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Adaptive Neural Finite-Time Deployment of Heterogeneous Multi-agent Systems via a Cross-Species Bionic PDE-ODE Approach

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人工智能科学与工程 2025年第1期1卷 52-63页

作者： Jingtao MAN Zhigang ZENG School of Artificial Intelligence and Automation Huazhong University of Science and TechnologyWuhan 430074China Key Laboratory of Image Processing and Intelligent Control of Education Ministry of China Wuhan 430074China

For large-scale heterogeneous multi-agent systems(MASs)with cha-racteristics of dense-sparse mixed distribution,this paper investigates the practical finite-time deployment problem by establishing a novel cross-species bionic analytical framework based on the partial differential equation-ordinary differential equation(PDE-ODE)***-fically,by designing a specialized network communication protocol and employing the spatial continuum method for densely distributed agents,this paper models the tracking errors of densely distributed agents as a PDE equivalent to a human disease transmission model,and that of sparsely distributed agents as several ODEs equivalent to the predator population *** coupling relationship between the PDE and ODE models is established through boundary conditions of the PDE,thereby forming a PDE-ODE-based tracking error model for the considered ***,by integrating adaptive neural control scheme with the aforementioned biological models,a"Flexible Neural Network"endowed with adaptive and self-stabilized capabilities is constructed,which acts upon the considered MASs,enabling their practical finite-time ***,effectiveness of the developed approach is illustrated through a numerical example.

关键词： large-scale heterogeneous MASs cross-species bionic framework prac-tical finite-time deployment PDE-ODE approach adaptive neural con-trol

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Global Exponential Synchronization of Delayed Fuzzy Neural Networks With Reaction Diffusions

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IEEE TRANSACTIONS ON FUZZY SYSTEMS 2023年第8期31卷 2809-2820页

作者： Sheng, Yin Xing, Yun Huang, Tingwen Zeng, Zhigang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Educ Minist China Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China Texas A&M Univ Qatar Sci Program Doha 5825 Qatar

This article is concerned with global exponential synchronization of delayed fuzzy neural networks with reaction diffusions (RDFNNs). By adopting analytic method and some inequality techniques, a global exponential synchronization criterion in terms of p-norm (p = 2) is obtained for the RDFNNs via adaptive intermittent control. One numerical example is provided to demonstrate the validity of the proposed outcomes. Two other examples are given to show the applications in image encryption and pseudorandom number generation, respectively.

关键词： Adaptive intermittent control exponential synchronization fuzzy neural networks (FNNs) reaction diffusions (RDs)

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An Assist-as-Needed Variable Admittance controller for Adaptive Support of Mobile Walking Assistive Robots 30

An Assist-as-Needed Variable Admittance Controller for Adapt...

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30th International Conference on Mechatronics and Machine Vision in Practice, M2VIP 2024

作者： Chen, Xinxing Zheng, Yue Su, Zongming Leng, Yuquan Huang, Jian Fu, Chenglong Guangdong Provincial Key Laboratory of Human-Augmentation and Rehabilitation Robotics in Universities Southern University of Science and Technology Shenzhen China Huawei Technologies Technology Planning Department Shenzhen China Key Laboratory for Image Processing and Intelligent Control School of Artificial Intelligence and Automation Huazhong University of Science and Technology Wuhan China

ISBN: (纸本)9798350391916

Mobile walking assistive robots have been widely used for monitoring patients' gait patterns and providing support to prevent falls. Traditional approaches often separate the operational modes of these robots into human-following and supporting modes, which can lead to discontinuities in assistance and potentially compromise safety. This paper proposes a novel assist-as-needed control strategy that incorporates a Balance Index (BI) to dynamically adjust the robot's support based on the user's balance capability. The BI is calculated using the interaction force between the user and the robot along the z-axis and the gait symmetry index (GSI). The proposed variable admittance controller modifies its parameters based on the BI, ensuring seamless transitions between compliance and support modes. Experimental validation was conducted with a healthy subject walking both with and without a knee fixation brace. The results demonstrate that the robot provides minimal interference during natural gait and increased support during impaired gait, validating the effectiveness of the proposed control strategy in enhancing user safety and promoting natural walking patterns. © 2024 IEEE.

