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A comprehensive review of electrochemical hybrid power supply systems and intelligent energy managements for unmanned aerial vehicles in public services

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Energy and AI 2022年第3期9卷 148-171页

作者： Caizhi Zhang Yuqi Qiu Jiawei Chen Yuehua Li Zhitao Liu Yang Liu Jiujun Zhang Chan Siew Hwa College of Mechanical and Vehicle Engineering The State Key Laboratory of Mechanical TransmissionsChongqing Automotive Collaborative Innovation CentreChongqing UniversityChongqing400044China College of Automation Chongqing UniversityKey Laboratory of Complex System Safety and ControlMinistry of EducationChongqing UniversityChongqing400044China School of Mechanical Engineering University of Science and Technology BeijingBeijing100083China State Key Laboratory of Industrial Control Technology Institute of Cyber-Systems and ControlZhejiang UniversityHangzhou310027China Institute for Sustainable Energy/College of Sciences Shanghai UniversityShanghai 200444China School of Mechanical and Aerospace Engineering Nanyang Technological University50 Nanyang Avenue639798Singapore Sichuan Energy Internet Research Institute Tsinghua UniversityChengdu 610213Sichuan ProvinceChina

The electric unmanned aerial vehicles (UAVs) are rapidly growing due to their abilities to perform some difficult or dangerous tasks as well as many public services including real-time monitoring, wireless coverage, search and rescue, wildlife surveys, and precision agriculture. However, the electrochemical power supply system of UAV is a critical issue in terms of its energy/power densities and lifetime for service endurance. In this paper, the current power supply systems used in UAVs are comprehensively reviewed and analyzed on the existing power configurations and the energy management systems. It is identified that a single type of electrochemical power source is not enough to support a UAV to achieve a long-haul flight;hence, a hybrid power system architecture is necessary. To make use of the advantages of each type of power source to increase the endurance and achieve good performance of the UAVs, the hybrid systems containing two or three types of power sources (fuel cell,battery, solar cell, and supercapacitor,) have to be developed. In this regard, the selection of an appropriate hybrid power structure with the optimized energy management system is critical for the efficient operation of a UAV. It is found that the data-driven models with artificial intelligence (AI) are promising in intelligent energy management. This paper can provide insights and guidelines for future research and development into the design and fabrication of the advanced UAV power systems.

关键词： Unmanned aerial vehicles(UAVs) Power supply system Fuel cell system Artificial intelligence(AI) Energy management systems

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Constraint-Following Based Adaptive Robust control for Underactuated Mechanical systems

Constraint-Following Based Adaptive Robust Control for Under...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Cui Wei Ye-Hwa Chen Yanling Wei Institute of Intelligent Manufacturing Nanjing Tech University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China George W. Woodruff School of Mechanical Engineering Georgia Institute of Technology Atlanta GA USA Key Laboratory of Measurement and Control of Complex System of Engineering School of Automation Southeast University Nanjing China

ISBN: (数字)9798331518493

ISBN: (纸本)9798331518509

This paper introduces an adaptive robust control approach tailored for underactuated mechanical systems encountering matched and mismatched uncertainty, employing a constraint-following methodology. The control strategy unfolds in two phases: initially, a nominal control scheme is devised neglecting uncertainty and deviations in initial conditions from constraints. Subsequently, uncertainty is categorized into matched and mismatched components, ensuring that mismatched uncertainties remain unobservable. Leveraging the structural characteristics of the uncertainty bound, a novel segmented adaptive law is proposed and seamlessly integrated into the adaptive robust control framework. By employing the Lyapunov minimax approach, the method ensures uniform boundedness and uniform ultimate boundedness simultaneously, thereby ensuring approximate adherence to constraints for underactuated mechanical systems facing both matched and mismatched uncertainties alongside initial condition deviations.

关键词： Robust control Uncertainty Adaptive systems Costs automation Nonlinear dynamical systems Mechanical systems Closed loop systems Robots

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A Real-time Framework of Multi-Camera Vehicle Tracking system

A Real-time Framework of Multi-Camera Vehicle Tracking Syste...

