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第41届中国控制会议

作者： Yaru Yu Rongni Yang Dewei Li The Department of Automation Shanghai Jiao Tong University The School of Control Science and Engineering Shandong University

ISBN: (数字)9789887581536

ISBN: (纸本)9781665482561

In this paper,the sliding mode control problem for Markovian jump systems(MJS s) subject to parameter uncertainties and disturbances is solved via an event-triggered ***,a sliding mode surface is constructed,and then sufficient conditions are given to ensure the stochastic stability of the resultant Markov jump sliding mode ***,the system trajectories of the considered MJS s are driven onto the quasi-sliding mode band by synthesizing an event-triggered sliding mode ***,the event-triggered scheme is developed together with the design of sliding mode controller,which is different from the most existing ***,the value of the quasi-sliding mode band is also given by ***,the introduction of event-triggered scheme is capable of saving the network bandwidth utilization while maintaining a satisfactory system ***,the effectiveness of the presented approach is illustrated by utilizing a practical DC motor model.

关键词： Markovian jump systems(MJSs) sliding mode control(SMC) event-triggered scheme(ETS) uncertainty

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Dynamic Target Enclosing control Scheme for Multi-Agent Systems via a Signed Graph-Based Approach

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IEEE/CAA Journal of Automatica Sinica 2023年第2期10卷 560-562页

作者： Weihao Li Kaiyu Qin Mengji Shi Jingliang Shao Boxian Lin the School of Aeronautics and Astronautics University of Electronic Science and Technology of ChinaChengdu 611731 the Aircraft Swarm Intelligent Sensing and Cooperative Control Key Laboratory of Sichuan Province Chengdu 611731China the School of Automation Engineering University of Electronic Science and Technology of ChinaChengdu 611731China

Dear Editor,This letter investigates the target enclosing control problem of multi-agent systems.A signed graph-based control strategy is presented,where the agents are steered to enclose the dynamic target from both sides as they *** is inspired by the phenomenon that signed networks exhibit bipartite clustering if the underlying graph is structurally balanced,so that the agents may naturally enclose the zero point from opposite sides(+and.)if proper controllers are *** adopting a distributed observer to estimate the information of dynamic target。

关键词： networks agent Dynamic

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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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PI-funnel and inverse hysteresis compensation cascade control of smart soft dielectric elastomer actuator

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control Theory and Technology 2024年第4期22卷 552-567页

作者： Peng Huang Yawu Wang Yue Zhang Jundong Wu Chun-Yi Su School of Automation China University of GeosciencesWuhan430074HubeiChina Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074HubeiChina Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of EducationWuhan430074HubeiChina Gina Cody School of Engineering and Computer Science Concordia UniversityMontrealQCH3G 1M8Canada

Smart soft dielectric elastomer actuators(SSDEAs)possess wide applications in soft robotics due to their properties similar to natural muscles,including large deformation ratio,high energy density,and fast response ***,the complicated asymmetric and rate-dependent hysteresis property,creep property and quadratic input property of the SSDEA pose enormous challenges to its dynamic modeling and motion *** this paper,first,we construct the dynamic model of the SSDEA by connecting a square module,a one-sided Prandtl–Ishlinskii(OSPI)model and a linear system in series to describe the above *** key and innovative aspect of the dynamic modeling lies in cascading the square module in series with the OSPI model to construct the asymmetric hysteresis ***,a PI-funnel and inverse hysteresis compensation(PIFIHC)cascade control method of the SSDEA is proposed to actualize its tracking control *** performing the inversion operation on the asymmetric hysteresis model,the inverse hysteresis compensation controller(IHCC)is designed to compensate the asymmetric hysteresis property and quadratic input property of the *** addition,a PI-funnel controller is designed to cascade with the IHCC to construct the PIFIHC cascade controller to obtain a good tracking ***,the stability analysis of the PIFIHC cascade control system of the SSDEA is performed to theoretically prove that the tracking error can be controlled within the performance funnel and the steady-state error converges to ***,several practical tracking control experiments of the SSDEA are conducted,and RRMSEs are less than 2.30%for all *** experimental results indicate the effectiveness and feasibility of the proposed PIFIHC cascade control method of the SSDEA.

