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Kernel-Based State-Space Kriging for Predictive Control

IEEE/CAA Journal of Automatica Sinica 2023年第5期10卷 1263-1275页

作者： A.Daniel Carnerero Daniel R.Ramirez Daniel Limon Teodoro Alamo the Department of System Engineering and Automation University of SevilleSevilla 41020Spain the School of Engineering Tokyo Institute of TechnologyTokyo 152-8552Japan Department of System Engineering and Automation University of SevilleSevilla 41020Spain

In this paper, we extend the state-space kriging(SSK) modeling technique presented in a previous work by the authors in order to consider non-autonomous systems. SSK is a data-driven method that computes predictions as linear combinations of past outputs. To model the nonlinear dynamics of the system, we propose the kernel-based state-space kriging(K-SSK), a new version of the SSK where kernel functions are used instead of resorting to considerations about the locality of the data. Also, a Kalman filter can be used to improve the predictions at each time step in the case of noisy measurements. A constrained tracking nonlinear model predictive control(NMPC) scheme using the black-box input-output model obtained by means of the K-SSK prediction method is proposed. Finally, a simulation example and a real experiment are provided in order to assess the performance of the proposed controller.

关键词： Data-driven methods model identification Kernel methods predictive control

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A novel stiffness optimization model of space telescopic boom based on locking mechanism

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Frontiers of Mechanical engineering 2024年第3期19卷 41-59页

作者： Kun XU Xinghan ZHUANG Zhou SU Qiuhong LIN Shouzhi REN Hang XIAO Xilun DING School of Mechanical Engineering and Automation Beihang UniversityBeijing 100191China Beijing Institute of Spacecraft System Engineering Beijing 100094China

The deployable telescopic boom,whose mass and stiffness play crucial roles,is extensively used in the design of space-deployable ***,the most existing optimal design that neglects the influence of the locking mechanisms in boom joints cannot raise the whole stiffness while reducing the boom *** tackle this challenge,a novel optimization model,which utilizes the arrangement of the locking mechanisms to achieve synchronous improvement of the stiffness and mass,is *** proposed optimization model incorporates a novel joint stiffness model developed based on an equivalent parallel mechanism that enables the consideration of multiple internal stiffness factors of the locking mechanisms and tubes,resulting in more accurate representations of the joint stiffness *** analysis shows that the proposed stiffness model achieves more than at least 11% improved accuracy compared with existing ***,case verification shows that the proposed optimization model can improve stiffness while effectively reducing mass,and it is applied in boom optimization design.

关键词： deployable telescopic boom locking mechanism stiffness model clearance error optimization model

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Parallel system Based Quantitative Assessment and Self-evolution for Artificial Intelligence of Active Power Corrective Control

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CSEE Journal of Power and Energy systems 2024年第1期10卷 13-28页

作者： Tianyun Zhang Jun Zhang Feiyue Wang Peidong Xu Tianlu Gao Haoran Zhang Ruiqi Si School of Electrical Engineering and Automation Wuhan UniversityWuhan 430072HubeiChina State Key Laboratory for Management and Control of Complex System Institute of AutomationChinese Academy of SciencesBeijing 100190China

In artificial intelligence(AI)based-complex power system management and control technology,one of the urgent tasks is to evaluate AI intelligence and invent a way of autonomous intelligence ***,there is,currently,nearly no standard technical framework for objective and quantitative intelligence *** this article,based on a parallel system framework,a method is established to objectively and quantitatively assess the intelligence level of an AI agent for active power corrective control of modern power systems,by resorting to human intelligence evaluation *** this basis,this article puts forward an AI self-evolution method based on intelligence assessment through embedding a quantitative intelligence assessment method into automated reinforcement learning(AutoRL)systems.A parallel system based quantitative assessment and self-evolution(PLASE)system for power grid corrective control AI is thereby constructed,taking Bayesian Optimization as the measure of AI evolution to fulfill autonomous evolution of AI under guidance of their intelligence assessment *** results exemplified in the power grid corrective control AI agent show the PLASE system can reliably and quantitatively assess the intelligence level of the power grid corrective control agent,and it could promote evolution of the power grid corrective control agent under guidance of intelligence assessment results,effectively,as well as intuitively improving its intelligence level through selfevolution.

关键词： AI quantitative intelligence assessment and self-evolution automated reinforcement learning Bayesian optimization corrective control parallel system

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Controllability of heterogeneous networked sampled-data systems

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Science China(Information Sciences) 2025年第3期68卷 302-318页

作者： Zixuan YANG Lin WANG Xiaofan WANG Guanrong CHEN Department of Automation Shanghai Jiao Tong University Key Laboratory of System Control and Information Processing Ministry of Education of China School of Mechatronic Engineering and Automation Shanghai University School of Electrical and Electronic Engineering Shanghai Institute of Technology Department of Electrical Engineering City University of Hong Kong

