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arXiv 2020年

作者： Zheng, Shiqi Shi, Peng Agarwal, Ramesh K. Lim, Chee Peng School of Automation China University of Geosciences Wuhan430074 China Hubei key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan430074 China School of Electrical and Electronic Engineering University of Adelaide AdelaideSA5005 Australia Department of Mechanical Engineering Washington University Box 1185 St Louis CampusMO63130 United States Institute for Intelligent Systems Research and Innovation Deakin University Australia

This study considers the problem of periodic event-triggered (PET) cooperative output regulation for a class of linear multi-agent systems. The advantage of the PET output regulation is that the data transmission and triggered condition are only needed to be monitored at discrete sampling instants. It is assumed that only a small number of agents can have access to the system matrix and states of the leader. Meanwhile, the PET mechanism is considered not only in the communication between various agents, but also in the sensorto-controller and controller-to-actuator transmission channels for each agent. The above problem set-up will bring some challenges to the controller design and stability analysis. Based on a novel PET distributed observer, a PET dynamic output feedback control method is developed for each follower. Compared with the existing works, our method can naturally exclude the Zeno behavior, and the inter-event time becomes multiples of the sampling period. Furthermore, for every follower, the minimum inter-event time can be determined a prior, and computed directly without the knowledge of the leader information. An example is given to verify and illustrate the effectiveness of the new design scheme. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Nonlinear-Periodic control system for Non-Affine Stationary Plant with Statement Delay

Nonlinear-Periodic Control System for Non-Affine Stationary ...

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2018 International Multi-Conference on Industrial engineering and Modern Technologies, FarEastCon 2018

作者： Eremin, E.L. Shelenok, E.A. Information and Control Systems Department Amur State University Blagoveshchensk Russia Automation and System Engineering Department Pacific National University Khabarovsk Russia

ISBN: (纸本)9781538695357

The article deals with the problem of synthesis of nonlinear regulator of control system for non-affine stationary plant with known constant statement delay. The plant is functions in periodic modes in the presence of constantly acting external perturbations and parametric uncertainty. As solution methods the hyperstability criterion, the fast-acting dynamic corrector, and L-dissipativity conditions are used. The key stage of the synthesis is the receipt for V. M. Popov's inequality special integral estimates that are ensure the fulfillment of the control goal. In final part of the article with the help of simulation the dynamic processes taking place in the proposed management system, which indicate its high quality are being visually illustrated. © 2018 IEEE.

关键词： control system synthesis

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Anchor-based spatio-temporal attention 3D convolutional networks for dynamic 3D point cloud sequences

arXiv

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arXiv 2020年

作者： Wang, Guangming Chen, Muyao Liu, Hanwen Yang, Yehui Liu, Zhe Wang, Hesheng The Department of Automation Institute of Medical Robotics Key Laboratory of System Control and Information Processing Ministry of Education Key Laboratory of Marine Intelligent Equipment System of Ministry of Education Shanghai Jiao Tong University Shanghai200240 China Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology China The Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai200240 China The Department of Computer Science and Technology University of Cambridge

With the rapid development of measurwement technology, LiDAR and depth cameras are widely used in the perception of the 3D environment. Recent learning based methods for robot perception most focus on the image or video, but deep learning methods for dynamic 3D point cloud sequences are underexplored. Therefore, developing efficient and accurate perception method compatible with these advanced instruments is pivotal to autonomous driving and service robots. An Anchor-based Spatio-Temporal Attention 3D Convolution operation (ASTA3DConv) is proposed in this paper to process dynamic 3D point cloud sequences. The proposed convolution operation builds a regular receptive field around each point by setting several virtual anchors around each point. The features of neighborhood points are firstly aggregated to each anchor based on the spatio-temporal attention mechanism. Then, anchor-based 3D convolution is adopted to aggregate these anchors' features to the core points. The proposed method makes better use of the structured information within the local region and learns spatio-temporal embedding features from dynamic 3D point cloud sequences. Anchor-based Spatio-Temporal Attention 3D Convolutional Neural Networks (ASTA3DCNNs) are built for classification and segmentation tasks based on the proposed ASTA3DConv and evaluated on action recognition and semantic segmentation tasks. The experiments and ablation studies on MSRAction3D and Synthia datasets demonstrate the superior performance and effectiveness of our method for dynamic 3D point cloud sequences. Our method achieves the state-of-the-art performance among the methods with dynamic 3D point cloud sequences as input on MSRAction3D and Synthia datasets. Copyright © 2020, The Authors. All rights reserved.

关键词： Embeddings

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Reliability Analysis of Assembly Processes Performed by Human-Robot Interaction

Reliability Analysis of Assembly Processes Performed by Huma...

