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International Conference on Wireless Power Transfer, ICWPT 2022

作者： Xue, Xuchi Liu, Zhitao Liu, Jia Chen, Wenjie Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou310027 China

ISBN: (纸本)9789819906307

During the dynamic wireless charging process, the coupling coefficient between the wireless charging transmitter coil and the receiver coil varies greatly, thereby reducing the charging efficiency. Firstly, the change law of the magnetic coupling coefficient of the magnetic coupling mechanism in the process of dynamic wireless charging is analyzed. Secondly, the wireless charging network is analyzed to derive the relationship of the duty cycle under the optimal load. According to the changing law of the coupling coefficient, this paper analyzes the Kalman prediction model and the cubic exponential smoothing model, and proposes an improved error adaptive model based on the two algorithms. When the coupling coefficient changes rapidly, the error of the coefficient estimation can improve the efficiency of the whole wireless charging system. The method proposed in this paper can effectively improve the dynamic wireless charging efficiency by 9.5%, which is conducive to the popularization of electric AGV in the fields of transportation and logistics sorting. © 2023, The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd.

关键词： Efficiency

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Improved hybrid Gaussian process regression Model for state-of-health Estimation of Li-ion Batteries

Improved hybrid Gaussian process regression Model for State-...

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2024 China Automation Congress, CAC 2024

作者： An, Tao Liu, Zhitao Yan, Chizhou Xu, Ke Su, Hongye State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China Wanxiang A123 Systems Corp. Hangzhou China

ISBN: (纸本)9798350368604

Accurate state-of-health (SOH) estimation contributes to the healthy and stable operation of the Li-ion batteries. This paper proposes an improved hybrid Gaussian process regression (GPR) method incorporating physical information for the high-accuracy estimation of battery SOH. The estimation process considers the effects of temperature, discharge rate, and depth of discharge (DOD) on the battery health, and the relevant features of the electrode degradation process are extracted for battery SOH estimation. The kernel function of GPR comprehensively considers the mechanical characteristics of battery degradation and can effectively track the battery degradation process. The validation experiments were conducted on the A123 LFP/Graphite battery dataset. Sufficient comparative experiments have validated the accuracy and robustness of the proposed method. © 2024 IEEE.

关键词： state of charge

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A Novel Trajectory Planning Method Based on Trust Region Policy Optimization

IEEE Transactions on Intelligent Vehicles

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IEEE Transactions on Intelligent Vehicles 2024年 1-15页

作者： Ye, Bao-Lin Zhang, Jiajie Li, Lingxi Wu, Weimin Jiaxing Key Laboratory of Smart Transportations the School of Information Science and Engineering Jiaxing University China Elmore Family School of Electrical and Computer Engineering Purdue University Indianapolis USA State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and Control Zhejiang University Hangzhou China

Trajectory planning method is a research hotspot in autonomous driving. Existing reinforcement learning-based trajectory planning methods suffer from unstable performance due to the strong randomness of network weight parameter updates during the training process. Therefore, this paper proposes a novel trajectory planning method based on deep reinforcement learning trust region policy optimization (TRPO). Firstly, in order to enhance the robustness of the trajectory planning method based on deep reinforcement learning TRPO, a TRPO-LSTM based decision model was proposed. More specifically, a long short term memory (LSTM) based state feature extraction network was designed and embeded into a TRPO-based decision model to enhance the ability of TRPO to extract information from the environmental state space. Secondly, in order to make the planned trajectory adaptive to the dynamic changes of traffic environment, we presented a novel TRPO-LSTM trajectory fitting algorithm. To the best of our knowledge, this is the first work aiming at applying the TRPO-LSTM based decision model in the trajectory fitting process to search the optimal longitudinal trajectory speed. Finally, the proposed trajectory planning method was implemented and simulated on the CARLA simulator. The experimental results show that, compared with existing trajectory planning methods based on deep reinforcement learning algorithms, our proposed method achieves a cumulative reward improvement of over 28.9% in the scenario of four lane highway, and has better robustness. Meanwhile, the proposed method can achieve a lower collision rate of 0.93% while improving the average speed and comfort of vehicle driving. IEEE

关键词： Heuristic algorithms

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Enhanced Seagull Optimization Algorithm for Photovoltaic Cell Parameter Estimating 41

Enhanced Seagull Optimization Algorithm for Photovoltaic Cel...

