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Robust Consensus of Perturbed Euler-Lagrange Agents with Unknown Disturbances

IFAC-PapersOnLine 2024年第6期58卷 190-195页

作者： Alexey Bobtsov Romeo Ortega Jose Guadalupe Romero Emmanuel Nuño Department of Control Systems and Robotics ITMO University Kronverkskiy av. 49 197101 Saint Petersburg Russia Departament of Electrical and Electronic Engineering ITAM Progreso Tizapán 1 04100 Ciudad de México México Department of Computer Science CUCEI University of Guadalajara 44430 Guadalajara Mexico

In this paper we consider the problems of leaderless consensus for networks of fully actuated Euler-Lagrange agents perturbed by unknown additive disturbances. The network is an undirected weighted graph with time delays. The proposed controller has a PD structure that incorporates, in a certainty-equivalent way, the estimate of the unknown disturbance. The design of the disturbance estimator proceeds along the following steps. First, the derivation of a regression equation, that turns out to be nonlinearly parameterized, but with an injective mapping. Second, we propose to use a recently introduced least-squares plus dynamic regressor extension algorithm that allows us to estimate the unknown frequencies imposing extremely weak excitation assumptions. In this way, we derive a sufficient condition on the proportional and derivative gains of the controller to ensure that the systems globally and asymptotically converge to a consensus position.

关键词： Robust adaptive control Multi-agent systems Disturbance rejection Robust time delay systems

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Exploring the Feasibility of Hybrid PV-Wind Energy Plant for Costal-Tourism Sites

Exploring the Feasibility of Hybrid PV-Wind Energy Plant for...

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IEEE Power India Conference

作者： Md Ashraful Islam Md Shahadat Hossenk Fareesa Firdouse Md. Zahid Hasan M M Naushad Ali Golla Suribabu Hayitov Abdulla Nurmatovich Valisher Sapaev Odilbek Uglu Dept of Electrical and Electronic Engineering Green University of Bangladesh Dhaka Bangladesh Department of Electrical and Computer Engineering Gannon University USA Department of Computer Science Engineering Keshav Memorial Institute Of Technology (KMIT) Hyderabad India Civil Engineering Department SRKR Engineering College (A) Bhimavaram A.P. India Department of Transports Systems Urgench State University Uzbekistan Department of General Professional Sciences Mamun University Khiva Uzbekistan

ISBN: (数字)9798350367065

ISBN: (纸本)9798350367072

This study presents the design, optimization, and performance analysis of a PV-Wind hybrid energy system for Kuakata, a coastal region and popular tourist destination in Bangladesh. The hybrid system integrates Vertical Axis Wind Turbines (VAWT) and photovoltaic (PV) technology, addressing both noise reduction and safety concerns, making it particularly suitable for tourist-friendly environments. The system was optimized using HOMER Pro simulation software, which provided the optimal configuration based on technical, economic, and environmental parameters. The results show a 100% renewable energy fraction, a Levelized Cost of Energy (LCOE) of $0.041/kWh, and a Net Present Cost (NPC) of $4.58 million. Additionally, the system demonstrates significant environmental benefits by reducing 230,680 kg of CO 2 emissions annually. This study highlights the feasibility of deploying a PV-Wind hybrid system in coastal regions to meet growing energy demands while promoting sustainability and environmental stewardship. The proposed design also enhances the attraction of Kuakata as a tourist destination by offering a quiet and safe renewable energy solution.

关键词： Photovoltaic systems Renewable energy sources Wind energy Sea measurements Hybrid power systems Software Wind turbines Safety Performance analysis Sustainable development

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Electric Vehicle Physical Parameters Identification 48

Electric Vehicle Physical Parameters Identification

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48th Annual Conference of the IEEE Industrial Electronics Society, IECON 2022

作者： Maia, Ricardo Mendes, Jerome Araujo, Rui University of Coimbra Institute of Systems and Robotics Department of Electrical and Computer Engineering Pólo II CoimbraPT-3030-290 Portugal Critical Software S.A. Pq. Ind. de Taveiro Lt 49 CoimbraPT-3045-504 Portugal