This study investigates the controllability of a general heterogeneous networked sampled-data system(HNSS) consisting of nonidentical node systems, where the inner coupling between any pair of nodes can be described by a unique *** signals on control and transmission channels are sampled and held by zero-order holders, and the control sampling period of each node can be different. Necessary and sufficient controllability conditions are developed for the general HNSS, using the Smith normal form and matrix equations, respectively. The HNSS in specific topology or dynamic settings is discussed subsequently with easier-to-verify conditions derived. These heterogeneous factors have been determined to independently or jointly affect the controllability of networked sampled-data systems. Notably, heterogeneous sampling periods have the potential to enhance the overall controllability, but not for systems with some special dynamics. When the node dynamics are heterogeneous,the overall system can be controllable even if it is topologically uncontrollable. In addition, in several typical heterogeneous sampled-data multi-agent systems, pathological sampling of single-node systems will necessarily cause overall uncontrollability.

关键词： network controllability sampled-data system heterogeneous system inner coupling multi-agent system

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Study on plasma expansion model of primary discharge on spacecraft solar array

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Plasma Science and Technology 2024年第11期26卷 87-95页

作者： Dejie WEI Jianwen WU Liying ZHU School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191People’s Republic of China Institute of Spacecraft System Engineering CAST Beijing 100094People’s Republic of China

In the space plasma environment, primary discharge may occur on the solar array and evolve into a destructive sustained arc, which threatens the safe operation of the spacecraft. Based on the plasma expansion fluid theory, a new multicomponent plasma expansion model is proposed in this study, which takes into account the effects of ion species, ion number, initial discharge current, and Low Earth Orbit(LEO) plasma environment. The expansion simulation of single-component and multicomponent ions is carried out respectively, and the variations of plasma number density, expansion distance, and speed during the expansion process are *** with the experimental results, the evolution of propagation distance and speed is closed and the error is within a reasonable range, which verifies the validity and rationality of the model. The propagation characteristics of the primary discharge on the solar array surface and the influence of the initial value on the maximum propagation distance and the propagation current peaks are investigated. This study can provide important theoretical support for the propagation and evolution of the primary discharge and the key behavior of the transition to secondary discharge on spacecraft solar array.

关键词： primary discharge plasma expansion propagation characteristics spacecraft solar array

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Spiking Reinforcement Learning Enhanced by Bioinspired Event Source of Multi-dendrite Spiking Neuron and Dynamic Thresholds

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IEEE/CAA Journal of Automatica Sinica 2025年第3期12卷 618-629页

作者： Xingyue Liang Qiaoyun Wu Yun Zhou Chunyu Tan Hongfu Yin Changyin Sun the School of Artificial Intelligence Anhui University Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education IEEE the Institute of Artificial Intelligence Hefei Comprehensive National Science Center the School of Automation Southeast University the Engineering Research Center of Autonomous Unmanned System Technology Ministry of Education

Deep reinforcement learning(DRL) achieves success through the representational capabilities of deep neural networks(DNNs). Compared to DNNs, spiking neural networks(SNNs),known for their binary spike information processing, exhibit more biological characteristics. However, the challenge of using SNNs to simulate more biologically characteristic neuronal dynamics to optimize decision-making tasks remains, directly related to the information integration and transmission in *** by the advanced computational power of dendrites in biological neurons, we propose a multi-dendrite spiking neuron(MDSN) model based on Multi-compartment spiking neurons(MCN), expanding dendrite types from two to multiple and deriving the analytical solution of somatic membrane *** apply the MDSN to deep distributional reinforcement learning to enhance its performance in executing complex decisionmaking tasks. The proposed model can effectively and adaptively integrate and transmit meaningful information from different sources. Our model uses a bioinspired event-enhanced dendrite structure to emphasize features. Meanwhile, by utilizing dynamic membrane potential thresholds, it adaptively maintains the homeostasis of MDSN. Extensive experiments on Atari games show that the proposed model outperforms some state-of-the-art spiking distributional RL models by a significant margin.

关键词： Deep reinforcement learning multi-compartment spiking neurons spiking neural network

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Interference Suppression and Jitter Elimination Ability-Based Adaption Tracking Guidance for Robotic Fishes

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IEEE/CAA Journal of Automatica Sinica 2025年第1期12卷 126-137页

作者： Dongfang Li Jie Huang Rob Law Xin Xu Limin Zhu Edmond Q.Wu IEEE the School of Electrical Engineering and Automation Fuzhou University the Key Laboratory of System Control and Information Processing Ministry of Education the School of Electrical Engineering and Automation Fuzhou University 5G+Industrial Internet Institute Fuzhou University the University of Macau the College of Mechatronics and Automation National University of Defense Technology the School of Mechanical Engineering Shanghai Jiao Tong University the Department of Computer Science and Engineering Shanghai Jiao Tong University

This work presents an adaptive tracking guidance method for robotic fishes. The scheme enables robots to suppress external interference and eliminate motion jitter. An adaptive integral surge line-of-sight guidance rule is designed to eliminate dynamics interference and sideslip issues. Limited-time yaw and surge speed observers are reported to fit disturbance variables in the model. The approximation values can compensate for the system's control input and improve the robots' tracking ***, this work develops a terminal sliding mode controller and third-order differential processor to determine the rotational torque and reduce the robots' run jitter. Then, Lyapunov's theory proves the uniform ultimate boundedness of the proposed method. Simulation and physical experiments confirm that the technology improves the tracking error convergence speed and stability of robotic fishes.