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第41届中国控制会议

作者： Hongyin Wei Kailin Xu Jianming Zhang Institute of Cyber-Systems and Control State Key Laboratory of Industrial Control TechnologyZhejiang University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,an enhanced seagull optimization algorithm based on a double group evolutionary mechanism(DSOA) is proposed for photovoltaic(PV) cell parameter *** the DSOA,a double group search strategy and time-based mutation strategy are added to the population renewal mechanism of the conventional *** performance of DSOA on standard benchmark functions is surprising;it was good at accuracy and exploitation,also convergence *** with SOA and the other two classical intelligent optimization algorithms,the performance of DSOA is comprehensively *** is adopted to estimate PV cell *** simulation results demonstrate that estimated currents of circuit model based on DSOA have high similarity to the measured value of the photovoltaic cell.

关键词： Photovoltaic(PV) parameter estimating seagull optimization algorithm intelligent optimization algorithms

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A novel motion coordination method for variable-sized multi-mobile robots

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Frontiers of Information technology & Electronic Engineering 2023年第4期24卷 521-535页

作者： Zichao XING Xingkai WANG Shuo WANG Weimin WU Ruifen HU State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

Multi-mobile robot systems(MMRSs)are widely used for transportation in industrial scenes such as manufacturing and *** an MMRS,motion coordination is important as collisions and deadlocks may lead to losses or system ***,in some scenarios,robot sizes are different when loaded and unloaded,which means that the robots are variable-sized,making motion coordination more *** methods based on zone control need to first divide the environment into disjoint zones,and then allocate the zones statically or dynamically for motion *** zone-control-based methods are not accurate enough for variable-sized multi-mobile robots and reduce the efficiency of the *** paper describes a motion coordination method based on glued nodes,which can dynamically avoid collisions and deadlocks according to the roadmap structure and the real-time paths of *** features make this method directly applicable to various scenarios,instead of dividing a roadmap into disjoint *** proposed method has been applied to many industrial projects,and this study is based on some manufacturing projects for *** analysis and experimental results show that the proposed algorithm is effective and efficient.

关键词： Multi-mobile robot system Collision avoidance Deadlock avoidance Glued nodes Motion coordination

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Review of Clustering technology and Its Application in Coordinating Vehicle Subsystems

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Automotive Innovation 2023年第1期6卷 89-115页

作者： Caizhi Zhang Weifeng Huang Tong Niu Zhitao Liu Guofa Li Dongpu Cao Chongqing Automotive Collaborative Innovation Centre The State Key Laboratory of Mechanical TransmissionsChongqing UniversityChongqing 400044China State Key Laboratory of Industrial Control Technology Institute of Cyber‑Systems and ControlZhejiang UniversityHangzhou 310027China School of Vehicle and Mobility Tsinghua UniversityBeijingChina

Clustering is an unsupervised learning technology,and it groups information(observations or datasets)according to similarity *** clustering algorithms is a hot topic in recent years,and this area develops rapidly with the increasing complexity of data and the volume of *** this paper,the concept of clustering is introduced,and the clustering technologies are analyzed from traditional and modern ***,this paper summarizes the principles,advantages,and disadvantages of 20 traditional clustering algorithms and 4 modern ***,the core elements of clustering are presented,such as similarity measures and evaluation *** that data processing is often applied in vehicle engineering,finally,some specific applications of clustering algorithms in vehicles are listed and the future development of clustering in the era of big data is *** purpose of this review is to make a comprehensive survey that helps readers learn various clustering algorithms and choose the appropriate methods to use,especially in vehicles.

关键词： Unsupervised learning Clustering Similarity measures Vehicle

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Distributed event-triggered adaptive control for second-order nonlinear uncertain multi-agent systems

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Chinese Journal of Aeronautics 2021年第10期34卷 237-247页

作者： Ming XIAO Zhitao LIU Hongye SU The State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou 310027China

In this paper,the event-triggered consensus control problem for nonlinear uncertain multi-agent systems subject to unknown parameters and external disturbances is *** dynamics of subsystems are second-order with similar structures,and the nodes are connected by undirected *** event-triggered mechanisms are not only utilized in the transmission of information from the controllers to the actuators,and from the sensors to the controllers within each agent,but also in the communication between *** on the adaptive backstepping method,extra estimators are introduced to handle the unknown parameters,and the measurement errors that occur during the event-triggered communication are well handled by designing compensating terms for the control *** presented distributed event-triggered adaptive control laws can guarantee the boundness of the consensus tracking errors and the Zeno behavior is ***,the update frequency of the controllers and the load of communication burden are vastly *** obtained control protocol is further applied to a multi-input multi-output second-order nonlinear multi-agent system,and the simulation results show the effectiveness and advantages of our proposed method.

