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第28届中国控制与决策会议

作者： HE Yudong WANG Junzheng KE Xianfeng WANG Shoukun Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Institute of Technology

ISBN: (纸本)9781467397155

Quadruped robot has gained its popularity due to the adaptation ability of rough *** improve the walking stability and balance of quadrupeds,separate static walking methods are discussed based on specific known *** some unknown terrains,a uniform terrain model is established in this paper.A fuzzy logic based terrain estimation method is then proposed to estimate the terrain *** on the criterion of maximum working space,a body posture and center of gravity(COG) position adjusting strategy is proposed,and a method to adjust the posture and COG position is derived based on the kinematic *** show that the proposed methods can deal with different terrains and body posture and COG position can be tuned according to the terrain.

关键词： Quadruped Robots Terrain Estimation Body Posture and COG adjustment

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Short-term wind power forecast with turning weather based on DBSCAN-RFE-LightGBM

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Renewable Energy 2025年 251卷

作者： Wu, Zhenlong Fan, Xinyu Bian, Guibin Liu, Yanhong Zhang, Xiaoke Chen, YangQuan School of Electrical and Information Engineering Zhengzhou University Zhengzhou450001 China State Key Laboratory of Intelligent Agricultural Power Equipment Zhengzhou University Luoyang471000 China State Key Laboratory of Management and Control for Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Electric Power Research Institute of State Grid Henan Electric Power Company Zhengzhou450052 China Lab Department of Mechanical Engineering School of Engineering University of California MercedCA95343 United States

At present, the wind power prediction technology is becoming more and more mature, however, the turning weather brings a decrease in prediction accuracy due to its suddenness and instability. In this paper, a wind power prediction method considering the turning period and non-turning period respectively is proposed to weaken the adverse effects caused by turning weather. Firstly, the prediction effects of multiple models are compared, density-based spatial clustering of applications with noise (DBSCAN) is selected as the outlier processing method, recursive feature elimination (RFE) is used as the feature selection method, and Light gradient boosting machine (LightGBM) is used for prediction. The combined prediction method based on DBSCAN-RFE-LightGBM can reduce the influence of abnormal data and redundant features and improve the prediction effect. Then, the sliding window is set to detect the turning period. Considering that the turning weather is an emergency and does not happen frequently, the amount of data is small, which leads to the inability to train the model well. Generative adversarial networks (GAN) are applied to expand the turning period data. The LightGBM is trained and predicted by using the expended turning period data. Finally, the time-division prediction results are merged. Using the data collected from wind farms for short-term power prediction experiments, the time-segment prediction method proposed in this paper with GAN reduces MAE by 1.913 and RMSE by 3.351 on a single unit compared with the non-differentiated period. © 2025 Elsevier Ltd

关键词： Merging

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Path Planning for Distribution Network Robots with Adaptive Simulated Annealing-Enhanced Artificial Potential Field Method

Path Planning for Distribution Network Robots with Adaptive ...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Baichao Zhang Xin Chen Jinge Chen Jinbin Li Xiaokai Wang Xu Jian School of Automation China University of Geosciences Wuhan China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China State Grid Hubei Electric Power Co. Ltd. Electric Power Science Research Institute Wuhan P. R. China Hubei Fangyuan Dongli Electric Power Science Research Co. Ltd Wuhan P. R. China

ISBN: (数字)9798331521950

ISBN: (纸本)9798331521967

In this paper, we propose a hybrid algorithm that combines an improved Artificial Potential Field (APF) method with the Simulated Annealing (SA) algorithm for path planning of an electric power operation robot manipulator in complex distribution grid environments. To address the unreachable target issue inherent in traditional APF, we introduce a distance regulation factor to optimize the repulsive function. This modification allows the manipulator to smoothly approach the target point as it nears, while the repulsion from obstacles gradually decreases. Additionally, to overcome the limitations of the traditional SA algorithm, such as its tendency to get trapped in local minimum solutions and its inefficiency in complex environments, we propose an adaptive temperature rise strategy. This strategy increases the temperature, enhancing the probability of escaping local optimal solutions. When the APF algorithm becomes trapped in a local optimum, the improved SA algorithm is applied to escape the local minimum. Once the local optimum is avoided, the algorithm switches back to APF to continue the path planning process. Simulation results demonstrate that the proposed improved APF-SA algorithm adapts effectively to various complex environments, achieving shorter planning times and higher success rates compared to traditional APF and SA algorithms. It successfully resolves the unreachable target and local minimum problems associated with APF. Finally, the feasibility of the proposed APF-SA fusion algorithm is validated through experiments conducted on an electric power operation robot experimental platform for distribution grid applications.

