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42nd Chinese control Conference, CCC 2023

作者： Lu, Huangyuwei Wang, Zuo Sun, Jiankun Xiao, Xi Li, Shihua School of Automation Southeast University Nanjing210096 China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Shenzhen Research Institute Southeast University Shenzhen518063 China School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Aviation Key Laboratory of Science and Technology on Aero Electromechanical System Integration Nanjing211106 China

ISBN: (纸本)9789887581543

To improve the disturbance rejection ability and repetitive tracking accuracy of manipulators, a composite iterative learning control (ILC) scheme via generalized proportional integral observer (GPIO) is proposed. A high-order polynomial is first employed to model the time-varying disturbances that include unmodeled dynamics, parameter uncertainties and load fluctuations. A GPIO is then designed to estimate the disturbances and high-order time derivatives. By introducing estimations into a PD-type ILC at each iteration, a composite control scheme is obtained, such that the undesirable influence of time-varying disturbances can be effectively attenuated in the repetitive tracking process of manipulators. In this paper, the rigorous stability analysis of the closed-loop system is presented to guarantee that the tracking error exponentially converges to zero as the iteration number tends to infinity. The effectiveness of the proposed control scheme is finally verified by simulation results. © 2023 Technical Committee on control Theory, Chinese Association of Automation.

关键词： Disturbance rejection

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Global Consensus for Heterogeneous Saturated Multi-Agent Systems via Sampled-Data control 63

Global Consensus for Heterogeneous Saturated Multi-Agent Sys...

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63rd IEEE Conference on Decision and control, CDC 2024

作者： Qian, Juan Wang, Xiaoling Astolfi, Daniele Su, Housheng Jiang, Guo-Ping Nanjing University of Posts and Telecommunications College of Automation and the College of Artificial Intelligence Nanjing210023 China Nanjing210023 China Université Claude Bernard Lyon 1 Cnrs Lagepp Umr 5007 43 boulevard du 11 novembre 1918 VilleurbanneF-69100 France East China University of Science and Technology Key Laboratory of Smart Manufacturing in Energy Chemical Process Ministry of Education Shanghai200237 China Huazhong University of Science and Technology School of Artificial Intelligence and Automation Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Luoyu Road 1037 Wuhan430074 China

ISBN: (纸本)9798350316339

This paper addresses the global consensus problem for multi-input multi-output saturated systems within a sampled-data framework, aiming to advance global consensus, manage heterogeneous actuator saturation across components, and preserve distributed characteristics by using sampled-data feedback. We propose a distributed control algorithm that incorporates a redesigned saturation function, represented as decentralized dynamic saturation levels. These levels for each agent's dimensions are autonomously updated through an adaptive strategy, which mitigates heterogeneous saturation by carefully selecting constant and time-varying saturation parameters in it. Lyapunov analysis proves that global consensus can be achieved under the proposed control law, provided the sampling periods of all agents remain below a calculated threshold. An example is given to demonstrate the effectiveness of this approach. © 2024 IEEE.

关键词： Decentralized control

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Embedding any desired number of coexisting attractors in memristive system

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Chinese Physics B 2021年第12期30卷 53-62页

作者： Chunbiao Li Ran Wang Xu Ma Yicheng Jiang Zuohua Liu Jiangsu Collaborative Innovation Center of Atmospheric Environment and Equipment Technology(CICAEET) Nanjing University of Information Science&TechnologyNanjing 210044China School of Artificial Intelligence Nanjing University of Information Science&TechnologyNanjing 210044China State Key Laboratory of Coal Mine Disaster Dynamics and Control Chongqing UniversityChongqing 400044China

A simple variable-boostable system is selected as the structure for hosting an arbitrarily defined memristor for chaos *** derived three-dimensional(3-D)memristive chaotic system shows its distinct property of offset,amplitude and frequency *** its merits any desired number of coexisting attractors are embedded by means of attractor doubling and self-reproducing based on function-oriented offset *** this circumstance two classes of control gates are found:one determines the number of coexisting attractors resorting to the independent offset controller while the other is the initial condition selecting any one of *** simulation gives a consistent output with theoretically predicted embedded attractors.

关键词： offset boosting attractor doubling attractor self-reproducing memristive system

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Data-Driven Modeling for Pneumatic Muscle Using Koopman-Based Kalman Filter

Data-Driven Modeling for Pneumatic Muscle Using Koopman-Base...

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IEEE International Conference on Development and Learning, ICDL

作者： Yu Caol Mengshi Zhang Bo Yang Jian Huang Key Laboratory for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

This paper presents a data-driven modeling approach for enhancing the understanding of pneumatic muscles (PMs) through Koopman kalman filter (KKF). The proposed method involves the construction of a comprehensive pneumatic muscle motion data-set, obtained by capturing extensive input-state-output data through the application of random inputs. Subsequently, the states of pneumatic muscle are lifted through a kernel-based technique. The nonlinear pneumatic muscle model is then transformed into a linear counterpart using the extended dynamic mode decomposition (EDMD). Then, a kalman filter is further used to improve the model accuracy. The effectiveness of this approach is demonstrated through simulation analysis, highlighting its capacity to yield superior pneumatic muscle modeling and state estimation results when compared to conventional Koopman operator methodologies.