ISBN: (数字)9781665480253

ISBN: (纸本)9781665480253

Electric vehicle physical parameters highly influence the modeling of its different systems. Although a simulation using data acquired from field tests can have satisfactory results, the parameters inaccuracy, due to either insufficient information or wear, can prevent a better performance. In this paper, 10 electric vehicle physical parameters are adjusted/calibrated by three metaheuristic algorithms: Particle Swarm Optimization, Genetic Algorithms, and Simulated Annealing. Moreover, tests on real short and long distance data sets were used in order to validate the proposed framework to EV model calibration. The results achieved indicate that parameter calibration is effective in the reduction of the modeling error. © 2022 IEEE.

关键词： Simulated annealing

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Model-Free Predictive Control for Harmonic Suppression of PMSMs Based on Adaptive Resonant Controller

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IEEE Transactions on Energy Conversion 2025年

作者： Li, Teng Sun, Xiaodong Su, Zonghao Zha, Xuhao Dianov, Anton Prakht, Vladimir Demidova, Galina Ma, Jinlin Jiangsu University Automotive Engineering Research Institute Zhenjiang212013 China Wenzhou University Pingyang Institute of Intelligent Manufacturing Wenzhou325035 China Ural Federal University Department of Electrical Engineering Ekaterinburg620062 Russia ITMO University Faculty of Control Systems and Robotics Petersburg197101 Russia Jiangsu University School of Automotive and Traffic Engineering Zhenjiang212013 China

To simultaneously suppress the periodic and aperiodic disturbances experienced by permanent magnet synchronous motors in model predictive control, a model-free predictive current control with adaptive resonance control based on an ultra-local model is proposed. Firstly, the ultra-local models of the speed loop and the current loop are established respectively, and the unmodeled and uncertain unknown part F in the ultra-local model is estimated by using a high-order fast terminal sliding mode observer, and its stability is analyzed. Then, an adaptive resonant controller (ARC) is designed to suppress the periodic disturbance caused by the dead zone effect. The ARC and the model-free control based on the ultra-local model are combined to compensate for their respective shortcomings, achieving the suppression of periodic and aperiodic disturbances in the system. Finally, by comparing with the traditional duty cycle model predictive control and the model-free model predictive control without ARC, the proposed scheme is proved to be robust to periodic and aperiodic disturbances. © 2025 IEEE. All rights reserved.

关键词： Permanent magnets

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Reinforcement Learning-Based Optimal Multiple Waypoint Navigation

Reinforcement Learning-Based Optimal Multiple Waypoint Navig...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Christos Vlachos Panagiotis Rousseas Charalampos P. Bechlioulis Kostas J. Kyriakopoulos Department of Electrical and Computer Engineering University of Patras Greece School of Mechanical Engineering Control Systems Laboratory National Technical University of Athens Greece Center of AI & Robotics (CAIR) New York University Abu Dhabi

In this paper, a novel method based on Artificial Potential Field (APF) theory is presented, for optimal motion planning in fully-known, static workspaces, for multiple final goal configurations. Optimization is achieved through a Reinforcement Learning (RL) framework. More specifically, the parameters of the underlying potential field are adjusted through a policy gradient algorithm in order to minimize a cost function. The main novelty of the proposed scheme lies in the method that provides optimal policies for multiple final positions, in contrast to most existing methodologies that consider a single final configuration. An assessment of the optimality of our results is conducted by comparing our novel motion planning scheme against a RRT* method.