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2024 IEEE International Conference on Real-Time Computing and Robotics, RCAR 2024

作者： Zhuang, Hanyang Chen, Xingyuan Lan, Jianglin Wang, Ying Lu, Zhaoxuan Wang, Chunxiang Yang, Ming University of Michigan Shanghai Jiao Tong University Joint Institute Shanghai Jiao Tong University Shanghai200240 China University of Glasgow James Watt School of Engineering GlasgowG12 8QQ United Kingdom Shanghai Jiao Tong University School of Mechanical Engineering Shanghai200040 China Shanghai Intelligent and Connected Vehicle R and D Center Co. LTD Shanghai201400 China Shanghai Jiao Tong University Department of Automation Shanghai200240 China Ministry of Education of China Key Laboratory of System Control and Information Processing Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

ISBN: (纸本)9798350372601

Multi-camera vehicle tracking (MCVT) system is a key technology to build an intelligent city and intelligent transportation system. The MCVT system utilizes roadside monitoring devices and computing platforms to achieve city-level road traffic perception at a finer scale by tracking each vehicle on the road to obtain the trajectory. The existing MCVT system mainly focuses on dealing with the algorithm modules separately, without studying the real-time performance and system architecture of the entire pipeline. However, in real-world applications, many of the tricks in improving evaluation metrics are not applicable since there is endless traffic flow running all the time. Therefore, this paper proposes a real-time framework of the MCVT system to streamline all the algorithm modules with proper data flow. Firstly, a multi-threaded multi-vehicle tracking (MVT) module is developed to detect vehicles in each camera. Re-identification is implemented during MVT to provide the feature for tracking in the same camera and across different cameras. Then, after the vehicle leaves the camera field of view, the feature of vehicle trajectory is calculated by averaging the feature at each frame. Meanwhile, a background thread runs continuously to match the incoming feature of vehicle trajectory with past features by conducting a topology searching method. In the end, the vehicle trajectories with well-matched features are considered to be the same vehicle. The entire pipeline has been validated on two different datasets, the precision is 0.64 in the CityFlow dataset which uses 6 cameras simultaneously. In the customized dataset, the same method can still reach real-time when using 16 cameras at the same time with smaller network modules. © 2024 IEEE.

关键词： Vehicle locating systems

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Data-driven Model Based Online Fault Detection Using OMP-ERR 4

Data-driven Model Based Online Fault Detection Using OMP-ERR

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4th International Conference on Industrial Artificial Intelligence, IAI 2022

作者： Zhou, Guangze Luo, Zhong Zhu, Yunpeng Gao, Yi Wang, Zhiao Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China Northeastern University Key Laboratory of Vibration and Control of Aero-Propulsion Systems Ministry of Education of China Shenyang110819 China Dalian University of Technology State Key Laboratory of Structural Analysis for Industrial Equipment Dalian116024 China University of Sheffield Department of Automatic Control and System Engineering SheffieldS13JD United Kingdom

ISBN: (数字)9781665451208

ISBN: (纸本)9781665451208

Model based online fault detection often conducted by extracting features from models driven by system input and output data under various working conditions. The efficiency of online system modelling is therefore significant to improve the performance of online fault detections. In this study, a novel fast data-driven modelling approach, known as the OMP (Orthogonal Matching Pursuit)- ERR (Error Reduction Ratio) method is proposed to improve the efficiency of online fault detections. The new system identification method is motivated by noticing that the traditional OMP algorithm is much faster but usually less accurate than the OLS (Orthogonal least squares) algorithm in the identification of system NARX (Nonlinear Auto-Regressive with Exogenous inputs) models. The problem is first illustrated by the identification of a Single Degree of Freedom (SDoF) system. After that, the OMP-ERR algorithm is developed to improve the NARX modelling efficiency for the purpose of system model-based online fault detections. A case study on the crack detection of a cantilever beam shows that the new approach is over 10 times faster than the traditional OLS modelling process, demonstrating the promising applications of the new approach in online fault detections in engineering practice. © 2022 IEEE.

关键词： Least squares approximations

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Interpretable analysis of feature importance and implicit correlation based on sEMG grayscale. images

Interpretable analysis of feature importance and implicit co...

