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Awareness in robotics: An early perspective from the viewpoint of the EIC Pathfinder Challenge "Awareness Inside"

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arXiv 2024年

作者： Santina, Cosimo Della Corbato, Carlos Hernandez Sisman, Burak Leiva, Luis A. Arapakis, Ioannis Vakalellis, Michalis Vanderdonckt, Jean D’Haro, LuisFernando Manzi, Guido Becchio, Cristina Elamrani, Aïda Alirezaei, Mohsen Castellano, Ginevra Dimarogonas, Dimos V. Ghosh, Arabinda Haesaert, Sofie Soudjani, Sadegh Stroeve, Sybert Verschure, Paul Bacciu, Davide Deroy, Ophelia Bahrami, Bahador Gallicchio, Claudio Hauert, Sabine Sanz, Ricardo Lanillos, Pablo Iacca, Giovanni Sigg, Stephan Gasulla, Manel Steels, Luc Sierra, Carles Department of Cognitive Robotics Delft University of Technology Delft Netherlands Oberpfaffenhofen Germany Department of Computer Science University of Luxembourg Luxembourg 4 Telefónica I+D Spain AEGIS IT Research GmbH Germany Université catholique de Louvain Belgium Speech Technology and Machine Learning Group ETSI de Telecomunicación Universidad Politécnica de Madrid Madrid Spain Alien Venture Studio Alien Technology Transfer Rome Italy Hamburg Germany Institut Jean Nicod École Normale Supérieure Paris France Research Technology and Development Department Digital Industry Software Helmond Netherlands Department of Information Technology Uppsala University Uppsala Sweden Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Max Planck Institute for Software Systems Kaiserslautern Germany Department of Electrical Engineering Control Systems Group Eindhoven University of Technology Eindhoven Netherlands Amsterdam Netherlands Donders Centre for Neuroscience Radboud University Nijmegen Netherlands Computer Science Department University of Pisa Pisa Italy Faculty of Philosophy Philosophy of Science The Study of Religion Ludwig Maximilian University of Munich Munich Germany School of Engineering Mathematics and Technology University of Bristol Bristol United Kingdom Autonomous Systems Laboratory Universidad Politécnica de Madrid Spain Madrid Spain Department of Information Engineering and Computer Science University of Trento Trento Italy Department of Information and Communications Engineering Aalto University Espoo Finland Department of Electronic Engineering Universitat Politècnica de Catalunya Barcelona Spain Studio Stelluti Brussels Belgium Barcelona Spain

Consciousness has been historically a heavily debated topic in engineering, science, and philosophy. On the contrary, awareness had less success in raising the interest of scholars in the past. However, things are changing as more and more researchers are getting interested in answering questions concerning what awareness is and how it can be artificially generated. The landscape is rapidly evolving, with multiple voices and interpretations of the concept being conceived and techniques being developed. The goal of this paper is to summarize and discuss the ones among these voices that are connected with projects funded by the EIC Pathfinder Challenge called "Awareness Inside", a nonrecurring call for proposals within Horizon Europe that was designed specifically for fostering research on natural and synthetic awareness. In this perspective, we dedicate special attention to challenges and promises of applying synthetic awareness in robotics, as the development of mature techniques in this new field is expected to have a special impact on generating more capable and trustworthy embodied systems. © 2024, CC BY.

关键词： Robotics

Domain decomposition and mortar mixed approach for nonlinear elliptic equations modeling flow in porous media

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Heliyon 2025年第4期11卷 e42724页

作者： Arshad, Muhammad Mehmood, Adil Salleh, Zabidin Akhtar, Sumaira Saleem Khan, Suliman Inc, Mustafa Department of Mathematics Abbottabad University of Science and Technology Abbottabad Pakistan Special Interest Group on Modelling and Data Analytics Faculty of Computer Science and Mathematics Universiti Malaysia Terengganu Kuala Nerus Terengganu 21030 Malaysia Department of Mathematics Women University Mardan Khyber Pakhtunkhwa Pakistan State Key Laboratory of Mechanics and Control for Aerospace Structures College of Aerospace Engineering Nanjing University of Aeronautics and Astronautics Nanjing 210016 China Department of Mathematıcs Firat University Elazig 23119 Türkiye Department of Mathematics Saveetha School of Engineering Saveetha Institute of Medical and Technical Sciences Saveetha University Tamil Nadu Chennai 602105 India Department of Computer Engineering Biruni University Istanbul 34010 Türkiye

The equations describe the behavior of steady state flow in porous medium generally results in elliptic partial differential equations with coefficient represents the permeability of the medium. This article presents the extension of mortar mixed method for second order nonlinear elliptic equations that describes flow in porous media. The domain is decomposed into non-overlapping regions with each partitioned independently. The grids on subdomains are allowed to be non-matching across the subdomains internal boundaries. The fixed point argument (FPA) is employed to establish the existence and uniqueness of discrete problem, and optimal order error estimates are provided for approximations. The computational results are given to validate the theory. © 2025 The Author(s)

