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2nd International Conference on Algorithm, Image Processing and Machine Vision, AIPMV 2024

作者： Zhang, Jiahao Wei, Zongshou Lanzhou Jiaotong University Gansu Key Laboratory of Plateau Traffic Information Engineering and Control Key Laboratory of Optoelectronic Technology and Intelligent Control of Ministry of Education Lanzhou730070 China

ISBN: (纸本)9798350390254

The purpose of fusing infrared and visible photos is to provide high-quality combined images with clear objects and detailed textures, even in very dark environments. The visual quality and contrast of both infrared and visible images tend to suffer in low-light situations. Previous algorithms fused poor- quality source images directly, resulting in fused images that still had low contrast and lost detail information. Thus, in this paper, we first design a multi-level brightness adjustment unit to learn visible light illumination components layer by layer and perform luminance enhancement while fusing multi-source image information. Second, to enhance the network's capacity for feature extraction, we developed the parallel attention module. This module was inserted after each brightness adjustment module. Extensive trials show that our technique works better than nine common fusion methods when compared visually and using objective measures. © 2024 IEEE.

关键词： Image fusion

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Adaptive Optimal Output Regulation of Interconnected Singularly Perturbed Systems With Application to Power Systems

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IEEE/CAA Journal of Automatica Sinica 2024年第3期11卷 595-607页

作者： Jianguo Zhao Chunyu Yang Weinan Gao Linna Zhou Xiaomin Liu the Engineering Research Center of Intelligent Control for Underground Space Ministry of EducationChina University of Mining and TechnologyXuzhou 221116 the School of Information and Control Engineering China University of Mining and TechnologyXuzhou 221116 IEEE the State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyang 110819China

This article studies the adaptive optimal output regulation problem for a class of interconnected singularly perturbed systems(SPSs) with unknown dynamics based on reinforcement learning(RL).Taking into account the slow and fast characteristics among system states,the interconnected SPS is decomposed into the slow time-scale dynamics and the fast timescale dynamics through singular perturbation *** the fast time-scale dynamics with interconnections,we devise a decentralized optimal control strategy by selecting appropriate weight matrices in the cost *** the slow time-scale dynamics with unknown system parameters,an off-policy RL algorithm with convergence guarantee is given to learn the optimal control strategy in terms of measurement *** combining the slow and fast controllers,we establish the composite decentralized adaptive optimal output regulator,and rigorously analyze the stability and optimality of the closed-loop *** proposed decomposition design not only bypasses the numerical stiffness but also alleviates the *** efficacy of the proposed methodology is validated by a load-frequency control application of a two-area power system.

关键词： Adaptive optimal control decentralized control output regulation reinforcement learning(RL) singularly perturbed systems(SPSs)

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An Attitude Sliding Mode control Method for In-Orbit Fuel Filling Combination of SAR Satellite 4

An Attitude Sliding Mode Control Method for In-Orbit Fuel Fi...

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4th China International SAR Symposium, CISS 2023

作者： Hu, Wenkun Chen, Xiumei Pei, Jiarui Guo, Siyan Zhong, Jinfeng Shanghai Aerospace Control Technology Institute Shanghai Key Laboratory of Aerospace Intelligent Control Technology Shanghai China

ISBN: (纸本)9798350307955

In-orbit fuel refueling is a necessary measure to extend the lifespan of in-orbit SAR satellite. During the refueling period in orbit, the high precision, high stability, and rapid maneuverability of the attitude control of the combination of SAR satellite and refueling satellites are prerequisites for the smooth completion of the refueling mission in orbit and imaging mission during refueling. This article will study the attitude control problem of the combination of SAR satellite during refueling in orbit. Firstly, establish a time-varying center of mass and time-varying inertia matrix model for the combination during fuel refueling in orbit;Then the quaternion is used to describe the dynamic and kinematics equations of the combination;Finally, taking into account the attitude angle and velocity of the combination, an attitude sliding mode controller is designed to achieve high precision, high stability, and fast maneuvering attitude control of the combination during the refueling period of the SAR satellite in orbit. © 2023 IEEE.