关键词： Assistive technology

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3-D temperature field reconstruction of lithium-ion battery pack using real-time distributed moving horizon estimation 35

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

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35th Chinese control and Decision Conference (CCDC)

作者： Yan, Jiayu Wan, Yiming Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Minist Educ Key Lab Image Proc & Intelligent Control Wuhan 430074 Peoples R China

ISBN: (纸本)9798350334722

As lithium-ion batteries are widely used in different fields, the thermal effect is of serious concern. How to achieve accurate temperature estimation in real time is the main challenge of current research. To address this problem, we propose a real-time distributed moving horizon estimation (RT-DMHE) based on partial differential equations describing thermal dynamics of a lithium-ion battery pack. It decomposes the real-time centralized moving horizon estimation (RT-CMHE) into multiple local estimators that run in parallel with information exchange from adjacent subsystems. Simulation 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 literature. Moreover, 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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Presketched DNA Origami Canvas for Polymerase-Driven DNA Kirigami

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ACS NANO 2023年第17期17卷 17265-17272页

作者： Chen, Kuiting Xie, Chun Chen, Zhekun Wang, Shichen Hu, Yingxin Xu, Fei Pan, Linqiang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Key Lab Image Informat Proc Intelligent Control Educ Minist China Wuhan 430074 Hubei Peoples R China Shijiazhuang Tiedao Univ Coll Informat Sci & Technol Shijiazhuang 050043 Hebei Peoples R China

Reconfigurable DNA origami provides a versatile tool to manipulate the conformation of matter on the nanometer scale. Typically, the DNA kirigami method enables the transformation of an origami structure from an initial shape to another predesigned shape by reconfiguring the staple strands. In a regular origami structure, since the perfectly matched and densely packed DNA duplexes block the removal of staple strands, the construction of finely trimmed "sub-origami" structures by the DNA kirigami method has remained challenging. Herein, we proposed a strategy to construct the presketched DNA origami canvas, where the offcut area in the canvas was sketched by loosely fixed staple strands with single-base insertion, to enhance the fineness of polymerase-driven DNA kirigami. We successfully trimmed presketched two-dimensional rectangular canvas, three-dimensional Mo''bius strip, and genie bottle canvases into complex letter patterns, supercoiled rings, and nanorods, respectively. Finally, we demonstrated a size-controlled DNA kirigami system: a presketched 6HB origami was trimmed into a set of shorter nanowires with predefined lengths, which quantitatively characterized the fineness of the improved DNA kirigami. The presketched origami design was a general method that applied to both 2D and 3D DNA origami structures in square and honeycomb lattices. Loosening DNA origami structures by introducing single-base insertions provides a practical approach to constructing dynamic components when designing DNA nanomachines. Furthermore, the delicate trimming of the DNA origami canvas driven by polymerase may inspire strategies for graphical information encryption and storage.

关键词： DNA nanotechnology DNA origami reconfigurableDNA nanostructure polymerase-triggered strand displacement DNA kirigami

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Stability of networked control systems under malicious attacks and bit rate constraints

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JOURNAL OF THE FRANKLIN INSTITUTE-ENGINEERING AND APPLIED MATHEMATICS 2024年第18期361卷

作者： Wang, Wen-Hui Wang, Yan-Wu Hu, Meng-Jie Yang, Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China China Univ Min & Technol Sch Informat & Control Engn Xuzhou 221000 Peoples R China Guangxi Univ Sch Elect Engn Nanning 530004 Peoples R China

This article investigates the stability of networked control systems under two types of malicious attacks and bit rate constraints. The malicious attacks may lead to parameter mismatches, including scaling variable mismatches between the encoder and decoder sides and discrepancies between the data sent by the encoder and received by the decoder, causing system instability. To address these issues, scaling variable update rules are proposed for the encoder and decoder sides separately to mitigate the adverse effects of malicious attacks. A control strategy featuring a compensation term is designed to counteract the detrimental impacts of the mismatch. A lower bound on the bit rate is established to prevent quantization saturation and achieve exponential stability of the system. Finally, confirmatory and comparative simulations showcase the effectiveness of the theoretical insights and the merits of the proposed strategies, respectively.