关键词： Darcy law Existence Mixed methods Mortar methods Nonlinear equations Numerical results

Extended Horizon Predictive control for Software Defined Networked Microgrids

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SSRN

SSRN 2024年

作者： Guzmán, Ricardo Pérez Rivera, Marco Araya, Baldomero Gómez, Juan S. Salgueiro, Yamisleydi Restrepo, Carlos Wheeler, Patrick You, Minglei Sumner, Mark Department of Computer Science Faculty of Engineering Universidad de Talca Curicó Maule 3341717 Chile Power Electronics Machines and Control Research Group Faculty of Engineering University of Nottingham NottinghamNG7 2GT United Kingdom Laboratorio de Conversión de Energías y Electrónica de Potencia LCEEP Dirección de Investigación Universidad de Talca Curicó Maule 3341717 Chile Department of Electrical Engineering Faculty of Engineering Universidad de Talca Curicó Maule 3341717 Chile Department of Engineering Sciences The Energy Transformation Center Universidad Andrés Bello Santiago-Chile Santiago de Chile8370035 Chile Department of Industrial Engineering Faculty of Engineering Universidad de Talca Curicó Maule 3341717 Chile

This paper presents a model-based predictive control implementation (FCS-MPC) with extended horizon prediction to address the resiliency problem and voltage/frequency deviations for hierarchical microgrids. The proposed framework integrates Software-Defined Networking (SDN) as a set of microservices, where prediction models enable effective coordination and enhance system reliability by including communication constraints. The control strategy considers the variability of communication latency and packet loss to adjust the shared references based on the secondary control’s spatial and temporal correlation. The system is subjected to four test case scenarios to analyze the impact of communications in distributed generation, plugand-play capabilities, and load fluctuations on the microgrid. The proposed SDN-based framework enables the resolution of slow dynamic responses to parameter variations, by exploiting the advantages of FCS-MPC. The prediction block in the proposed secondary control outperforms traditional communication methods in terms of latency, recovery time, and packet loss among distributed energy resources, improving hierarchical microgrid performance. © 2024, The Authors. All rights reserved.

关键词： Software defined networking

Nonlinear Tracking and Rejection using Linear Parameter-Varying control

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arXiv 2021年

作者： Koelewijn, Patrick J.W. Tóth, Roland Nijmeijer, Henk Weiland, Siep Control Systems Group Department of Electrical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands Systems and Control Laboratory Institute for Computer Science and Control Budapest1111 Hungary Dynamics and Control Group Department of Mechanical Engineering Eindhoven University of Technology P.O. Box 513 Eindhoven5600 MB Netherlands

The Linear Parameter-Varying (LPV) framework has been introduced with the intention to provide stability and performance guarantees for analysis and controller synthesis for Nonlinear (NL) systems via convex methods. By extending results of the Linear Time-Invariant framework, mainly based on quadratic stability and performance using dissipativity theory, it has been assumed that they generalize tracking and disturbance rejection guarantees for NL systems. However, as has been shown in literature, stability and performance through standard dissipativity is not sufficient in order to satisfy the desired guarantees in case of reference tracking and disturbance rejection for nonlinear systems. We propose to solve this problem by the application of incremental dissipativity, which does ensure these specifications. A novel approach is proposed to synthesize and realize an NL controller which is able to guarantee incremental stability and performance for NL systems via convex optimization using methods from the LPV framework. Through simulations and experiments, the presented method is compared to standard LPV controller designs, showing significant performance improvements. Copyright © 2021, The Authors. All rights reserved.

关键词： Nonlinear systems

Sampled-data funnel control and its use for safe continual learning

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arXiv 2023年

作者： Lanza, Lukas Dennstädt, Dario Worthmann, Karl Schmitz, Philipp Şen, Gökçen Devlet Trenn, Stephan Schaller, Manuel Technische Universität Ilmenau Institute of Mathematics Optimization-based Control Group Ilmenau Germany Universität Paderborn Institut für Mathematik Paderborn Germany University of Groningen Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence Groningen Netherlands Istanbul Technical University Department of Control and Automation Engineering Istanbul Turkey Brandenburgische Technische Universität Cottbus-Senftenberg Fachgebiet Regelungssysteme und Netzleittechnik Cottbus Germany

We propose a novel sampled-data output-feedback controller for nonlinear systems of arbitrary relative degree that ensures reference tracking within prescribed error bounds. We provide explicit bounds on the maximum input signal and the required uniform sampling time. A key strength of this approach is its capability to serve as a safety filter for various learning-based controller designs, enabling the use of learning techniques in safety-critical applications. We illustrate its versatility by integrating it with two different controllers: a reinforcement learning controller and a non-parametric predictive controller based on Willems et al.’s fundamental lemma. Numerical simulations illustrate effectiveness of the combined controller design. © 2023, CC BY-NC-ND.