关键词： Adaptive integral surge line-of-sight approximation robotic fish speed observer

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Development of a cable-driven redundant space manipulator with large bending angle by combining quaternion joints and segmented coupled linkages mechanism

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Chinese Journal of Aeronautics 2023年第11期36卷 483-499页

作者： Taiwei YANG Jian HUANG Wenfu XU Ke SHAO Bin LIANG School of Mechanical Engineering and Automation Harbin Institute of TechnologyShenzhen 518055China State Key Laboratory of Robotics and System Harbin Institute of TechnologyHarbin 150001China Department of Automation Tsinghua UniversityBeijing 100854China

A cable-driven redundant manipulator has significant potential in confined space applications, such as environmental exploration, equipment monitoring, or maintenance. A traditional design requires 3N driving motors/cables to supply 2N degrees of freedom(DOF) movement *** number of motors is 1.5 times that of the joints’ DOF, increasing the hardware cost and the complexity of the kinematics, dynamics, and control. This study develops a novel redundant space manipulator with decoupled cable-driven joints and segmented linkages. It is a 1680 mm continuum manipulator with eight DOF, consisting of four segmented linkages driven by eight motors/pairs of cables. Each segment has two equivalent DOF, which are realized by four quaternion joints synchronously driven by two linkage cables. The linkage cables of adjacent joints are symmetrically decoupled and offset at 180°. This design allows equal-angle movement of all the joints of each segment. Moreover, each decoupling driving mechanism is designed based on a pulley block composed of two fixed and movable pulleys. The two movable pulleys realize the opposite but equidistant motions of the two driving cables, i.e., pulling and loosening, assuring symmetrical movements of the two driving cables of each segment. Consequently, the equivalent 2N-DOF joints are driven only by 2N motors, significantly reducing the hardware cost and simplifying the mapping relationship between the motor angle/cable length and the joint angle. Furthermore, the bending range of each segment could reach 360°, which is three times that of a traditional design. Finally, a prototype has been developed and experimented with to verify the performance of the proposed mechanism and the corresponding algorithms.

关键词： Cable-driven Mechanism design Redundant manipulators Segmented linkages Kinematics

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Physical Mechanism Enabled Neural Network for Power system Dynamic Security Assessment

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CSEE Journal of Power and Energy systems 2024年第6期10卷 2296-2307页

作者： Guozheng Wang Jianbo Guo Shicong Ma Kui Luo Xi Zhang Qinglai Guo Shixiong Fan Tiezhu Wang Weilin Hou Department of Power System China Electric Power Research InstituteBeijing 100192China School of Automation Beijing Institute of TechnologyBeijing 100081China Department of Electrical Engineering Tsinghua UniversityBeijing 100084China

Data-driven artificial intelligence technologies have emerged as increasingly fascinating tools for assessing power system ***,their inherent mechanism of inexplicability and unreliability now limits their scalability in power *** address this problem,this paper proposes a neural network design method empowered by physical mechanisms for power system security *** incorporates geometric characteristics of dynamic security regions into the network training process and constructs connections between network structure and system's unstable mode,which can perform security assessment with a neural network efficiently while ensuring physical ***,a credibility evaluation mechanism is established to ensure credibility of neural network predictions and reduce ***,effectiveness of the proposed method is verified on test *** and considerations in building a neural network with interpretable structures and credible predictions can provide a reference for machine intelligence applied in other industrial systems.

关键词： Credibility index machine intelligence neural network structure physical properties power system security assessment

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Research on Digital Twin system Platform Framework and Key Technologies of Unmanned Ground Equipment

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Complex system Modeling and Simulation 2024年第2期4卷 109-123页

作者： Kunyu Wang Lin Zhang Cheng Xu Han Lu Zhen Chen Hongbo Cheng Rui Guo the School of Automation Science and Electrical Engineering Beihang UniversityBeijing 100191China the State Key Laboratory of Intelligent Manufacturing System Technology Beijing 100854China the Beijing Institute of Electronic System Engineering Beijing 100854China

As an emerging technology,digital twin is expected to bring novel application modes to the whole life cycle process of unmanned ground equipment,including research and development,design,control optimization,operation and maintenance,*** highly dynamic,complex,and uncertain characteristics of unmanned ground equipment and the battlefield environment also pose new challenges for digital twin *** from the new challenges faced by the digital twin of unmanned ground equipment,this paper designs a service-oriented cloud-edge-end collaborative platform architecture of the digital twin system of unmanned ground equipment,and further analyzes several key technologies supporting the implementation of the platform architecture.

关键词： unmanned ground equipment digital twin native cloud platform Modeling and Simulation(M&S) artificial intelligence

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