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Fixed-Time Consensus-Based Nash Equilibrium Seeking

IEEE/CAA Journal of Automatica Sinica 2024年第1期11卷 267-269页

作者： Mengwei Sun Jian Liu Lu Ren Changyin Sun the Institutes of Physical Science and Information Technology Anhui UniversityHefei 230601China IEEE the School of Automation and the Key Laboratory of Measurement and Control of Complex System of Engineering Ministry of EducationSoutheast UniversityNanjing 210096China the School of Artificial Intelligence and the Engineering Research Center of Autonomous Unmanned System Technology Ministry of EducationAnhui UniversityHefei 230601China

Dear Editor,This letter examines the fixed-time stability of the Nash equilibrium(NE)in non-cooperative *** propose a consensus-based NE seeking algorithm for situations where players do not have perfect information and communicate via a topology *** proposed algorithm can achieve NE in a fixed time that does not depend on initial conditions and can be adjusted in advance.

关键词： Fixed seeking letter

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AirVista: Empowering UAVs with 3D Spatial Reasoning Abilities Through a Multimodal Large Language Model Agent 27

AirVista: Empowering UAVs with 3D Spatial Reasoning Abilitie...

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27th IEEE International Conference on Intelligent Transportation systems, ITSC 2024

作者： Lin, Fei Tian, Yonglin Wang, Yunzhe Zhang, Tengchao Zhang, Xinyuan Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Capital University of Economics and Business Beijing100070 China University of Chinese Academy of Sciences Department of Artificial Intelligence Beijing100049 China State Key Laboratory for Management and Control of Complex Systems Chinese Academy of Sciences Beijing100190 China Macau University of Science and Technology Faculty of Innovation Engineering Department of Engineering Science 999078 China

ISBN: (纸本)9798331505929

In urban environments, complex transportation demands, including land, air, and maritime transport, are increasingly growing. While significant advancements have been made in land transportation and autonomous driving, research on urban air mobility (UAM) systems is still in its early stages. This paper presents an innovative urban air unmanned aerial vehicle (UAV) framework: AirVista, which is designed and built based on the Artificial systems, Computational experiments, and Parallel execution (ACP) approach, integrated with a multimodal large language model (MLLM) agent. Considering that UAM tasks often require UAVs to possess fine-grained spatial perception and reasoning capabilities, and given that existing MLLMs are somewhat lacking in exploring 3D spaces, this paper further proposes an instruction fine-tuning strategy integrated with 3D spatial knowledge, which has been validated experimentally for its effectiveness. Additionally, to enhance the understanding of the efficiency of MLLM for UAV tasks, this paper delves into prompt fine-tuning templates tailored for UAV task decomposition. Through experimental demonstrations, we showcase that the prompt-tuned MLLM exhibits efficient task decomposition and execution capabilities in handling complex UAV tasks. © 2024 IEEE.

关键词： Unmanned aerial vehicles (UAV)

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Simulation and optimization of inchworm-like pneumatic crawling actuator based on ABAQUS software 7

Simulation and optimization of inchworm-like pneumatic crawl...

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7th International Conference on Robotics, control and Automation engineering, RCAE 2024

作者： Mu, Junqi Zong, Xiaofeng Wei, Yiyang Hou, Xuping China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education School of Automation Wuhan430074 China

ISBN: (纸本)9798350355642

The actuator, serving as the fundamental power source of a soft robot, functions as its central component. The field of soft robotics has garnered increasing research attention since its inception. Pneumatic crawling robots, being an essential branch within the realm of soft robotics, possess notable characteristics such as rapid response time, cost-effectiveness, and human-computer interaction safety. Consequently, they hold significant research value. Among various types of crawling robots that have garnered considerable interest from researchers is the inchworm crawling robot. This paper aims to address the design and development aspects pertaining to inchworm actuators. By utilizing ABAQUS simulation software and taking displacement as the reference parameter, an analysis was conducted to investigate the impact of various geometric parameters on actuator displacement. Additionally, optimization of these geometric parameters was performed. The values of aspect ratio, length-to-width ratio, vertex angle and gap depth suitable for inchworm-like actuator are obtained. These findings are presented for the first time in the field of crawling soft robots and provide a theoretical basis for the development of pneumatic inchworm-like actuators. © 2024 IEEE.

关键词： Aspect ratio

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Multi-UAV Coverage Path Planning Method Based on Improved Particle Swarm Optimization

Multi-UAV Coverage Path Planning Method Based on Improved Pa...