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3-D temperature field reconstruction of lithium-ion battery pack using real-time distributed moving horizon estimation

3-D temperature field reconstruction of lithium-ion battery ...

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第35届中国控制与决策会议

作者： Jiayu Yan Yiming Wan School of Artificial Intelligence and Automation Huazhong University of Science and Technologyand Key Laboratory of Image Processing and Intelligent ControlMinistry of Education

As lithium-ion batteries are widely used in different fields,the thermal effect is of serious *** to achieve accurate temperature estimation in real time is the main challenge of current *** address this problem,we propose a realtime distributed moving horizon estimation(RT-DMHE) based on partial differential equations describing thermal dynamics of a lithium-ion battery *** decomposes the real-time centralized moving horizon estimation(RT-CMHE) into multiple local estimators that run in parallel with information exchange from adjacent *** validation shows that the root mean square error of temperature estimates from the proposed RT-DMHE is smaller than that of an existing distributed Kalman filter in ***,compared to the RT-CMHE,the proposed RT-DMHE achieves comparable estimation accuracy while vastly reducing the average computation time per sample.

关键词： lithium-ion battery pack distributed moving horizon estimation real-time computation state-of-temperature estimation

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Small-Gain Theorem Based Distributed Prescribed-Time Convex Optimization For Networked Euler-Lagrange Systems

arXiv

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arXiv 2024年

作者： Zuo, Gewei Li, Mengmou Zhu, Lijun School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan430074 China Key Laboratory of Imaging Processing and Intelligence Control Huazhong University of Science and Technology Wuhan430074 China Graduate School of Advanced Science and Engineering Hiroshima University Higashi-Hiroshima739-0046 Japan

In this paper, we address the distributed prescribed-time convex optimization (DPTCO) for a class of networked Euler-Lagrange systems under undirected connected graphs. By utilizing position-dependent measured gradient value of local objective function and local information interactions among neighboring agents, a set of auxiliary systems is constructed to cooperatively seek the optimal solution. The DPTCO problem is then converted to the prescribed-time stabilization problem of an interconnected error system. A prescribed-time small-gain criterion is proposed to characterize prescribed-time stabilization of the system, offering a novel approach that enhances the effectiveness beyond existing asymptotic or finite-time stabilization of an interconnected system. Under the criterion and auxiliary systems, innovative adaptive prescribed-time local tracking controllers are designed for subsystems. The prescribed-time convergence lies in the introduction of time-varying gains which increase to infinity as time tends to the prescribed time. Lyapunov function together with prescribed-time mapping are used to prove the prescribed-time stability of closed-loop system as well as the boundedness of internal signals. Finally, theoretical results are verified by one numerical example. Copyright © 2024, The Authors. All rights reserved.

关键词： Lyapunov functions

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Hop-by-hop Redundancy-guaranteed Adaptive Coding for Enhancing Transmission Reliability of UAV Networks

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IEEE Transactions on Communications 2025年

作者： He, Huasen Ren, Yue Li, Junjun Jiang, Xiaofeng Hou, Yunpeng Chen, Shuangwu Yang, Jian University of Science and Technology of China Department of Automation Hefei230027 China Deep Space Exploration Laboratory Hefei230088 China Southwest University of Science and Technology School of Information Engineering Sichuan621010 China Hefei Comprehensive National Science Center Institute of Artificial Intelligence Hefei230026 China

The integrated merits of Unmanned Aerial Vehicle (UAV) networks including high mobility, ease of deployment and low cost have promoted their widely application in both civilian and military areas. However, the complex communication environments, dynamic network topology and intermittent links pose significant challenges to the transmission reliability of UAV networks. Existing end-to-end reliable transmission mechanisms rely on feedbacks from receivers to trigger retransmission, which impose extra transmission delay and redundant retransmission. In this work, we propose a Hop-by-Hop Redundancy-guaranteed Adaptive Coding (HHRAC) approach for enhancing transmission reliability of dynamic UAV Networks. To cope with lossy links, a link quality-adaptive coding algorithm is proposed, which dynamically adjusts coding redundancy rate according to link quality. Meanwhile, the Cauchy matrix is employed to design efficient coding matrices, which greatly improve decoding efficiency and enable the intermediate nodes to perform low-complexity verification. Moreover, a redundancy-guaranteed hop-by-hop transmission mechanism is provided to avoid End-to-End (E2E) retransmission and ensure the destination node has a high probability to receive sufficient packets. To avoid receive queue overflow, we further propose a queue length prediction based congestion control algorithm to control the sending rates of UAVs. The experimental results show that HHRAC achieves significant performance gains compared to existing algorithms in terms of transmission delay and retransmission times. © 1972-2012 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Temperature Gradient Analyses of a Tubular Solid Oxide Fuel Cell Fueled by Methanol