关键词： Adaptive distributed control structure Event-triggered control Multi-agent systems Second-order nonlinear models

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Obstacle Avoidance for Unicycle-Modelled Mobile Robots with Time-Varying control Barrier Functions 49

Obstacle Avoidance for Unicycle-Modelled Mobile Robots with ...

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49th Annual Conference of the IEEE industrial Electronics Society, IECON 2023

作者： Huang, Jihao Liu, Zhitao Zeng, Jun Chi, Xuemin Su, Hongye Institute of Cyber-Systems and Control Zhejiang University State Key Laboratory of Industrial Control Technology Hangzhou China Cruise Llc United States

ISBN: (纸本)9798350331820

In this paper, we propose a safety-critical controller based on time-varying control barrier functions (CBFs) for a robot with an unicycle model in the continuous-time domain to achieve navigation and dynamic collision avoidance. Unlike previous works, our proposed approach can control both linear and angular velocity to avoid collision with obstacles, overcoming the limitation of confined control performance due to the lack of control variable. To ensure that the robot reaches its destination, we also design a control Lyapunov function (CLF). Our safety-critical controller is formulated as a quadratic program (QP) optimization problem that incorporates CLF and CBFs as constraints, enabling real-time application for navigation and dynamic collision avoidance. Numerical simulations are conducted to verify the effectiveness of our proposed approach. © 2023 IEEE.

关键词： Lyapunov functions

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Few-shot object detection via class encoding and multi-target decoding

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IET cyber-systems and Robotics 2023年第2期5卷 1-14页

作者： Xueqiang Guo Hanqing Yang Mohan Wei Xiaotong Ye Yu Zhang State Key Laboratory of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina Key Laboratory of Collaborative Sensing and Autonomous Unmanned Systems of Zhejiang Province HangzhouChina

The task of few‐shot object detection is to classify and locate objects through a few annotated *** many studies have tried to solve this problem,the results are still not *** studies have found that the class margin significantly impacts the classification and representation of the targets to be *** methods use the loss function to balance the class margin,but the results show that the loss‐based methods only have a tiny improvement on the few‐shot object detection *** this study,the authors propose a class encoding method based on the transformer to balance the class margin,which can make the model pay more attention to the essential information of the features,thus increasing the recognition ability of the ***,the authors propose a multi‐target decoding method to aggregate RoI vectors generated from multi‐target images with multiple support vectors,which can significantly improve the detection ability of the detector for multi‐target *** on Pascal visual object classes(VOC)and Microsoft Common Objects in Context datasets show that our proposed Few‐Shot Object Detection via Class Encoding and Multi‐Target Decoding significantly improves upon baseline detectors(average accuracy improvement is up to 10.8%on VOC and 2.1%on COCO),achieving competitive *** general,we propose a new way to regulate the class margin between support set vectors and a way of feature aggregation for images containing multiple objects and achieve remarkable *** method is implemented on mmfewshot,and the code will be available later.

关键词： Class Margin Few-Shot Object Detection Multi-Target Transformer

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Model predictive control with fractional-order delay compensation for fast sampling systems

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Science China(Information Sciences) 2021年第7期64卷 165-180页

作者： Ze ZHOU Zhitao LIU Hongye SU Liyan ZHANG State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang University School of Automation Wuhan University of Technology

Model predictive control(MPC) is widely used in fast sampling systems owing to its fast regulating ability. However, the sampling delay is a key issue and tends to be a fractional multiple of the sampling period. If the fractional-order delay is not accurately offset, the controller output will exhibit errors, thus resulting in oscillations in controlled system. Moreover, the MPC delay compensation algorithm is limited to the computation time. To address the problems of fractional delay and computational burden in fast sampling systems, we propose a new method to compensate for the fractional-order sampling ***, we use a finite-impulse-response fractional delay filter based on a Lagrange interpolation polynomial to approximate the fractional portion. Moreover, we prove that high accuracy and simplicity can be ensured when the polynomial order is one. Then, we estimate the current state variable using the delayed sampling signal and control signals of past moments. Further, we obtain the current control signal according to the estimated state variable. By considering the simultaneous existence of computational and sampling delays,a full compensation strategy is proposed. Computational simulation results validate the proposed MPC algorithm with fractional-order delay compensation and demonstrate its advantages.

关键词： model predictive control fast sampling systems sampling delay fractional-order Lagrange interpolation polynomial

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