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2024 China Automation Congress, CAC 2024

作者： Zhou, Yan Xiong, Yonghua School of Automation China University of Geosciences Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan430074 China

ISBN: (纸本)9798350368604

The widespread application of unmanned aerial vehicle (UAV) has made the coverage path planning problem for multiple UAV systems a research hotspot. In this paper, we propose a multi-UAV solution to achieve complete coverage of multi-region. Based on this solution, we present an improved particle swarm optimization (PSO) algorithm that combines PSO algorithm, greedy strategy, and back-and-forth (BAF) algorithm. Its purpose is to plan the optimal paths for multi-UAV while achieving the shortest total distance and the highest UAV cooperation efficiency with the minimum number of UAVs, thereby enhancing the multi-UAV coverage cooperation and path optimization capabilities. Simulation results demonstrate the feasibility and superiority of this algorithm. © 2024 IEEE.

关键词： Particle swarm optimization (PSO)

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Design and Performance Analysis of a Series-Parallel Self-Aligning Index Finger Exoskeleton

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IEEE Robotics and Automation Letters 2025年第6期10卷 6456-6463页

作者： Sun, Ning Wang, Zelong Cheng, Long Li, Houcheng Niu, Ben Sun, Xijin Li, Ke Shandong Normal University School of Information Science and Engineering Jinan China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing China University of Chinese Academy of Sciences School of Artificial Intelligence Beijing China Shandong University Institute of Intelligent Medical Engineering School of Control Science and Engineering Jinan China

Hand exoskeletons have become increasingly crucial for the rehabilitation of hand function, as relevant studies have shown that using the exoskeletons to assist in rehabilitation training can improve hand motor function. However, developing a human-robot kinematic compatibility exoskeleton while providing sufficient assistance torque is still a challenge. This paper develops a series-parallel self-aligning index finger exoskeleton to assist the index finger in flexion/extension and adduction/abduction training. A series-parallel mechanism driven by two motors simultaneously was proposed for the metacarpophalangeal (MCP) joint, which can ensure human-robot joint axes self-alignment and increase the joint assistance torque. A kinematic compatibility analysis method was proposed, and the kinematic compatibility of the series-parallel mechanism was analyzed. The degrees of freedom and forward kinematics of the proposed mechanism were analyzed, and its workspace was calculated, which results show that the motion range of the MCP joint can meet the grasping training requirements. Preliminary experiments were carried out, and the results indicate that the motion trajectory coefficients of the marker points at the MCP, PIP, and DIP joints averaged for all subjects with and without the proposed exoskeleton are 0.993, 0.956, and 0.939, respectively, which can verify the kinematic transparency of the proposed mechanism. The assistance torque generated by the proposed mechanism on the MCP joint can meet the joint assistance torque requirements. In a word, the proposed exoskeleton can achieve flexion/extension and adduction/abduction training, human-robot joint axes self-alignment, and provide sufficient assistance torque. © 2016 IEEE.

关键词： Exoskeleton (Robotics)

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Adaptive Cooperative Estimation and Guidance Against Unknown Maneuvering Target

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IEEE Transactions on Aerospace and Electronic systems 2025年

作者： Liu, Tianrun Chen, Yang-Yang Li, Shihua Southeast University School of Automation Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Nanjing210096 China Advanced Ocean Institute of Southeast University Nantong226000 China

A critical challenge in missile guidance is the frequent inaccessibility of essential target information by on-board seekers. This paper studies the three-dimensional cooperative guidance issue of multiple missiles simultaneously attacking an unknown maneuvering target. Different from most existing research, the pitch and yaw lead angles of a maneuvering target are entirely unknown, while the position and velocity information is only accessible to neighboring missiles. An adaptive distributed estimator is designed to estimate the target information over a directed communication network, generating a transmitted target with similar maneuverability to the actual target for each missile. Boundedness of the estimation errors are guaranteed within a prescribed time. Subsequently, a modified guidance law that integrates proportional navigation (PN) and coordination components is developed for simultaneously tracking the trajectories of the transmitted targets. The superiority of the developed adaptive cooperative estimation and guidance approach is confirmed through simulations. © 1965-2011 IEEE.

关键词： adaptive estimate Cooperative guidance maneuvering target prescribed-time three-dimensional

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Robust Speed Regulation of PMSM under Disturbances and Noises using Composite Model Predictive control

Robust Speed Regulation of PMSM under Disturbances and Noise...