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Transactions of Tianjin University 2023年第1期29卷 14-30页

作者： Qidong Xu Meiting Guo Lingchao Xia Zheng Li Qijiao He Dongqi Zhao Keqing Zheng Meng Ni Department of Building and Real Estate Research Institute for Sustainable Urban Development(RISUD)&Research Institute for Smart Energy(RISE)The Hong Kong Polytechnic UniversityHong Kong 999077China School of Artifi cial Intelligence and Automation Key Laboratory of Image Processing and Intelligent ControlHuazhong University of Science and TechnologyWuhan 430074China School of Low-Carbon Energy and Power Engineering China University of Mining and TechnologyXuzhou 221116China

Thermal management in solid oxide fuel cells(SOFC)is a critical issue due to non-uniform electrochemical reactions and convective fl ows within the ***,a 2D mathematical model is established herein to investigate the thermal responses of a tubular methanol-fueled *** show that unlike the low-temperature condition of 873 K,where the peak temperature gradient occurs at the cell center,it appears near the fuel inlet at 1073 K because of the rapid temperature rise induced by the elevated current *** the large heat convection capacity,excessive air could not eff ectively eliminate the harmful temperature gradient caused by the large current ***,optimal control of the current density by properly selecting the operating potential could generate a local thermal neutral ***,the maximum axial temperature gradient could be reduced by about 18%at 973 K and 20%at 1073 K when the air with a 5 K higher temperature is ***,despite the higher electrochemical performance observed,the cell with a counter-fl ow arrange-ment featured by a larger hot area and higher maximum temperature gradients is not preferable for a ceramic SOFC system considering thermal ***,this study could provide insightful thermal information for the operating condition selection,structure design,and stability assessment of realistic SOFCs combined with their internal reforming process.

关键词： Solid oxide fuel cell Modeling Methanol fuel Temperature gradient Internal reforming

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HyRSM++: Hybrid relation guided temporal set matching for few-shot action recognition

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Pattern Recognition 2024年 147卷

作者： Wang, Xiang Zhang, Shiwei Qing, Zhiwu Zuo, Zhengrong Gao, Changxin Jin, Rong Sang, Nong Key Laboratory of Ministry of Education for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology China Alibaba Group China Meta AI United States

Few-shot action recognition is a challenging but practical problem aiming to learn a model that can be easily adapted to identify new action categories with only a few labeled samples. However, existing attempts still suffer from two drawbacks: (i) learning individual features without considering the entire task may result in limited representation capability, and (ii) existing alignment strategies are sensitive to noises and misaligned instances. To handle the two limitations, we propose a novel Hybrid Relation guided temporal Set Matching (HyRSM++) approach for few-shot action recognition. The core idea of HyRSM++ is to integrate all videos within the task to learn discriminative representations and involve a robust matching technique. To be specific, HyRSM++ consists of two key components, a hybrid relation module and a temporal set matching metric. Given the basic representations from the feature extractor, the hybrid relation module is introduced to fully exploit associated relations within and cross videos in an episodic task and thus can learn task-specific embeddings. Subsequently, in the temporal set matching metric, we carry out the distance measure between query and support videos from a set matching perspective and design a bidirectional Mean Hausdorff Metric to improve the resilience to misaligned instances. Furthermore, we extend the proposed HyRSM++ to deal with the more challenging semi-supervised few-shot action recognition and unsupervised few-shot action recognition tasks. Experimental results on multiple benchmarks demonstrate that our method consistently outperforms existing methods and achieves state-of-the-art performance under various few-shot settings. The source code is available at https://***/alibaba-mmai-research/HyRSMPlusPlus. © 2023 Elsevier Ltd

关键词： Benchmarking

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Thermal Safety Analysis and Dynamic control Strategy for Mode Switching Process of Reversible Solid Oxide Cell System

Thermal Safety Analysis and Dynamic Control Strategy for Mod...

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第42届中国控制会议

作者： Wei Zhao Guoqiang Liu Zexin Li Xi Li School of Artificial Intelligence and Automation Key Laboratory of Image Processing and Intelligent Control of Education MinistryHuazhong University of Science and Technology

Reversible solid oxide cells(rSOC) can operate in both electrolysis mode and in fuel cell mode with high efficiency and reduced cost using the same device for both *** used in dynamic operation with intermittent electrical power sources,rSOC system switches from the fuel cell(SOFC) to electrolyzer(SOEC) and vice versa depending on load and grid *** can lead to temperature profiles within the stack that can potentially lead to the failure of the stack and eventually the *** the present work,a system-level dynamic model of r SOC is established and validated against experimental ***,detailed dynamic thermal behavior of stack during the switching between the two modes is analyzed,and a temperature management controller based on Model Predict control method(MPC) is *** flow and temperature at the stack inlet are controlled by air flow and bypass valves,avoiding problems associated with temperature overshoot during transient *** simulation results show that the temperature controller has the ability to follow fast thermal changes while maintaining thermal safety,which indicates the competitiveness of the controller.

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