关键词： Smart soft dielectric elastomer actuator Dynamic modeling Inverse hysteresis compensation controller PI-funnel controller Cascade controller

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Observer-based quantised control of networked systems with round-robin protocol and transmission delay

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Journal of control and Decision 2025年第1期12卷 24-33页

作者： Ge Guo Xuefei Yan Jian Kang State Key Laboratory of Synthetical Automation for Process Industries Northeastern UniversityShenyangPeople's Republic of China School of Control Engineering Northeastern University at QinhuangdaoQinhuangdaoPeople's Republic of China College of Information Science and Engineering Northeastern UniversityShenyangPeople's Republic of China

This paper addresses the ultimate boundedness control problem for a class of networked nonlinear systems with the round-robin(RR)protocol and uniform *** communication between sensor nodes and the controller is implemented via a constrained communication *** quantised output of the system is transmitted to the remote controller through a communication channel subject to a transmission *** the purpose of alleviating possible data collision,the well-known RR communication protocol is deployed to schedule the data *** the other hand,the uniform quantisation effects of the network are characterised by a round function(*** nearest integer function).The purpose of the addressed problem is to design an observer-based controller for the networked nonlinear systems such that,in the presence of RR protocol and uniform quantisation effects,the closed-loop system is ultimately *** controller is designed based on mean square stability analysis and Lyapunov-like method.A set of sufficient conditions for the ultimate boundedness of the closed-loop system are established and,on the basis of which,the desired controller gains are obtained by solving a set of linear matrix *** effectiveness of the proposed method is verified by numerical examples.

关键词： Networked control systems(NCSs) round-robin(RR)protocol transmission delay uniform quantisation ultimate boundedness control

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Learning from ChatGPT: A Transformer-Based Model for Wind Power Forecasting

Learning from ChatGPT: A Transformer-Based Model for Wind Po...

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2023 IEEE International Conference on Environment and Electrical engineering and 2023 IEEE Industrial and Commercial Power Systems Europe, EEEIC / I and CPS Europe 2023

作者： Dai, Xiaoran Liu, Guo-Ping Hu, Wenshan Lei, Zhongcheng Zhou, Hong School of Electrical Engineering and Automation Wuhan University Wuhan China Center for Control Science and Technology Southern University of Science and Technology Shenzhen China

ISBN: (纸本)9798350347432

Wind power forecasting is a crucial aspect of re-newable energy production, as it helps to optimize energy output and ensure grid stability. In recent years, Transformer-based language models such as ChatGPT have been successfully used in natural language processing tasks, but their application in wind power forecasting remains largely unexplored. In this article, we propose using a Transformer model, the core of ChatGPT, to improve the accuracy of wind power forecasting. Using the self-attention mechanism, the developed model can capture the complex temporal relationships in large-scale time series data. Furthermore, the proposed method is evaluated on a test set using various performance metrics. Results show that our model outperforms traditional forecasting models, achieving higher accuracy. Our findings suggest that Transformer-based models have significant potential for improving wind power forecasting accuracy and ultimately contributing to a more sustainable energy future. © 2023 IEEE.

关键词： Time series

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Multi-Spill Surface Target Tracking Based on Oil Particle-Random Point Pattern 12

Multi-Spill Surface Target Tracking Based on Oil Particle-Ra...

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12th IEEE International Conference on control, automation and Information sciences, ICCAIS 2023

作者： Sun, Qiankun Liu, Weifeng Wen, Chenglin Shaanxi University of Science and Technology School of Electrical and Control Engineering Xi'an China Guangdong University of Petrochemical Technology School of Automation Maoming China

ISBN: (纸本)9798350328783

In complex marine environments, it is difficult to obtain important parameters such as the number, location, and shape of oil spill surfaces;multiple oil spill surfaces may overlap and merge, which makes the accurate tracking of multiple oil spill surfaces even more difficult. To address the aforementioned issues, proposed a multi-spill surface target tracking method based on the oil particle-random point pattern. Firstly, the oil spill surface is represented by an oil particle model. Then, a random point pattern algorithm is introduced to cluster the oil spill surface. Finally, the GLMB filtering method is utilized to track the centroid trajectory of the oil spill surface, and its shape and concentration information is recorded at the same time. Simulation experiments show the effectiveness of the proposed algorithm. © 2023 IEEE.