关键词： Attitude control

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Managing Battery Performance Degradation Using Physics-Informed Learning Scheme for Multiple Health Indicators

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IEEE Transactions on Transportation Electrification 2025年第3期11卷 7309-7321页

作者： Qin, Linxiao Sun, Tao Sun, Xi-Ming Xia, Weiguo Dalian University of Technology Key Laboratory of Intelligent Control and Optimization for Industrial Equipment of Ministry of Education Dalian116024 China Dalian University of Technology School of Control Science and Engineering Dalian116024 China Tsinghua University Department of Automation Beijing100084 China

To address the challenges in battery health management, this paper introduces a physics-informed neural network predictor-estimator scheme. In the framework, the predictor forecasts health degradation, setting benchmarks for the estimator, while the estimator provides calibrations for the predictor as substitution to infeasible measurement techniques. For the predictor design, a linear-exponential model is employed for two-stage degradation prediction, enabling online parameter updates and knee point detection. For the estimator design, three neural networks embedded with Coulomb counting and equivalent circuits are proposed to estimate state of charge, internal resistance, and capacity, respectively. Experimental results on the A123 dataset demonstrate superior accuracy of our scheme, with a maximum R-squared improvement of 22.8% in prediction tasks and 11.5% in estimation tasks, while maintaining lightweight network structures with fewer than 1000 floating point operations and 200 parameters. © 2015 IEEE.

关键词： Electronic health record

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Trajectory tracking control of autonomous heavy-duty mining dump trucks with uncertain dynamic characteristics

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Science China(Information Sciences) 2023年第10期66卷 246-262页

作者： Liang CHEN Zhaobo QIN Manjiang HU Hongbo GAO Yougang BIAN Biao XU Xiaoyan PENG State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body Hunan University Wuxi Intelligent Control Research Institute of Hunan University Department of Automation University of Science and Technology of China

The proportion of mines using autonomous mining trucks is still very low at present. To promote the development of intelligent mining, it is urgent to proceed with the drive-by-wire modification to common mining trucks and design a motion control algorithm considering uncertain dynamic *** paper proposes a trajectory tracking control method for autonomous heavy-duty mining dump trucks(AHMDTs) with uncertain dynamic characteristics. In this method, a driving/braking force compensation algorithm based on an inverse dynamic model is designed to guarantee accurate longitudinal control with less control gain tuning. Using road curvatures, a modified rear-wheel position feedback control method is proposed to deal with reverse-path tracking, which can simultaneously reduce the lateral error and yaw angle error. A modified Stanley controller considering the collaborative preview based on speed and curvature is constructed to achieve accurate path tracking in the forward gear. Moreover, the proposed method focuses on the practice of trajectory tracking control in an open-pit mine condition with the adverse effects caused by uncertain vehicle dynamics, huge variable load, and large actuator lag. Real vehicle tests show that the proposed methodology can control AHMDTs with a low tracking error.

关键词： vehicle control trajectory tracking control driving/braking force compensation rear-wheel position feedback

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Data-Driven control of Distributed Event-Triggered Network Systems

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 351-364页

作者： Xin Wang Jian Sun Gang Wang Frank Allgower Jie Chen the National Key Laboratory of Autonomous Intelligent Unmanned Systems School of AutomationBeijing Institute of TechnologyBeijing 100081 the Beijing Institute of Technology Chongqing Innovation Center Chongqing 401120China IEEE the Institute for Systems Theory and Automatic Control University of StuttgartStuttgart 70550Germany the Department of Control Science and Engineering Tongji UniversityShanghai 201804 the National Key Laboratory of Autonomous Intelligent Unmanned Systems Beijing Institute of TechnologyBeijing 100081China

The present paper deals with data-driven event-triggered control of a class of unknown discrete-time interconnected systems(*** systems).To this end,we start by putting forth a novel distributed event-triggering transmission strategy based on periodic sampling,under which a model-based stability criterion for the closed-loop network system is derived,by leveraging a discrete-time looped-functional *** the model-based criterion with a data-driven system representation recently developed in the literature,a purely data-driven stability criterion expressed in the form of linear matrix inequalities(LMIs)is ***,the data-driven stability criterion suggests a means for co-designing the event-triggering coefficient matrix and the feedback control gain matrix using only some offline collected state-input ***,numerical results corroborate the efficacy of the proposed distributed data-driven event-triggered network system(ETS)in cutting off data transmissions and the co-design procedure.