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International Symposium on Multidisciplinary Studies and Innovative Technologies (ISMSIT)

作者： Mustafa Çoban Özgür Turay Kaymakçı Gökhan Gelen Department of Mechatronics Engineering Bursa Technical University Bursa Turkey Faculty of Electric Electronic Control and Automation Engineering Yıldız Technical University İstanbul Turkey

Together with innovations in robot technologies and the emergence of the fourth industrial revolution called Industry 4.0, collaborative robot applications have improved. Collaborative robots are the robots that provide the safe handling of many processes such as assembly, pick and place, palletizing in factories. The reliability analysis of the system has great importance in order to determine the failure conditions and failure possibilities that will occur in the systems enabling these operations. In this study, reliability analysis of assembly processes performed by human-robot interaction is presented. The reliability block diagram of the system is created and the reliability value of the system over time is determined. Then, Markov model indicating the fault conditions in the system is created and the probability of occurrence of these fault conditions is determined. The results show that if the system operates continuously for five years, the reliability will drop below 10% and the reasons that decrease the reliability are discussed in the last section.

关键词： Reliability Service robots Safety Robotic assembly Sensors Relays

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Online Supervisory control of Networked Discrete-Event systems with control Delays

Online Supervisory Control of Networked Discrete-Event Syste...

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IEEE Annual Conference on Decision and control

作者： Zhaocong Liu Xiang Yin Shaolong Shu Shaoyuan Li Department of Automation and Key Laboratory of System Control and Information Processing Shanghai Jiao Tong University China School of Electronics and Information Engineering Tongji University China

ISBN: (数字)9781728113982

ISBN: (纸本)9781728113999

We investigate state estimation and safe controller synthesis for networked discrete-event systems (DES), where supervisors send control decisions to plants via communication channels subject to communication delays. Previous works on state estimation of networked DES are based on the open-loop system without utilizing the knowledge of the control policy. In this paper, we propose a new approach for online estimation and control of networked DES with control delays. We first propose a new state estimation algorithm for the closed-loop system utilizing the information of control decision history. Then we investigate how to predict the effect of control delays in order to calculate a control decision online at each instant. We show that the proposed online supervisor can be updated effectively and the resulting closed-loop behavior is safe.

关键词： Delays Supervisory control State estimation Safety Closed loop systems Discrete-event systems

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Local Pose optimization with an Attention-based Neural Network

Local Pose optimization with an Attention-based Neural Netwo...

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2019 IEEE/RSJ International Conference on Intelligent Robots and systems (IROS)

作者： Yiling Liu Hesheng Wang Fan Xu Yong Wang Weidong Chen Qirong Tang Department of Automation Shanghai Jiao Tong University Shanghai China State Key Laboratory of Robotics and System (HIT) Beijing Institute of Control Engineering Tongii University

In this paper, we propose a novel pose optimizer which can be inserted into either supervised or unsupervised end-to-end visual odometry for the purpose of local pose optimization. The pose optimizer is an analogue of the pose graph optimization used in traditional VSLAM algorithms. Local pose optimization is performed by an attention-based neural network which iteratively refines the predicted pose estimates of an image snippet. Instead of complicated graph convolutional network, the attention mechanism based on geometric consistency of trajectory constraint is utilized because pose features whose spatial distribution is not important can be flattened to vectors and then processed. The pose optimizer is aimed at improving pose estimation accuracy by redistributing errors of pose estimates. Quantitative and qualitative evaluation of the proposed approach on the KITTI Odometry dataset [1] is presented to demonstrate its effectiveness in improving pose estimation accuracy and minimizing pose drift.

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Performance of different threshold estimation methods on SEMG wavelet de-noising in prolonged fatigue identification

Performance of different threshold estimation methods on SEM...

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2018 IEEE EMBS Conference on Biomedical engineering and Sciences, IECBES 2018

作者： Jamaluddin, Fauzani N Ahmad, Siti A Mohd Noor, Samsul Bahari Hassan, Wan Zuha Wan Shair, E.F. Malaysia Control System and Signal Processing Group Australia Department of Electrical and Electronic Engineering Faculty of Engineering Universiti Putra Malaysia Serdang Malaysia

ISBN: (纸本)9781538624715

Surface electromyography (SEMG) signals are widely used in fatigue identification. Fatigue after high intensity exercise and sports training needs to be balanced with rest to allow biochemical reactions during sports activity to return to a normal level. Inadequate rest leads to prolonged fatigue (PF) conditions such as musculoskeletal disorder, unexplained lethargy and performance decrement. Continuous sports training under these conditions may lead to injury. Fatigue identification at this stage is crucial since changes in amplitude and frequency of SEMG may determine whether the player is under normal fatigue (NF) or PF condition. During data collection, there are many interferences and noises which can reduce signal to noise ratio (SNR) of SEMG and affect PF detection. This paper pre-processed SEMG signals using Stationary Wavelet Transform (SWT) ‘db’ 45 with different threshold (Th) estimation techniques of de-noising such as RigRSURE, HeurSURE, minimax, universal threshold and a new estimation of threshold method which is based on a baseline of SEMG decomposition details. Naïve Bayes classification results using time and frequency features indicate that the new estimation of threshold method have the highest accuracy (98%), compared to RigRSURE (85%), HuerSURE (68%), Universal Threshold (74%) and minimax (76%). © 2018 IEEE

