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

作者： Hemjyoti Das Bjørn Kåre Sæbø Kristin Y. Pettersen Christian Ott Faculty of Electrical Engineering and Information Technology Automation and Control Institute (ACIN) Technical University of Vienna TU Wien Vienna Austria Department of Engineering Cybernetics Centre for Autonomous Marine Operations and Systems (NTNU AMOS) NTNU Norwegian University of Science and Technology Trondheim Norway German Aerospace Center Institute of Robotics and Mechatronics Wessling Germany

Hardware-in-the-loop simulation (HILS) allows a more realistic evaluation of control approaches than what is possible with pure software simulations, but without the actual complexity of the complete system. This is important for some complex systems such as orbital robots, where testing of the system is typically not possible after its launch, and an on-ground replica is used to validate the performance of such a system. In this article, an impedance-matching approach is presented to match the end-effector dynamics of a fixed-base robot manipulator with that of a target vehicle-manipulator system (VMS), while taking into account the redundant nullspace dynamics in a connected real-time simulation framework. This approach ensures that the forces and torques exerted by the system on the environment matches with that of the simulated system. The contact wrenches used in our approach are not obtained from numerical simulations, but rather from real physical interaction, which is one of the main advantages of our approach. The effectiveness of our method is validated by demonstrating various physical interaction tasks with the environment, using a suspended aerial manipulator as the target system.

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Spirometer and sEMG respiratory patterns for clinical decision support system

Spirometer and sEMG respiratory patterns for clinical decisi...

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IEEE Instrumentation and Measurement Technology Conference

作者： Amit Krishan Kumar Mansour H. Assaf Voicu Z. Groza Emil M. Petriu Faculty of Electrical-Electronic Engineering Duy Tan University Da Nang Vietnam Key Laboratory of Complex System Intelligent Control and Decision School of Automation Beijing Institute of Technology Beijing China School of Information Technology Engineering Mathematics and Physics The University of the South Pacific Suva Republic of Fiji School of Electrical Engineering and Computer Science University of Ottawa Ottawa Canada

To improve support system for subjects with respiratory ailments, this work analyses the respiratory patterns from spirometer and surface electromyography (sEMG). The patterns are integrated with risk and biochemical systems model to optimise the clinical decision support system (CDSS). The work considers terminal events for the spirometer and sEMG. The events and their associated patterns are correlated and projected on a hyperspace prior implementing it in decision support system. The proposed method shows that the different characteristics of breathing indicate some essential hidden information which when used as 4D scattered projection, optimises the decision making in CDSS. The analysis shows the effectiveness of bimodal respiratory patterns for different breathing capacities, which is promising for the modelled conditions.

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A K-Means Clustering-Based Optimization of IT2FL for Improved Regenerative Braking Performance

A K-Means Clustering-Based Optimization of IT2FL for Improve...

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Smart Mechatronics (ICSMech), IEEE International Conference on

作者： Muhammad Rizalul Wahid Endra Joelianto Bentang Arief Budiman Manida Tongroon Mulia Pratama Mahmudah Salwa Gianti Muhammad Fauzan Hernadi Mechatronics and Artificial Intelligence Universitas Pendidikan Indonesia Bandung Indonesia Instrumentation Control and Automation Research Group Institut Teknologi Bandung Bandung Indonesia Faculty of Mechanical and Aerospace Engineering Institut Teknologi Bandung Bandung Indonesia Department of Mechanical Engineering ATAE Research Unit Kasetsart University Sriracha Thailand Pusat Riset Mekatronika Cerdas Organisasi Riset Elektronika dan Informatika-BRIN Bandung Indonesia

ISBN: (数字)9798350368918

ISBN: (纸本)9798350368925

Optimizing regenerative braking systems in electric vehicles presents a complex challenge requiring precise and adaptable control. This research proposes employing K-Means Clustering to the Interval Type-2 Fuzzy Logic (IT2FL) membership functions, thereby improving overall regenerative braking efficiency and enhancing driving range. This research demonstrates that implementing a K-Means in the IT2FL control system in electric vehicles effectively recovers 35.84% of energy. By incorporating a K-means-based approach, the IT2FL controller further enhances vehicle range by 43 kilometers, achieving a total range of 108 kilometers. In comparison, an IT2FL system without K-means recovered only 26.67% of energy and achieved a total range of 93 kilometers. Notably, the IT2FL controller with K-means enabled the electric vehicle to attain an energy efficiency of 22 kilometers per kilowatt-hour. These findings underscore the significant improvement in maximum range offered by the IT2FL controller with K-means compared to alternative methods.

关键词： Fuzzy logic Energy consumption Electric potential Mechatronics Electric vehicles control systems Energy efficiency Optimization

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Time varying disturbance observer based on sliding mode control for active magnetic bearing system 2nd

Time varying disturbance observer based on sliding mode cont...