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An Image Acquisition Scheme for Visual Odometry based on Image Bracketing and Online Attribute Control

An Image Acquisition Scheme for Visual Odometry based on Ima...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Shuyang Zhang Jinhao He Bohuan Xue Jin Wu Pengyu Yin Jianhao Jiao Ming Liu Department of Electronic and Computer Engineering the Hong Kong University of Science and Technology Hong Kong SAR China Thrust of Robotics and Autonomous Systems the Hong Kong University of Science and Technology (Guangzhou) Guangzhou China Center for Advanced Robotics Technology Innovation (CARTIN) School of Electrical and Electronic Engineering Nanyang Technological University Singapore Department of Computer Science University College London London UK

ISBN: (数字)9798350384574

ISBN: (纸本)9798350384581

Visual odometry (VO) system is challenged by complex illumination environments. Image quality and its consistency in the time domain directly determine feature detection and tracking performance, which further affect the robustness and accuracy of the entire system. In this paper, an image acquisition scheme with image bracketing patterns is proposed. Images with different exposure levels are continuously captured to sufficiently explore the scene under varying illumination. An attribute control method is designed to adjust image exposures within the brackets online. Gaussian process regression fits the relationship between image quality metric and exposure via image synthesis technique. The optimal exposures for the next bracket are obtained directly without attempts to ensure a quick response. Experiments show our acquisition system’s effectiveness and performance improvement for VO tasks in complex illumination scenes.

关键词： Image quality Measurement Image synthesis Lighting Gaussian processes Robustness Time-domain analysis

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FAIR-FATE: Fair Federated Learning with Momentum

arXiv

引用

arXiv 2022年

作者： Salazar, Teresa Fernandes, Miguel Araújo, Helder Abreu, Pedro Henriques Centre for Informatics and Systems Department of Informatics Engineering of The University of Coimbra University of Coimbra Coimbra Portugal Institute of Systems and Robotics Department of Electrical and Computer Engineering of The University of Coimbra University of Coimbra Coimbra Portugal

While fairness-aware machine learning algorithms have been receiving increasing attention, the focus has been on centralized machine learning, leaving decentralized methods underexplored. Federated Learning is a decentralized form of machine learning where clients train local models with a server aggregating them to obtain a shared global model. Data heterogeneity amongst clients is a common characteristic of Federated Learning, which may induce or exacerbate discrimination of unprivileged groups defined by sensitive attributes such as race or gender. In this work we propose FAIR-FATE: a novel FAIR FederATEd Learning algorithm that aims to achieve group fairness while maintaining high utility via a fairness-aware aggregation method that computes the global model by taking into account the fairness of the clients. To achieve that, the global model update is computed by estimating a fair model update using a Momentum term that helps to overcome the oscillations of non-fair gradients. To the best of our knowledge, this is the first approach in machine learning that aims to achieve fairness using a fair Momentum estimate. Experimental results on real-world datasets demonstrate that FAIR-FATE outperforms state-of-the-art fair Federated Learning algorithms under different levels of data *** Codes 68T07 © 2022, CC BY.

关键词： Momentum

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A Consistency-Based Loss for Deep Odometry Through Uncertainty Propagation

A Consistency-Based Loss for Deep Odometry Through Uncertain...

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IEEE International Conference on robotics and Automation (ICRA)

作者： Hamed Damirchi Roohollah Khorrambakht Hamid D. Taghirad Behzad Moshiri Advanced Robotics and Automated Systems Faculty of Electrical Engineering K. N. Toosi University of Technology Tehran Iran Department of Electrical and Computer Engineering New York University New York USA School of ECE University College of Engineering University of Tehran Tehran Iran

Conventionally, deep odometry networks use objective functions that only penalize short-term deviations from the true path. Since such an objective does not impose any constraints on the long-term deviations from the path, a second consistency-based loss term may be added to lower long-term drift. However, maintaining a balance between the two loss terms is challenging and often treated as a design hyperparameter. To mitigate this balancing issue, we propose to use the uncertainty over both odometry and the long-term transformations in a maximum likelihood setting and allow the network to tune the weighting between the two loss terms. To this end, we derive the odometry uncertainty alongside the pose outputs using the network itself and to derive the covariance matrix over the integrated transformation, we propose to propagate the odometry uncertainty through each iteration. This formulation provides an adaptive and statistically consistent method to weigh the incremental and integrated loss terms against each other, noting the increase in uncertainty as more steps are integrated over. We show that our approach to consistency-based losses allows the network to surpass the accuracy of the state-of-the-art visual odometry approaches. Then, the efficacy of the derived uncertainty as weighting medium is visualized and the performance benefits of uncertainty quantification are shown in a pose-graph based localization scenario.