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Industrial Cyber-Physical systems (ICPS)

作者： Xiaohu AO Feng Wang Juan Zhao Jinhua She School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex System Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China School of Engineering Tokyo University of Technology Hachioji Tokyo Japan

For patients requiring upper limb rehabilitation, the hand rehabilitation robot assists the patient in completing movements within a certain training trajectory to achieve therapeutic results. There have been studies based on deep learning to convert surface electromyography (sEMG) signals into sEMG images for motion intention analysis. Although good recognition accuracy has been achieved, the working principle of neural networks and the processing of image features by the networks are not well explained. The interpretability of deep neural networks determines human confidence in neural network decisions. In this paper, we design a method based on feature importance and implicit correlation for hand motion intention recognition, experimentally explored that convolutional neural networks have implicit definitions for sEMG grayscale images of the same hand gesture action, and verified the effectiveness of the designed method.

关键词： Deep learning Analytical models Correlation Image recognition Neural networks Thumb Gray-scale

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control Analysis of Propfan Engine Based on Dual Redundancy Electro-hydrostatic Actuator

Control Analysis of Propfan Engine Based on Dual Redundancy ...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Cun Shi Qiyang Wang Jing Chen Siming Fan Xingjian Wang Shaoping Wang School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Innovation Research Institute Beihang University Ningbo China AECC Aero-Engine Control System Institute Wuxi China

With the advantages of high fault tolerance, high reliability, high dynamic response and high power-to-weight ratio, the propfan engine is one of the most promising aircraft propulsion systems. In this paper, the model and control method of controlling the thrust of the propfan engine by controlling the blade pitch angle through the dual redundant electro-hydrostatic actuator (EHA) are constructed. The variable pitch propfan engine model is constructed by physical mathematical analysis, interpolation fitting and so on. The thrust control of variable pitch engine by dual redundancy EHA is completed by two-phase current control, fuzzy control and other control methods. The reliability of the constructed model and the better response characteristics of the design control method are verified by comparing the simulation experiment with the public data set. This paper provides a reference for thrust control of variable pitch propfan engine.

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Autonomous Exploration and Mapping for Mobile Robots via Cumulative Curriculum Reinforcement Learning

arXiv

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arXiv 2023年

作者： Li, Zhi Xin, Jinghao Li, Ning Department of Automation Shanghai Jiao Tong University Shanghai200240 China Key Laboratory of System Control and Information Processing Ministry of Education of China Shanghai200240 China Shanghai Engineering Research Center of Intelligent Control and Management Shanghai200240 China

Deep reinforcement learning (DRL) has been widely applied in autonomous exploration and mapping tasks, but often struggles with the challenges of sampling efficiency, poor adaptability to unknown map sizes, and slow simulation speed. To speed up convergence, we combine curriculum learning (CL) with DRL, and first propose a Cumulative Curriculum Reinforcement Learning (CCRL) training framework to alleviate the issue of catastrophic forgetting faced by general CL. Besides, we present a novel state representation, which considers a local egocentric map and a global exploration map resized to the fixed dimension, so as to flexibly adapt to environments with various sizes and shapes. Additionally, for facilitating the fast training of DRL models, we develop a lightweight grid-based simulator, which can substantially accelerate simulation compared to popular robot simulation platforms such as Gazebo. Based on the customized simulator, comprehensive experiments have been conducted, and the results show that the CCRL framework not only mitigates the catastrophic forgetting problem, but also improves the sample efficiency and generalization of DRL models, compared to general CL as well as without a curriculum. Our code is available at https://***/BeamanLi/CCRL_Exploration. Copyright © 2023, The Authors. All rights reserved.