关键词： Predictive control systems

Data-driven output synchronization of heterogeneous leader-follower multi-agent systems

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arXiv 2021年

作者： Jiao, Junjie van Waarde, Henk J. Trentelman, Harry L. Camlibel, M. Kanat Hirche, Sandra The Chair of Information-oriented Control Department of Electrical and Computer Engineering Technical University of Munich Munich80333 Germany The Control Group Department of Engineering University of Cambridge Cambridge United Kingdom The Bernoulli Institute for Mathematics Computer Science and Artificial Intelligence University of Groningen Nijenborgh 9 Groningen9747 AG Netherlands

This paper deals with data-driven output synchronization for heterogeneous leader-follower linear multiagent systems. Given a multi-agent system that consists of one autonomous leader and a number of heterogeneous followers with external disturbances, we provide necessary and sufficient data-based conditions for output synchronization. We also provide a design method for obtaining such output synchronizing protocols directly from data. The results are then extended to the special case that the followers are disturbance-free. Finally, a simulation example is provided to illustrate our results. Copyright © 2021, The Authors. All rights reserved.

关键词： Multi agent systems

Learning Based Model Predictive control for Quadcopters with Dual Gaussian Process

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arXiv 2021年

作者： Liu, Yuhan Tóth, Roland The Harbin Institute of Technology Department of Control Science and Engineering Harbin China The Eindhoven University of Tech. Dep. of Electrical Eng. Control Systems Group Eindhoven Netherlands The Institute for Computer Science and Control Budapest Hungary

An important issue in quadcopter control is that an accurate dynamic model of the system is nonlinear, complex, and costly to obtain. This limits achievable control performance in practice. Gaussian process (GP) based estimation is an effective tool to learn unknown dynamics from input/output data. However, conventional GP-based control methods often ignore the computational cost associated with accumulating data during the operation of the system and how to handle forgetting in continuous adaption. In this paper, we present a novel Dual Gaussian Process (DGP) based model predictive control strategy that improves the performance of a quadcopter during trajectory tracking. The bio-inspired DGP structure is a combination of a long-term GP and a short-term GP, where the long-term GP is used to keep the learned knowledge in memory and the short-term GP is employed to rapidly compensate unknown dynamics during online operation. Furthermore, a novel recursive online update strategy for the short-term GP is proposed to successively improve the learnt model during online operation in an efficient way. Numerical simulations are used to demonstrate the effectiveness of the proposed strategy. © 2021, CC BY-NC-SA.

关键词： Model predictive control

Compensation Mechanisms for Double Auctions in Peer-to-Peer Local Energy Markets

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Current Sustainable/Renewable Energy Reports 2020年第4期7卷 165-175页

作者： Gerwin, Christoph Mieth, Robert Dvorkin, Yury Workgroup for Infrastructure Policy Technische Universität Berlin Straße des 17. Juni 135 Berlin10623 Germany Tandon School of Engineering Department of Electrical and Computer Engineering NYU BrooklynNY11201 United States Control Systems Group Technische Universität Berlin Einsteinufer 17 Berlin10587 Germany

Purpose of Review: This paper compares different double-auction pricing mechanisms in the context of peer-to-peer trading in local electricity markets. Benchmarking against the traditional system marginal price (SMP) approach, we analyze the outcomes of the Vickrey-Clarke-Groves (VCG) and Pay-as-bid (PAB) approaches, which lead to a revenue imbalance in the market. To mitigate this imbalance, we propose a set of mechanisms that impose trading fees or subsidies with different fairness policies and discuss their impact on the behavior of market participants. Recent Findings: Proliferation of small-scale and distributed energy resources in low-voltage distribution systems has spurred the development of platforms for peer-to-peer local electricity trading. While recent studies prove that local electricity trading can be beneficial to both the peers and system, implementation of local energy markets is still in the early stages and there is no consensus on an optimal market design. Summary: This paper provides a detailed description of market properties for a competitive LEM that is cleared using the SMP, VCG, and PAB approaches. We show that the proposed compensation mechanisms effectively enforce predefined fairness policies and derive exact payments for each peer depending on market results and individual peer characteristics. The case study uses real-world data to illustrate that different compensation mechanisms can be used to incentivize desirable peer behavior, e.g., installation of new distributed energy resources, investment in grid supportive generation, or flexible energy usage. © 2020, Springer Nature Switzerland AG.

关键词： Power markets

Corrigendum to "IoT application for energy poverty detection based on thermal comfort monitoring" [Heliyon 9 (1) (January 2023) Article e12943]

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Heliyon 2023年第3期9卷 e14128页

作者： Ascensión López-Vargas Agapito Ledezma-Espino Control Learning and Optimization Group Computer Science and Engineering Department University Carlos III of Madrid. Leganes Madrid Spain.

[This corrects the article DOI: 10.1016/***.2023.e12943.].

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