关键词： Electric potential Adaptation models Force Distribution networks Simulated annealing Manipulators Path planning Planning Collision avoidance Robots

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Adaptive Fixed-Time Synchronization of Delayed Memristor-Based Neural Networks with Discontinuous Activations

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Computer Modeling in Engineering & Sciences 2023年第1期134卷 221-239页

作者： Tianyuan Jia Xiangyong Chen Xiurong Yao Feng Zhao Jianlong Qiu School of Automation and Electrical Engineering and Key Laboratory of Complex Systems and Intelligent Computing in Universities of ShandongLinyi UniversityLinyi276005China The Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems and School of AutomationChina University of GeosciencesWuhan430074China

Fixed-time synchronization(FTS)of delayed memristor-based neural networks(MNNs)with discontinuous activations is studied in this *** continuous and discontinuous activations are considered *** the mixed delays which are closer to reality are taken into the ***,two kinds of control schemes are proposed,including feedback and adaptive control *** on some lemmas,mathematical inequalities and the designed controllers,a few synchronization criteria are ***,the upper bound of settling time(ST)which is independent of the initial values is ***,the feasibility of our theory is attested by simulation examples.

关键词： Memristor-based neural networks fixed-time synchronization mixed delays discontinuous activations adaptive control

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Construction of Multilayer Porous Scaffold Based on Magnetically Guided Assembly of Microfiber

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Journal of systems Science & complexity 2018年第3期31卷 581-595页

作者： LI Xingfu WANG Huaping SHI Qing SUN Tao HUANG Qiang FUKUDA Toshio Intelligent Robotics Institute School of Mechatronical Engineering Beijing Institute of Technology Beijing 100081 China Key Laboratory of Biomimetic Robots and Systems Ministry of Education Beijing 100816 China Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing 100081 China

This paper proposes a novel method of magnetically guided assembly to construct multi- layer porous scaffold for three-dimensional cell culture by apply magnetic microfibers. Microfibers are composed of biocompatible and biodegradable alginate solution with homogeneous magnetic nanopar- ticles, which are continuously spun from a microfluidic device by precise pressure control of the syringe pump. Magnetic nanoparticles enable the control of magnetic field on microfibers. Meanwhile, mag- netized device combining with a round permanent magnet are utilized to guide the distribution of spouted microfibers. The device is composed by pure iron wire arrays and wax, which stimulates pow- erful magnetic flux density and magnetic field gradients for the capture and assembly of microfibers. Thus, magnetic microfibers are spun on desired places of the magnetized device by motion control of the micromanipulation robot, and precise locations are adjusted by magnetic force couple with the assist of glass micropipette. Afterwards, microfibers are spatially organized by periodic magnetic force and crossed layer-by-layer to form micro-pore structure with both length and width of 650μm. Finally, the authors construct a multilayer microfiber-based scaffold with high porosity to provide a satisfactory environment for long-term cell culture. The experimental results demonstrate the effectiveness of the proposed method.

关键词： Magnetically guided assembly magnetic microfiber magnetized device periodic magneticforce multilayer porous scaffold.