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2nd Annual International Conference on Material, Machines and Methods for Sustainable Development, MMMS 2020

作者： Giap, Van-Nam Huang, Shyh-Chour Nguyen, Quang Dich Trinh, Xuan Thang Department of Mechanical Engineering National Kaohsiung University of Science and Technology Kaohsiung80778 Taiwan Institute for Control Engineering and Automation Hanoi University of Science and Technology No. 1 Dai Co Viet Hai Ba Trung Hanoi100000 Viet Nam Faculty of Mechanical Engineering Hung Yen University of Technology and Education Hungyen160000 Viet Nam

ISBN: (纸本)9783030696092

This paper proposes a time varying disturbance observer for the active magnetic bearing system. The first derivative disturbance value was considered different to zero to show the effectiveness and originality of the proposed methodology. A novel disturbance observer form was constructed based on the basic nonlinear disturbance observer, which was combined with a proportional integral derivative sliding mode control for designing a control system. The disturbance estimation error was converged exponentially to the zero when the time goes to infinite. The output distance of the active magnetic bearing was closely converged to the desired trajectory. The Lyapunov law was used to analyses the convergent condition of the control system. Simulation results were used to prove the effectiveness of the proposed theory. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2021.

关键词： Active magnetic bearing system Sliding mode control Time varying disturbance observer

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A Numerical Study of Multiphase Flow Boiling Heat Transfer of Nanofluids in the Horizontal Metal Foam Tubes

SSRN

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SSRN 2023年

作者： Azizifar, Shahram Song, Mengjie Chao, Christopher Yu Hang Hosseini, Seyyed Hossein Pekař, Libor Faculty of Mechanical and Energy Engineering Shahid Beheshti University Tehran Iran Department of Energy and Power Engineering Beijing Institute of Technology Beijing China Department of Building Environment and Energy Engineering Department of Mechanical Engineering The Hong Kong Polytechnic University Hong Kong999077 Hong Kong Department of Chemical Engineering Ilam University Ilam69315-516 Iran Department of Automation and Control Engineering Faculty of Applied Informatics Tomas Bata University in Zlín Nad Stráněmi 4511 Zlín76005 Czech Republic

The study aims to numerically investigate the flow boiling of Al2O3/H2O and CuO/H2O nanofluids and water in pipes filled with copper metal foams. Four different values of porosity and three values of pore density have been used. To perform numerical simulation, the mixture model has been developed. Also, with the help of user-defined functions, the effects of nanoparticle deposition on the wettability of heating surfaces were considered. The thermal performance of metal foam pipes has been compared with each other by comparing the increase in heat transfer and pressure drop. Besides, the effect of metal foams with different porosities on the onset of nucleate boiling was evaluated. As a result, by reducing the porosity from 0.95 to 0.80, the heat transfer coefficient was increased by 59%, while the pressure drop increased by 28%. Finally, by comparing the increase in heat transfer and pressure drop, results show that the metal foam pipe with 80% porosity and 5 PPI has the best thermal performance. The results of this study are expected to be used for the optimization of advanced phase change cooling technologies. © 2023, The Authors. All rights reserved.

关键词： Pressure drop

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Analytical Center of Mass Trajectory Generation for Humanoid Walking and Running with Continuous Gait Transitions

Analytical Center of Mass Trajectory Generation for Humanoid...

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IEEE-RAS International Conference on Humanoid Robots

作者： Tobias Egle Johannes Englsberger Christian Ott Faculty of Electrical Engineering and Information Technology TU Wien Tobias Egle and Christian Ott are with the Automation and Control Institute Vienna Austria Institute of Robotics and Mecha-tronics German Aerospace Center (DLR) Wessling Germany

ISBN: (纸本)9798350309805

We present an analytical trajectory generation framework for the combined computation of multiple walking and running sequences with continuous gait transitions. This framework builds on the Divergent Component of Motion (DCM)-based walking algorithm and the spline-based trajec-tory generation of the Biologically Inspired Deadbeat (BID) control for running. We describe our approach to generating closed-form center of mass (CoM) trajectories for walking and running by alternately linking the two gaits through continuity constraints. Thereby, we distinguish between vertical and horizontal planning. The vertical trajectory is computed in a forward recursion from the first to the last gait sequence. Due to the coupling of the gait sequences in the horizontal direction, we show the efficient generation of the horizontal CoM trajectory in a single matrix calculation. Subsequently, we unify the control strategies using a DCM tracking controller for the complete trajectory and integrate the proposed framework into an inverse dynamics-based whole-body controller. Finally, the presented approaches are validated in simulations with the humanoid robot Toro.

关键词： Legged locomotion Couplings Humanoid robots Biology Trajectory Planning Splines (mathematics)

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Peak Time-Windowed Mean Estimation using Convex Optimization

Peak Time-Windowed Mean Estimation using Convex Optimization

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IEEE Conference on Decision and control

作者： Jared Miller Niklas Schmid Matteo Tacchi Didier Henrion Roy S. Smith Department of Information Technology and Electrical Engineering (D-ITET) ETH Zürich Physikstrasse 3 Automatic Control Laboratory (IfA) and NCCR Automation Zürich Switzerland Univ. Grenoble Alpes CNRS Grenoble INP (Institute of Engineering Univ. Grenoble Alpes) GIPSA-lab Grenoble France LAAS-CNRS Université de Toulouse CNRS Toulouse France and the Faculty of Electrical Engineering Czech Technical University in Prague Czech Republic