关键词： Networked control system Malicious attack Bit rate constraint

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Designing a completely distributed observer with robustness against disturbances

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INTERNATIONAL JOURNAL OF ROBUST AND NONLINEAR control 2024年第12期34卷 7912-7935页

作者： Wang, Xiaoling Zhang, Ankang Su, Housheng Chen, Guanrong Nanjing Univ Posts & Telecommun Coll Automat & AI Nanjing 210003 Peoples R China Jiangsu Engn Lab IOT Intelligent Robots IOTRobot Nanjing Peoples R China East China Univ Sci & Technol Minist Educ Key Lab Smart Mfg Energy Chem Proc Shanghai Peoples R China Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Image Proc & Intelligent Control Key Lab Educ Minist China Wuhan 430074 Peoples R China City Univ Hong Kong Dept Elect Engn Hong Kong Peoples R China

Distributed observer is an effective scheme for state estimation of a targeted system, utilizing a network of sensors to perform local output measurements. In this article, the problem of designing a distributed observer for a linear time-invariant system with external disturbances is addressed. The objective is to perform state estimation of such a system while simultaneously mitigating the impact of external disturbances and maintaining the distributed communication characteristics among the sensors. To achieve this, a completely distributed observer with robustness against disturbances is developed by combining the high-gain observer technique and the adaptive coupling strength strategy. Initially, a traditional high-gain observer is used for the state estimation on the observable subsystem, and subsequently a high-gain observer without peaking is introduced to avoid the peaking phenomenon. Finally, numerical simulations are presented to verify the theoretical results.

关键词： adaptive coupling gain distributed observer external disturbance high-gain observer robustness

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A transactive energy cooperation scheduling for hydrogen-based community microgrid with refueling preferences of hydrogen vehicles

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APPLIED ENERGY 2025年 377卷

作者： Zhang, Xiao-Yan Wang, Cenfeng Xiao, Jiang-Wen Wang, Yan-Wu Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automat Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Key Lab Image Proc & Intelligent Control Minist Educ Wuhan 430074 Peoples R China State Grid Zhejiang Elect Power Co Ltd Econ & Technol Res Inst Hangzhou 310008 Peoples R China

Hydrogen, as a high specific energy green carrier, is promising for power generation and transportation. This paper proposes a transactive energy cooperation framework for an end-user-oriented hydrogen-based community microgrid considering refueling preferences of hydrogen vehicles (HVs) and industrial hydrogen demand to minimize social cost. In this framework, an aggregator obtains stacking profits in both the electricity and hydrogen markets through flexible interconversion, storage, and interaction of electricity and hydrogen. For resident users, the refueling preferences of HVs are analyzed to reduce cost through demand response (DR). A novel energy density-weighted asymmetric Nash bargaining (DANB) method is designed to fairly assess the combined contribution, considering both electricity and hydrogen bargaining metrics for end- users. An alternating optimization procedure with the adaptive alternating direction method of multipliers (ADMM) algorithm is designed to solve the mixed-integer linear programming (MILP) problem in the social operation cost minimization process. Comparison results show the algorithm convergence advantage, the cost-effectiveness and scalability of the cooperation framework, as well as the rationality of the DANB and the flexibility of HVs in DR. Besides, the optimal configuration of the battery, the hydrogen tank, and the electrolyzer in the framework is explored, alongside the economic feasibility of electricity-hydrogen-electricity technology.