关键词： Signal to noise ratio

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Dexterous Manipulation through Imitation Learning: A Survey

arXiv

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arXiv 2025年

作者： An, Shan Meng, Ziyu Tang, Chao Zhou, Yuning Liu, Tengyu Ding, Fangqiang Zhang, Shufang Mu, Yao Song, Ran Zhang, Wei Hou, Zeng-Guang Zhang, Hong School of Electrical and Information Engineering Tianjin University Tianjin300072 China School of Control Science and Engineering Shandong University Jinan250061 China State Key Laboratory of General Artificial Intelligence Beijing100086 China Department of Mechanical and Process Engineering ETH Zurich Zurich8092 Switzerland Department of Electronic and Electrical Engineering Southern University of Science and Technology Shenzhen518055 China School of Informatics University of Edinburgh EH8 9AB United Kingdom Department of Computer Science University of Hong Kong 999077 Hong Kong State Key Laboratory of Multimodal Artificial Intelligence Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China School of Artificial Intelligence University of Chinese Academy of Sciences Beijing100049 China CASIA-MUST Joint Laboratory of Intelligence Science and Technology Institute of Systems Engineering Macau University of Science and Technology 999078 China

Dexterous manipulation, which refers to the ability of a robotic hand or multi-fingered end-effector to skillfully control, reorient, and manipulate objects through precise, coordinated finger movements and adaptive force modulation, enables complex interactions similar to human hand dexterity. With recent advances in robotics and machine learning, there is a growing demand for these systems to operate in complex and unstructured environments. Traditional model-based approaches struggle to generalize across tasks and object variations due to the high-dimensionality and complex contact dynamics of dexterous manipulation. Although model-free methods such as reinforcement learning (RL) show promise, they require extensive training, large-scale interaction data, and carefully designed rewards for stability and effectiveness. Imitation learning (IL) offers an alternative by allowing robots to acquire dexterous manipulation skills directly from expert demonstrations, capturing fine-grained coordination and contact dynamics while bypassing the need for explicit modeling and large-scale trial-and-error. This survey provides an overview of dexterous manipulation methods based on imitation learning (IL), details recent advances, and addresses key challenges in the field. Additionally, it explores potential research directions to enhance IL-driven dexterous manipulation. Our goal is to offer researchers and practitioners a comprehensive introduction to this rapidly evolving domain. Copyright © 2025, The Authors. All rights reserved.

关键词： Grippers

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Defining digital quadruplets in the cyber-physical-social space for parallel driving

arXiv

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arXiv 2020年

作者： Liu, Teng Xing, Yang Chen, Long Cao, Dongpu Wang, Fei-Yue Vehicle Intelligence Pioneers Inc Shandong Qingdao266109 China Qingdao Academy of Intelligent Industries QingdaoShandong266109 China Department of Mechanical and Mechatronics Engineering University of Waterloo N2L 3G1 Canada State Key Laboratory of Management and Control for Complex System Institute of Automation Beijing China

Parallel driving is a novel framework to synthesize the vehicle intelligence and transport automation. This article aims to define the digital quadruplets in parallel driving. In the cyber-physical-social systems (CPSS), based on the ACP method, the names of the digital quadruplets are first given, which are descriptive, predictive, prescriptive and real vehicles. The objectives of the three virtual digital vehicles are interacting, guiding, simulating and improving with the real vehicles. Then, the three virtual components of the digital quadruplets are introduced in detail and their applications are also illustrated. Finally, the real vehicles in parallel driving system and the research process of the digital quadruplets are depicted. The presented digital quadruplets in parallel driving are expected to make the future connected automated driving safety, efficiently and synergistically. Copyright © 2020, The Authors. All rights reserved.

关键词： Vehicles

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Event-triggered control for a class of second-order uncertain p-normal nonlinear systems

Event-triggered control for a class of second-order uncertai...

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第三十八届中国控制会议

作者： Wei Jiang Ting Li Zhenhua Zhao Department of Electronic Information Wuxi Vocational Institute of Arts & Technology the School of Automation Southeast University Key Laboratory of Measurement and Control of CSE Ministry of Education College of Automation Engineering Nanjing University of Aeronautics and Astronautics

The problem of event-triggered control for a class of second-order uncertain nonlinear systems subject to p-norm is investigated in this paper. A novel in this paper is that the input-to-state stability(ISS) assumption is removed. By adding a power integrator technique, we design a virtual control signal to address the uncertainties and nonlinearities of nonlinear *** rigorous stability analysis, all the signals of the closed-loop system are proven to be globally uniformly bounded and can converge to an arbitrarily small set which can be be adjusted by one parameter. A numerical example demonstrates the effectiveness of the designed scheme.

关键词： Event-triggered control uncertain nonlinear systems p-norm adding a power integrator technique

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