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Distributed multiple model filtering for markov jump systems with communication delays

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Journal of the Franklin Institute 2023年第4期360卷 3407-3435页

作者： Li, Hui Yan, Liping Xia, Yuanqing Zhang, Jinhui the Key Laboratory of Intelligent Control Decision of Complex Systems School of Automation Beijing Institute of Technology Beijing100081 China

In this paper, we study a distributed state estimation problem for Markov jump systems (MJS) over sensor networks, in which each sensor node connects with each other through wireless networks with communication delays. We assume that each sensor node maintains a buffer to store delayed data transmitted from neighbor nodes. A distributed multiple model filter is designed by using the interacting multiple model methods (IMM) and a recursive delays compensation method. In order to ensure the stability, two stability conditions are derived for boundedness of estimation errors and boundedness of error covariance. Finally, the effectiveness of the proposed methods is illustrated by simulations and experiments of maneuvering target tracking. © 2022 The Franklin Institute

关键词： Sensor nodes

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Preface——Special Issue to Celebrate the 30th Anniversary of Journal of systems Science and complexity

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Journal of systems Science & complexity 2017年第1期30卷 1-3页

作者： GAO Xiao-Shan CHEN Jie SHAO Jun WANG Shouyang Academy of Mathematics and Systems Science Chinese Academy of Sciences Key Laboratory of Intelligent Control and Design of Complex Systems Beijing Institute of Technology Department of Statistics University of Wisconsin-Madison

This special issue is dedicated to the 30th anniversary of Journal of systems Science and complexity(JSSC)which is under the auspices of the Institute of systems Science,Chinese Academy of *** of systems Science,Chinese Academy of Sciences was established in 1979 by scientists Chao-Chih Kwan,Wen-Tsun Wu,Guo-Zhi *** 1981,the Journal of systems

关键词：系统科学复杂性杂志中国科学院序言科学研究所

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An Overview of Distributed High-order Multi-agent Coordination

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 1-9页

作者： Jie Huang Hao Fang Lihua Dou Jie Chen the School of Automation Beijing Institute of Technology Key Laboratory of Intelligent Control and Decision of Complex Systems the Fujian Institute of Education

Research on multi-agent systems has attracted much attention in the past two decades, and numerous results have been obtained. Its widespread applications include spacecraft,mobile robots, sensor networks, etc. Most previous research works on multi-agent systems studied the first- and second-order dynamics. However, in engineering, many systems are modeled by higher-order dynamics. This paper reviews the major results and progress in distributed high-order multi-agent *** the review, a short discussion section is included to summarize the existing research and propose several promising research directions along with some open problems that are deemed important for further investigations.

关键词： Multi-agent systems Protocols Linear systems Nonlinear systems Heuristic algorithms Laplace equations

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ON THE ADAPTIVE FUZZY STABILIZATION OF UNKNOWN NONLINEAR systems

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control AND intelligent systems 2007年第4期35卷 337-350页

作者： Halima, D. B. Chtourou, M. Intelligent Control Optimization and Design of Complex Systems (ICOS) Department of Electrical Engineering National School of Engineers of Sfax ENIS P.B.W. 3038 Sfax Tunisia

In this work, we present a state feedback adaptive fuzzy control method, applied to the stabilization of a nonlinear system whose mathematical model is unknown or/and with varying time parameters. The synthesis of the control law is based on fuzzy models developed by a local description of the considered system's dynamics. Therefore, two steps, at each time, are necessary to the adaptive control of such system. The first one consists in estimating every local model parameters, using a gradient method as parameter's adjustment method. The second one consists in the computation, of the control law based on the classical methods applied for the linear system control as the state feedback control. The stability of the proposed adaptive control method is discussed.

关键词： Fuzzy dynamic system adaptive fuzzy control state feedback control gradient method stability analysis

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Simplified outlier detection for improving the robustness of a fuzzy model

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Science China(Information Sciences) 2020年第4期63卷 218-220页

作者： Yali JIN Weihua CAO Min WU Yan YUAN School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems China University of Geosciences

Dear editor,Fuzzy models have been widely employed in various fields, such as complex industrial process modeling, classification, function approximation, and time series prediction. Extracting fuzzy rules is very important as they determine the capabilities of the fuzzy model. In recent years, data-based methods such as fuzzy clustering, genetic algorithm, and neural networks [1–3], have been pro-

关键词： Simplified outlier detection for improving the robustness of a fuzzy model Gaussian

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