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第42届中国控制会议

作者： Linxuan Mao Jinya Su Shihua Li School of Automation Southeast University Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University

This paper presents a single-loop Model Predictive control strategy that incorporates a reduced-order Generalized Proportional Integral Observe and a Kalman filter to enhance the speed regulation of Permanent Magnet Synchronous Motor systems in the presence of complex disturbances and measurement noises. The proposed controller design seamlessly integrates the predictive control, disturbance observer, and state filter components, and it was evaluated through simulation comparisons. The performance of the proposed method is evaluated using various metrics, including maximum velocity drop, recovery time, and variance of steady-state error, which demonstrate its superior response performance and anti-disturbance ability when compared to other existing methods without state filtering.

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Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal Location Module

Fall-LSTM: A Fall Detection Network Based on Spatio-Temporal...

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Chinese control Conference (CCC)

作者： Dapeng Xu Xiaobo Lu Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education School of Automation Southeast University Nanjing China

Fall events have unique dynamic features, which are not fully utilized by existing fall detection methods. Based on video understanding, we propose Fall-LSTM to learn such features pertinently without additional inputs. Fall-LSTM is composed of CNN-LSTM framework and two excitation modules i.e., Spatial Attention Module (SAM) and Temporal Location Module (TLM). SAM provides spatial constraints on motion for feature layers through foreground extraction and spatial pooling. TLM emphasizes frames with high probability of fall events to LSTM by inferring the rate and trend of motion in clips. Experimental results show that our proposed modules significantly improve the performance of LSTM model, outperforming the state-of-the-art methods on two public Fall Detection Datasets i.e., Le2i and UR.

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PMSM System Identification by Knowledge-informed Machine Learning

PMSM System Identification by Knowledge-informed Machine Lea...

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IEEE International Conference on Industrial Informatics (INDIN)

作者： Yue Yu Jiageng Tong Jinhui Xia Jinya Su Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (数字)9798331527471

ISBN: (纸本)9798331527488

Because of its excellent efficiency, compact dimen-sions, and accurate control features, Permanent Magnet Syn-chronous Motor (PMSM) are experiencing widespread applications across various industries. By accurately characterizing the dynamic behavior of PMSM systems through system identi-fication, engineers can ensure that PMSM motors reach their maximum potentials and meet the stringent requirements of modern industrial and technical systems while reducing energy consumption and maintenance costs. The traditional recursive least squares method is sensitive to noises, and unable to accu-rately identify parameters in complex environments. Pure data-driven models lack interpretability and require complex model architecture and computational costs. To this end, this work draws knowledge-informed neural ordinary differential equations (NODEs) for system identification, which embeds system prior knowledge into the NODEs for more efficient and accurate model learning. Comparative simulations show that this method not only obtains a higher-precision system model, but also significantly reduces the amount of training data and computation costs.

关键词： Accuracy Costs Uncertainty Computational modeling Noise Ordinary differential equations Motors Mathematical models Data models System identification

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Bézier-UKF Enhanced Incremental MPC Planner for Quadrotor Based Target Following

Bézier-UKF Enhanced Incremental MPC Planner for Quadrotor B...

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IEEE International Conference on Industrial Technology (ICIT)

作者： Haodi Zhang Jinya Su Shihua Li School of Automation Southeast University Nanjing China Key Laboratory of Measurement and Control of Complex Systems of Engineering Ministry of Education Southeast University Nanjing China

ISBN: (数字)9798350340266

ISBN: (纸本)9798350340273

This paper presents a vision-based tracking control for a quadrotor to follow a moving target without assuming any quadrotor-target communication. Constant turn rate & acceleration model (CTRA) is first drawn to describe the target's motion, allowing to infer unmeasurable target motion variables while mitigating the adverse effects of vision sensor noises through an unscented Kalman filter (UKF). Then the target's future trajectory is firstly predicted by using a Bézier curve, which is further treated as virtual observation of the CTRA model within the prediction horizon so that a better target trajectory prediction is derived by using the proposed Bézier- UKF fusion predictor method. The outputs of Bézier- UKF predictor are input into an incremental model predictive control (IMPC) planner as the target reference, enabling the derivation of the desired position, velocity and acceleration signal for the quadrotor. These signals are implemented by the low-level SE(3) geometric controller. Finally, we conduct a comparative study of the proposed method against baseline planners such as MPC and IMPC planners in high-fidelity AirSim simulation environment, demonstrating better target following performance.

关键词： Target tracking Noise Kinematics Predictive models Vision sensors Inspection Trajectory

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