conducted on the work situation of the sterilization supply center from January 2021 to January 2023.The work situation before January 31,2022,was classified as the control group;a routine quality control management model was implemented,and the work situation after January 31,2022,was classified as the observation group.The quality of medical device management and department satisfaction between the two groups were compared.Results:The timely recovery and supply rate,classification and cleaning pass rate,disinfection pass rate,packaging pass rate,sterilization pass rate,and department satisfaction score in the observation group were all higher than those of the control group(P<0.05).Conclusion:Implementing a refined quality control management model in the sterilization supply center can improve the quality management level of medical devices and department satisfaction and is worthy of promotion. 展开更多
关键词 Refined quality control management model Sterilization supply center Disinfection and sterilization pass rate
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Virtually coupled train set control subject to space-time separation:A distributed economic MPC approach with emergency braking configuration
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作者 Xiaolin Luo Tao Tang +1 位作者 Le Wang Hongjie Liu 《High-Speed Railway》 2024年第3期143-152,共10页
The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calcula... The emerging virtual coupling technology aims to operate multiple train units in a Virtually Coupled Train Set(VCTS)at a minimal but safe distance.To guarantee collision avoidance,the safety distance should be calculated using the state-of-the-art space-time separation principle that separates the Emergency Braking(EB)trajectories of two successive units during the whole EB process.In this case,the minimal safety distance is usually numerically calculated without an analytic formulation.Thus,the constrained VCTS control problem is hard to address with space-time separation,which is still a gap in the existing literature.To solve this problem,we propose a Distributed Economic Model Predictive Control(DEMPC)approach with computation efficiency and theoretical guarantee.Specifically,to alleviate the computation burden,we transform implicit safety constraints into explicitly linear ones,such that the optimal control problem in DEMPC is a quadratic programming problem that can be solved efficiently.For theoretical analysis,sufficient conditions are derived to guarantee the recursive feasibility and stability of DEMPC,employing compatibility constraints,tube techniques and terminal ingredient tuning.Moreover,we extend our approach with globally optimal and distributed online EB configuration methods to shorten the minimal distance among VCTS.Finally,experimental results demonstrate the performance and advantages of the proposed approaches. 展开更多
关键词 Virtually coupled train set Space-time separation Economic model predictive control Distributed model predictive control Emergency braking configuration
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Disturbance rejection tube model predictive levitation control of maglev trains
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作者 Yirui Han Xiuming Yao Yu Yang 《High-Speed Railway》 2024年第1期57-63,共7页
Magnetic levitation control technology plays a significant role in maglev trains.Designing a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fa... Magnetic levitation control technology plays a significant role in maglev trains.Designing a controller for the levitation system is challenging due to the strong nonlinearity,open-loop instability,and the need for fast response and security.In this paper,we propose a Disturbance-Observe-based Tube Model Predictive Levitation Control(DO-TMPLC)scheme combined with a feedback linearization strategy for the levitation system.The proposed strategy incorporates state constraints and control input constraints,i.e.,the air gap,the vertical velocity,and the current applied to the coil.A feedback linearization strategy is used to cancel the nonlinearity of the tracking error system.Then,a disturbance observer is implemented to actively compensate for disturbances while a TMPLC controller is employed to alleviate the remaining disturbances.Furthermore,we analyze the recursive feasibility and input-to-state stability of the closed-loop system.The simulation results indicate the efficacy of the proposed control strategy. 展开更多
关键词 Maglev trains Levitation system Constrained control Disturbance observer Model predictive control
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A Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller Model Combined with an Improved Particle Swarm Optimization Method for Fall Detection
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作者 Jyun-Guo Wang 《Computer Systems Science & Engineering》 2024年第5期1149-1170,共22页
In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible t... In many Eastern and Western countries,falling birth rates have led to the gradual aging of society.Older adults are often left alone at home or live in a long-term care center,which results in them being susceptible to unsafe events(such as falls)that can have disastrous consequences.However,automatically detecting falls fromvideo data is challenging,and automatic fall detection methods usually require large volumes of training data,which can be difficult to acquire.To address this problem,video kinematic data can be used as training data,thereby avoiding the requirement of creating a large fall data set.This study integrated an improved particle swarm optimization method into a double interactively recurrent fuzzy cerebellar model articulation controller model to develop a costeffective and accurate fall detection system.First,it obtained an optical flow(OF)trajectory diagram from image sequences by using the OF method,and it solved problems related to focal length and object offset by employing the discrete Fourier transform(DFT)algorithm.Second,this study developed the D-IRFCMAC model,which combines spatial and temporal(recurrent)information.Third,it designed an IPSO(Improved Particle Swarm Optimization)algorithm that effectively strengthens the exploratory capabilities of the proposed D-IRFCMAC(Double-Interactively Recurrent Fuzzy Cerebellar Model Articulation Controller)model in the global search space.The proposed approach outperforms existing state-of-the-art methods in terms of action recognition accuracy on the UR-Fall,UP-Fall,and PRECIS HAR data sets.The UCF11 dataset had an average accuracy of 93.13%,whereas the UCF101 dataset had an average accuracy of 92.19%.The UR-Fall dataset had an accuracy of 100%,the UP-Fall dataset had an accuracy of 99.25%,and the PRECIS HAR dataset had an accuracy of 99.07%. 展开更多
关键词 Double interactively recurrent fuzzy cerebellar model articulation controller(D-IRFCMAC) improved particle swarm optimization(IPSO) fall detection
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Model Predictive Control for Cascaded H-Bridge PV Inverter with Capacitor Voltage Balance
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作者 Xinwei Wei Wanyu Tao +4 位作者 Xunbo Fu Xiufeng Hua Zhi Zhang Xiaodan Zhao Chen Qin 《Journal of Electronic Research and Application》 2024年第2期79-85,共7页
We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc... We designed an improved direct-current capacitor voltage balancing control model predictive control(MPC)for single-phase cascaded H-bridge multilevel photovoltaic(PV)inverters.Compared with conventional voltage balanc-ing control methods,the method proposed could make the PV strings of each submodule operate at their maximum power point by independent capacitor voltage control.Besides,the predicted and reference value of the grid-connected current was obtained according to the maximum power output of the maximum power point tracking.A cost function was con-structed to achieve the high-precision grid-connected control of the CHB inverter.Finally,the effectiveness of the proposed control method was verified through a semi-physical simulation platform with three submodules. 展开更多
关键词 Model predictive control(MPC) Photovoltaic system Cascaded H-bridge(CHB)inverter Capacitor voltage balance
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Cost Control with Modeling in Motor Housing Process
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作者 XU Run 《International Journal of Plant Engineering and Management》 2020年第1期51-64,共14页
With regards to the assembly line of cost control of Dechang company,the motor housing′s cost control of process will be necessarily appreciated.Though the supply quantity is large in a machine and the price of motor... With regards to the assembly line of cost control of Dechang company,the motor housing′s cost control of process will be necessarily appreciated.Though the supply quantity is large in a machine and the price of motor housing is cheaper,the cost control of automatic production line is significant in this respection.It is found that insufficiency power is main cause for production line failure.The cost control of equipment includes to structure wheel,conveyor and motor for benefit which also needs to be controlled in detail.Only in this way can we fundamentally resolve the main problem of high cost process.When the capital price L increases,Avc also increases too with nonlinear meantime,and Tc&Vc increase in proportion to K.Among them,the Tc increases the highest and then Vc increases lightly.Generally when labour quantity L and capital quantity K increase cost increases in proportion. 展开更多
关键词 automatic production line FLYWHEEL conveyor precision MOTOR motor housing MOLDS process of cost control modeling control
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