ISBN: (数字)9798350316339

ISBN: (纸本)9798350316346

This paper presents an algorithmic approach towards bounding the peak time-windowed average value attained by a state function along trajectories of a dynamical system. An example includes the maximum average current flowing across a power line in any 5 -minute window. The peak time-windowed mean estimation task may be posed as a finite-dimensional but nonconvex optimization problem in terms of an initial condition and stopping time. This problem can be lifted into an infinite-dimensional linear program in occupation measures, where no conservatism is introduced under compactness and dynamical regularity assumptions. The peak time-windowed mean estimation linear program is in turn truncated into a convergent sequence of semidefinite programs using the moment-Sum-of-Squares hierarchy. Bounds of the time-windowed mean are computed for example systems.

关键词： Heuristic algorithms Current measurement Estimation Convex functions Trajectory Dynamical systems Optimization

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Fault Detection and Isolation for Multi-agent Systems Under Event-Triggered Communication: A Zonotopic Joint Estimation Method

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IEEE Internet of Things Journal 2025年

作者： Tian, Mingliang Guo, Zhihua Wang, Xing Niu, Ben Wang, Xinjun Wang, Ding Wang, Huanqing Shandong Normal University School of Information Science and Engineering Jinan250014 China Beijing University of Technology Faculty of Information Technology Beijing100124 China Chinese Academy of Sciences State Key Laboratory of Management and Control for Complex Systems Institute of Automation Beijing100190 China Bohai University Department of Mathematical Science AndAutomatization Institute Jinzhou121000 China

This paper investigates the fault detection and isolation problem of a class of leader-follower multi-agent systems subject to unknown-but-bounded disturbances under an event-triggered communication mechanism (ETCM). Firstly, an adaptive ETCM is proposed to avoid the continuous acquisition of outputs from neighboring agents, thereby reducing the communication burden. Secondly, a joint state and fault observer is designed, and H∞ analysis is utilized to improve the robustness of the observer against external disturbances and event-triggered errors. Next, zonotopic reachability analysis is utilized to derive the estimated intervals of the system state and fault signal, based on which a fault detection and isolation method is developed to determine both when the system is faulty and which agent is at fault. Finally, a fighter formation model is employed to verify the effectiveness of the proposed approach. © 2014 IEEE.

关键词： Multi agent systems

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Traffic Flow Estimation using Graph Neural Network with Aggregation of Traffic Features

Traffic Flow Estimation using Graph Neural Network with Aggr...

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International Conference on control, automation, Robotics and Vision (ICARCV)

作者： Adiyana Putri Ferio Brahmana Endra Joelianto Herman Y. Sutarto Engineering Physics Doctoral Program Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Artificial Intelligence Control and Automation Laboratory Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Instrumentation and Control Research Group Faculty of Industrial Technology Institut Teknologi Bandung Indonesia Department of Intelligent System PT. Pusat Riset Energi (PRE) Bandung Indonesia

ISBN: (纸本)9781665476881

The increasing vehicle volume every year affects the prediction of the traffic system. The purpose of predicting traffic flow is to estimate the lost data caused by sensor malfunctions due to connection disruptions or ages. In estimating traffic flow, obtaining and explaining the historical data from the nearest segment sensor is necessary. The graph model can describe the spatial relationship between segments by connecting nodes with edges. Graph Neural Network (GNN) has been used as a learning method to predict the traffic flow in the segment sensor. GNN gets input in the form of spatial data built through a graph model, and the features are traffic density, average vehicle speed, and delay time on the road network. This paper shows that GNN's capability performs better in extracting spatial features and predicting the traffic flow by aggregating the features through connectivity nodes and edges.

关键词： Learning systems Roads Estimation Feature extraction Robot sensing systems Graph neural networks Spatial databases

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Social manufacturing pattern in the intelligent reform of the shoes and clothing industry 1

Social manufacturing pattern in the intelligent reform of th...

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1st IEEE International Conference on Digital Twins and Parallel Intelligence, DTPI 2021

作者： Cao, Yansong Wang, Yutong Dai, Juwu Zhu, Xihao Wang, Fei-Yue Macau Institute of Systems Engineering Macau University of Science and Technology China Institute of Automation Chinese Academy of Sciences The State Key Laboratory for Management and Control of Complex Systems Beijing China Ningbo Sanbody Intelligent Technology Co. LTD Ningbo China University of Nottingham Faculty of Science and Engineering Ningbo China

ISBN: (纸本)9781665433372

Along with economic globalization, the shoes and clothing market is undergoing huge changes and is facing increasing individualized demands. To realize personalized customization, we propose a social manufacturing pattern for the shoes and clothing industry. On the customer side, we collect costumer information with the help of 3D scanning and virtual fitting. On the production side, we replace human labor with intelligent production equipment. On the enterprise management side, we construct a cloud platform to realize source maximization. Through this social manufacturing pattern, we expect to accelerate the intelligent reform of the shoes and clothing industry. © 2021 IEEE.

关键词： Shoe manufacture

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