关键词： Oil spills

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A new noise network and gradient parallelisation‐based asynchronous advantage actor‐critic algorithm

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IET Cyber-Systems and Robotics 2022年第3期4卷 175-188页

作者： Zhengshun Fei Yanping Wang Jinglong Wang Kangling Liu Bingqiang Huang Ping Tan Provincial Key Institute of Robotics School of Automation and Electrical EngineeringZhejiang University of Science and TechnologyHangzhouChina State Key Lab of Industrial Control Technology College of Control Science and EngineeringZhejiang UniversityHangzhouChina

Asynchronous advantage actor‐critic(A3C)algorithm is a commonly used policy opti-mization algorithm in reinforcement learning,in which asynchronous is parallel inter-active sampling and training,and advantage is a sampling multi‐step reward estimation method for computing *** order to address the problem of low efficiency and insufficient convergence caused by the traditional heuristic exploration of A3C algorithm in reinforcement learning,an improved A3C algorithm is proposed in this *** this algorithm,a noise network function,which updates the noise tensor in an explicit way is constructed to train the *** advantage estimation(GAE)is also adopted to describe the dominance ***,a new mean gradient parallelisation method is designed to update the parameters in both the primary and secondary networks by summing and averaging the gradients passed from all the sub‐processes to the main *** experiments were conducted in a gym environment using the PyTorch Agent Net(PTAN)advanced reinforcement learning library,and the results show that the method enables the agent to complete the learning training faster and its convergence during the training process is *** improved A3C algorithm has a better performance than the original algorithm,which can provide new ideas for sub-sequent research on reinforcement learning algorithms.

关键词： asynchronous advantage actorcritic (A3C) generalised advantage estimation (GAE) parallelisation reinforcement learning

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Target Assignment in the Multi-UAV Combat Based on Distributed Compensation Auction Algorithm with Fixed-Time Consensus Protocol 7th

Target Assignment in the Multi-UAV Combat Based on Distri...

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7th Chinese Conference on Swarm Intelligence and Cooperative control, CCSICC 2023

作者： Chen, Yiyang Hua, Yongzhao Yu, Jianglong Dong, Xiwang Institute of Artificial Intelligence Beihang University Beijing100191 China School of Automation Science and Electrical Engineering Science and Technology on Aircraft Control Laboratory Beihang University Beijing100191 China

ISBN: (纸本)9789819733231

This paper mainly focuses on the target assignment problems in the unmanned aerial vehicle (UAV) swarm combat. Firstly, the idea of the multi-UAV swarm combat is shown and the constraints and the benefit matrix of the target assignment task are modeled. Secondly, a fixed-time consensus protocol is utilized to estimate the state of all the other agents and its convergence is proved by Lyapunov method. Then, a distributed compensation auction algorithm is proposed. Finally, the proposed distributed compensation auction algorithm is simulated and the results demonstrate the successful completion of the assignment task with only neighboring information. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

关键词： Lyapunov methods

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Model-free adaptive predictive control of nonlinear sandwich systems with input constraints 13

Model-free adaptive predictive control of nonlinear sandwich...

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13th IEEE Data Driven control and Learning Systems Conference, DDCLS 2024

作者： Dong, Jianguo Liu, Jun Jiang, Xiaoqing Wang, Ziyu Luo, Huarui Shi, Zhao School of Automation Southeast University Nanjing210000 China School of Information and Control Engineering China University of Mining and Technology Xuzhou221116 China College of Information Science and Engineering Northeastern University Shenyang China

ISBN: (纸本)9798350361674

Since nonlinear sandwich systems with input constraints are difficult to establish their model accurately, a model-free adaptive predictive control (MFAPC) based on compact format dynamic linearization is proposed. The criterion function of MFAPC algorithm is applied to build a quadratic programming problem with input constraints. The optimal control input signal can be obtained by solving the quadratic programming problem. In order to eliminate the adverse effect of random measurement noise on solving the optimal input signal and the stability of tracking control results, the tracking differentiator is used to estimate the output measurement signal. The stability of the control algorithm is also analyzed and proved. Finally, the merit of the proposed control algorithm is verified by example test. © 2024 IEEE.

关键词： Predictive control systems

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