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Influence of Elasticity of Elements of Kinematic Chains of Drives of the Main Movement of Lathes on the Dynamics and Accuracy of Maintaining the Spindle Speed

Influence of Elasticity of Elements of Kinematic Chains of D...

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electrical engineering, Automation & Control systems, Theory and Practical Applications (EEACS), Seminar on

作者： Oleg A. Kundyukov Vladimir I. Korolev Mikhail P. Belov Kirill K. Ershov Department of Robotics of Automated Production Systems Saint Petersburg Electrotechnical University "LETI" Saint Petersburg Russia Department of Automated Electric Drive and Electrical Engineering Graduate School of Technology and Energy Saint Petersburg Russia

Analysis of the elasticity of the elements of the kinematic chains of the drives of the main movement of lathes has been carried out. The study of the influence of elasticity on the dynamics and accuracy of maintaining the speed was carried out in the mathematical environment of Matlab and Simulink. Recommendations for improving the accuracy of maintaining the speed are formulated.

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Producing Lunar Steel and Oxygen using Molten Lunar Regolith Electrolysis

Producing Lunar Steel and Oxygen using Molten Lunar Regolith...

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Accelerating Space Commerce, Exploration, and New Discovery Conference, ASCEND 2023

作者： Patel, Palak B. Soto, Jose Adams, Zachary K. Koller, Scarlett Latyshev, Kir Boothe, Evan Cooper, Amber Fontanez, Jonatan Jalil, Laman Ma, Beverly Meza, Cesar Misquitta, Kristoff Na, Hyein Nguyen, Tom Pendley, Hezekiah Sangabattula, Lokesh Usey, Helena Zehner, Alice Allanore, Antoine Culpepper, Martin De Weck, Olivier Lordos, George Hoffman, Jeffrey Bergman, Dean Department of Mechanical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology CambridgeMA02139 United States Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology CambridgeMA02139 United States Department of Aeronautics and Astronautics Massachusetts Institute of Technology Sloan School of Management CambridgeMA02139 United States Department of Chemical Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Department of Material Science and Engineering Massachusetts Institute of Technology CambridgeMA02139 United States Honeybee Robotics Exploration Systems AltadenaCA91001 United States

ISBN: (纸本)9781624107054

With the current Artemis missions planned, by 2028, NASA and its international and commercial partners may be establishing a permanent presence at the lunar South pole. The Artemis Base Camp will be the locus of international and public-private collaboration under the Artemis Accords, helping to bootstrap a lunar economy. As the lunar economy grows, traffic of people and goods will grow with it. Thus, we envision that NASA and its international and commercial partners will have increasing long-term needs for producing metal from in situ resources such as lunar regolith. These metals can be used to produce many end products on the moon including large pressure vessels, both for spacious habitats and industrial-scale storage and operations. In this paper, as a part of the NASA 2023 BIG Idea Challenge ‘Lunar Forge: Producing Metal Products on the Moon’, we design and manufacture a molten regolith electrolysis (MRE) reactor capable of producing various alloys of steel and other metal products from lunar regolith, with oxygen as a useful byproduct. We have built ARTEMIS Steelworks (Advancing Reactor Technologies for Electrolytic Manufacturing of In situ Steel), which consists of an electrolytic reactor, supporting the addition of alloying elements to produce molten steel from lunar regolith simulant. To prepare for a lunar technology demonstration, a preliminary test of the reaction on Earth was performed in a vacuum, a sonicator was tested to dislodge oxygen bubbles from the anode to increase electrode life, and an automated iron and slag collector was made to reduce the need for astronaut operation. The project’s technical objectives are to demonstrate steel-making capability while also quantifying energy efficiency, steel quality, and the expected useful life of the electrodes and vessel under different configurations relative to the state of the art. The comprehensive testing plan presented here includes functional subsystem and integrated testing in ambient conditio

关键词： Electrolysis

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