关键词： Hydrogen-based microgrid Hydrogen demand response Combined contribution assessment Alternating optimization procedure with alternating direction method of multipliers

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Air Pollution Monitoring By Integrating Local and Global Information in Self-Adaptive Multiscale Transform Domain

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IEEE Transactions on Multimedia 2025年 27卷 3716-3728页

作者： Gu, Ke Liu, Yuchen Liu, Hongyan Liu, Bo Qiao, Junfei Lin, Weisi Zhang, Wenjun Beijing University of Technology School of Information Science and Technology Engineering Research Center of Intelligent Perception and Autonomous Control of Ministry of Education Beijing Laboratory of Smart Environmental Protection Beijing Key Laboratory of Computational Intelligence and Intelligent System Beijing Artificial Intelligence Institute Beijing100124 China Massey University School of Mathematical and Computational Sciences New Zealand Nanyang Technological University College of Computing and Data Science Singapore Shanghai Jiao Tong University Institute of Image Communication and Information Processing Shanghai China

As the deadliest form of pollution, air pollution had a prolonged severe damage to the human health and life safety of nearly 99% of the world's population. Facing to the problem that billions of tons of pollutants discharged into the air per year by industrial activities, this paper proposed a novel image-based air pollution monitor (IAPM) by incorporating local and global information in the self-adaptive multiscale transform domain, so as to achieve the timely and effective leakage detection of typical air pollutants from a single image. To be specific, this paper first developed a screen-shaped module according to two significant findings in visual neuroscience, which include the high sensitivity of human eyes to horizontal and vertical stimuli and the center-surround inhibition, by designing and fusing the square module, horizontal strip module and vertical strip module parallelly for simulating the behaviour of human eyes to extract local features. Second, the learnable weights and proportional mapping were applied to incorporate the screen-shaped module and lightweight vision transformer as backbone, towards more richly exploiting and fusing local and global information just as the way a brain perceives external stimuli. Third, a new self-adaptive multiscale transform domain method was devised based on two motivations from the visual characteristics of multiscale perception and the brain characteristics of self-adaptive domain transform to modify the backbone by using the operations of pooling and pointwise convolution. Extensive experiments implemented on the datasets of carbon particulate matters and ethylene leakage confirmed the superior monitoring performance of the proposed IAPM model beyond the state-of-the-art (SOTA) peers by an accuracy gain of about 4%. Furthermore, the proposed IAPM model only required 0.089 GFLOPs and 0.15 million model parameters, remarkably outperforming SOTA competitors in computational efficiency and storage resources. © 1999-2

关键词： Information leakage

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Variable Reconstruction for Evolutionary Expensive Large-Scale Multiobjective Optimization and Its Application on Aerodynamic Design

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IEEE-CAA JOURNAL OF AUTOMATICA SINICA 2025年第4期12卷 719-733页

作者： Lin, Jianqing He, Cheng Tian, Ye Pan, Linqiang Huazhong Univ Sci & Technol Sch Artificial Intelligence & Automation Key Lab Image Informat Proc & Intelligent Control Educ Minist China Wuhan 430074 Peoples R China Huazhong Univ Sci & Technol Sch Elect & Elect Engn Wuhan 430074 Peoples R China Anhui Univ Sch Comp Sci & Technol Hefei 230601 Peoples R China

Expensive multiobjective optimization problems (EMOPs) are complex optimization problems exacted from real-world applications, where each objective function evaluation (FE) involves expensive computations or physical experiments. Many surrogate-assisted evolutionary algorithms (SAEAs) have been designed to solve EMOPs. Nevertheless, EMOPs with large-scale decision variables remain challenging for existing SAEAs, leading to difficulties in maintaining convergence and diversity. To address this deficiency, we proposed a variable reconstruction-based SAEA (VREA) to balance convergence enhancement and diversity maintenance. Generally, a cluster-based variable reconstruction strategy reconstructs the original large-scale decision variables into low-dimensional weight variables. Thus, the population can be rapidly pushed towards the Pareto set (PS) by optimizing low-dimensional weight variables with the assistance of surrogate models. Population diversity is improved due to the cluster-based variable reconstruction strategy. An adaptive search step size strategy is proposed to balance exploration and exploitation further. Experimental comparisons with four state-of-the-art SAEAs are conducted on benchmark EMOPs with up to 1000 decision variables and an aerodynamic design task. Experimental results demonstrate that VREA obtains well-converged and diverse solutions with limited real FEs.

关键词： Optimization Computational modeling Iron Convergence Linear programming Predictive models Particle swarm optimization Kernel Costs Clustering algorithms Aerodynamic design large-scale optimization multiobjective evolutionary algorithm surrogate model variable reconstruction

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