关键词： Data-driven control distributed event-triggered network system(ETS) linear matrix inequalitie(LMI) looped-functional stability

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Distributed Event-Triggered Formation control of USVs with Prescribed Performance

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Journal of Systems Science & Complexity 2022年第3期35卷 820-838页

作者： CHEN Guangdeng YAO Deyin ZHOU Qi LI Hongyi LU Renquan School of Automation and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of TechnologyGuangzhou 510006China

In this paper,the formation control problem is investigated for a team of uncertain underactuated surface vessels(USVs)based on a directed *** the risk of collision and the limited communication range of USVs,the prescribed performance control(PPC)methodology is employed to ensure collision avoidance and connectivity *** event-triggered mechanism is designed to reasonably use the limited communication ***,neural networks(NNs)and an auxiliary variable are constructed to deal with the problems of uncertain nonlinearities and underactuation,***,an event-triggered formation control scheme is proposed to ensure that all signals of the closed-loop system are uniformly ultimately bounded(UUB).Finally,simulation results are presented to demonstrate the effectiveness of the proposed control scheme.

关键词： Event-triggered control formation control prescribed performance underactuated surface vessels(USVs)

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Lateral control of Vehicle Platoons Under External Disturbance and Parameter Uncertainty: An Adaptive DMPC Approach

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IEEE Transactions on Vehicular technology 2024年第5期74卷 7444-7457页

作者： Li, Panshuo Weng, Zhixiang Lin, Kunsong Zhao, Jing Guangdong University of Technology Guangdong Provincial Key Laboratory of Intelligent Decision and Cooperative Control Guangzhou510006 China Guangdong University of Technology Guangdong-Hong Kong Joint Laboratory for Intelligent Decision and Cooperative Control Guangzhou510006 China Guangdong University of Technology School of Automation Guangzhou510006 China Northeastern University School of Mechanical Engineering and Automation Shenyang110819 China

This paper proposes an estimator-based distributed model predictive control (DMPC) approach for vehicle platoons in the presence of external disturbance and uncertain cornering stiffness. A lateral dynamics model of vehicle platoons is established by utilizing a path-based vehicle-following strategy. An adaptive parameter estimator is then proposed to estimate the cornering stiffness. Based on it, a distributed disturbance-feedback min-max model predictive controller is developed to ensure the lateral disturbance string stability of vehicle platoons, enhance path-following performance and lateral stability of following vehicles, and simultaneously prevent the actuator saturation. Considering the high computational burden involved in solving min-max optimization, the linear matrix inequalities-based conditions are derived to facilitate the controller gain solving. The proposed method can effectively tackle the cornering stiffness within large uncertain intervals and guarantee the lateral string stability of platoons under external disturbances. Simulation results validate the effectiveness of the proposed DMPC approach in different scenarios. © 1967-2012 IEEE.

关键词： Linear matrix inequalities

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Human-in-the-Loop Consensus control for Nonlinear Multi-Agent Systems With Actuator Faults

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IEEE/CAA Journal of Automatica Sinica 2022年第1期9卷 111-122页

作者： Guohuai Lin Hongyi Li Hui Ma Deyin Yao Renquan Lu School of Automation and Guangdong Province Key Laboratory of Intelligent Decision and Cooperative Control Guangdong University of TechnologyGuangzhou 510006China

This paper considers the human-in-the-loop leader-following consensus control problem of multi-agent systems(MASs)with unknown matched nonlinear functions and actuator *** is assumed that a human operator controls the MASs via sending the command signal to a non-autonomous leader which generates the desired ***,the leader’s input is nonzero and not available to all *** using neural networks and fault estimators to approximate unknown nonlinear dynamics and identify the actuator faults,respectively,the neighborhood observer-based neural fault-tolerant controller with dynamic coupling gains is *** is proved that the state of each follower can synchronize with the leader’s state under a directed graph and all signals in the closed-loop system are guaranteed to be cooperatively uniformly ultimately ***,simulation results are presented for verifying the effectiveness of the proposed control method.

关键词： Actuator faults distributed control human-in-the-loop neighborhood observer nonlinear multi-agent systems(MASs)

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controllability of neighborhood Corona product networks

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Science China(Information Sciences) 2024年第12期67卷 327-328页

作者： Bo LIU Xuan LI Qiang ZHANG Junjie HUANG Housheng SU Ministry of Education Key Laboratory for Intelligent Analysis and Security Governance of Ethnic Languages School of Information Engineering Minzu University of China School of Mathematical Sciences Inner Mongolia University Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China School of Artificial Intelligence and Automation Huazhong University of Science and Technology

controlling networks aims to study the models, structures,and related dynamics of complex networks. The primary problem of controlling networks is to determine whether they are controllable. Nowadays, controllability has been widely studied and applied to system engineering and control theory, power systems, aerospace, and quantum systems. Various classical criteria include the Gram matrix criterion, Kalman rank criterion, and PBH test.

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