关键词： Reinforcement learning

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Smooth quadrotor trajectory generation for tracking a moving target in cluttered environments

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Science China(Information Sciences) 2021年第7期64卷 132-147页

作者： Lele XI Zhihong PENG Lei JIAO Ben M.CHEN School of Automation Beijing Institute of Technology State Key Laboratory of Intelligent Control and Decision of Complex System Peng Cheng Laboratory Department of Mechanical and Automation Engineering The Chinese University of Hong Kong

In this paper, we present a trajectory generation method of a quadrotor, based on the optimal smoothing B-spline, for tracking a moving target with consideration of relative tracking pattern or limited field of view of the onboard sensor in cluttered environments. Compared to existing methods, safe flying zone,vehicle physical limits, and smoothness are fully considered to guarantee flight safety, kinodynamic feasibility, and tracking performance. To tackle the cluttered environments, a parallel particle swarm optimization algorithm is applied to find the feasible waypoints that the generated trajectory should be as close to as possible, with consideration of the target's future state as well as obstacles to trade off the tracking performance and flight safety. Then, a sequential motion planning method, considering the above constraints, is applied and embedded into a cost function for solving the problem of robust tracking trajectory generation for the quadrotor via a convex optimization approach. The feasibility and effectiveness of the proposed method are verified by numerical simulations.

关键词： quadrotor target tracking trajectory generation B-spline convex optimization

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A Novel Integrated Energy Management Strategy of Energy Storage system for a Pure Electric-Driven Mining Hydraulic Excavator

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Chinese Journal of Mechanical engineering 2025年第2期 465-481页

作者： Tao Qin Yunhua Li Long Quang Yu Yao Liman Yang School of Automation Science and Electrical Engineering Beihang University Beijing Tianma Intelligent Control Technology Co. Ltd. Key Lab of Advanced Transducers and Intelligent Control System of Ministry of Education Taiyuan University of Technology

Using electric motors instead of diesel engines as the driving system for mining excavators can reduce the energy consumption and operating costs. However, pure electric-driven mining excavators are prone to unexpected power outages in mines because of drastic changes in load power, leading to significant fluctuations in the power demand of the grid, which in turn affects production. To solve the above problem, a pure electric-driven mining hydraulic excavator based on electric-motor-driven swing platform and hydraulic pumps was used as the research object. Moreover, supercapacitors and DC/DC converter, as the energy storage system(ESS) adjust the output power of the grid and recover the braking kinetic energy of the swing platform. Subsequently, a novel integrated energy management strategy for a DC bus voltage predictive controller based on the power feedforward of fuzzy rules is proposed to run mining excavators efficiently and reliably. Specifically, the working modes of the ESS are determined by the DC bus voltage and state of charge(SOC) of the supercapacitor. Next, the output power of the supercapacitor and the DC bus voltage were controlled by adjusting the charging and discharging currents of the DC/DC converter using a predictive controller and fuzzy rules. In addition, a digital prototype of the excavator was verified using an original machine test. The performance of the different strategies and driven systems were analyzed using digital prototypes. The results showed that, compared with traditional excavators with diesel engines, the operational cost of the developed excavators was reduced by 54.02%. Compared to pure electric-driven excavators without an ESS, the peak power of the grid for the developed excavators was reduced by 10%. This study designed an integrated energy management strategy for a pure electric mining excavator that can regulate the power output of the grid and maintain the stability of the bus voltage and SOC of the ESS.

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control Strategy of Multi-axis Serial Manipulator Based on Improved Active Disturbance Rejection control

Control Strategy of Multi-axis Serial Manipulator Based on I...

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第34届中国控制与决策会议

作者： Pengcheng Hu Chaochen Gu Kaijie Wu Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information ProcessingMinistry of Education of China Shanghai Engineering Research Center of Intelligent Control and Management

Aiming at the sudden change of load torque and uncertain external disturbance that multi-axis serial manipulators may face during operation,an improved Active Disturbance Rejection controller(ADRC) assisted by a Nonlinear Disturbance Observer(NLDOB) is designed and implemented in this *** realizes the estimation and compensation of known model parameter perturbation,and NLDOB is introduced to estimate and compensate the load torque and other unmodeled dynamic factors of the ***,the lumped control object model of three-bar mechanism and permanent magnet DC motor is established,and the control response curves of improved ADRC,traditional ADRC,and PID under the same conditions are compared and analyzed through *** experimental results show that compared with the traditional ADRC and PID,the improved ADRC has faster response speed,smaller overshoot and stronger robustness.

关键词： ADRC Multi-axis serial manipulator Permanent magnet DC motor NLDOB Load estimation

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