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IEEE Energy Conversion Congress and Exposition, ECCE

作者： Paychuda Kritprajun Leon M. Tolbert Nattapat Praisuwanna Jingxin Wang Yunting Liu Maximiliano Ferrari Dept. of Electrical Engineering and Computer Science The University of Tennessee Knoxville TN USA Dept. of Electrical Engineering The Pennsylvania State University PA USA Grid Components and Control Oak Ridge National Laboratory Oak Ridge TN USA

ISBN: (数字)9798350376067

ISBN: (纸本)9798350376074

This paper proposes a linear quadratic regulator (LQR)-based controller for a grid-connected photovoltaic (PV) with a supercapacitor (SC) system to ensure a smooth transition of control mode when the SC is unavailable (completely charged) during fault operations. The SC improves the low-voltage ride-through (LVRT) capability of the PV system by quickly balancing power between the PV system and the grid. When the SC reaches its full charge capacity, the DC-link voltage will be controlled by the inverter’s controller, and the PV system may need to curtail its power generation. During the transition, fluctuations in the DClink voltage can occur which can compromise the stability of the PV system, especially when the control mode switching happens during severe fault operations. The proposed LQR-based controller is validated on a hardware testbed platform to demonstrate its effectiveness in reducing DC-link overvoltage during the control mode transitions. As a result, the PV system can remain compliant with LVRT requirements while maintaining stability during fault operations.

关键词： Voltage fluctuations Regulators Power quality Power control Switches Power system stability Supercapacitors control systems Voltage control Transient analysis

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Discrete Shuffled Frog Leading Algorithm for Multiple-product Human-robot Collaborative Disassembly Line Balancing Problem

Discrete Shuffled Frog Leading Algorithm for Multiple-produc...

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2022 IEEE International Conference on Systems, Man, and Cybernetics, SMC 2022

作者： Fan, ChenYang Wang, JiaCun Guo, XiWang Qin, ShuJin Zhou, MengChu Qi, Liang Engineering of Liaoning Petrochemical University School of Information and Control Fushun China Engineering of Monmouth University Dept. Computer Science and Software West Long Branch United States Liaoning Petrochemical University Fushun China Monmouth University West Long Branch United States College of Economics and Management of Shangqiu Normal University Shangqiu China Dept. Electrical and Computer Engineering of New Jersey Institute of Technology Newark United States Tech of Shandong University of Science and Technology Dept. Computer Intelligent Sci. & Qingdao China

ISBN: (数字)9781665452588

ISBN: (纸本)9781665452588

With the rapid development of recycling and remanufacturing technologies, disassembly line balancing problems (DLBP) have drawn great attention. Considering the limitation of disassembly by humans or robots alone, this paper focuses on human-robot collaborative disassembly lines. Specifically, this work proposes a multi-product human-robot collaborative disassembly line balancing model to tackle the inflexibility of single product disassembly and inconsistency in recovery values of different product components. Its objective is to maximize disassembly profit. As a commercially available solver, IBM's CPLEX is used to obtain the exact solution of DLBP and verify the correctness of the proposed mathematical model. A discrete shuffled frog leading algorithm is newly designed to solve the sizable problems. Experimental results show that the proposed algorithm has a fast convergence rate and can find solutions consistent with those with CPLEX but requires much less time than the latter, thus advancing the field of disassembly automation. © 2022 IEEE.

关键词： Robots

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LLM Based Multi-Agent Generation of Semi-structured Documents from Semantic Templates in the Public Administration Domain

arXiv

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arXiv 2024年

作者： Musumeci, Emanuele Brienza, Michele Suriani, Vincenzo Nardi, Daniele Bloisi, Domenico Daniele Dept. of Computer Control and Management Engineering Sapienza University of Rome Rome Italy UNINT Univeristy Via Cristoforo Colombo 200 Rome00147 Italy

In the last years' digitalization process, the creation and management of documents in various domains, particularly in Public Administration (PA), have become increasingly complex and diverse. This complexity arises from the need to handle a wide range of document types, often characterized by semi-structured forms. Semi-structured documents present a fixed set of data without a fixed format. As a consequence, a template-based solution cannot be used, as understanding a document requires the extraction of the data structure. The recent introduction of Large Language Models (LLMs) has enabled the creation of customized text output satisfying user requests. In this work, we propose a novel approach that combines the LLMs with prompt engineering and multi-agent systems for generating new documents compliant with a desired *** main contribution of this work concerns replacing the commonly used manual prompting with a task description generated by semantic retrieval from an LLM. The potential of this approach is demonstrated through a series of experiments and case studies, showcasing its effectiveness in real-world PA scenarios. © 2024, CC BY.

关键词： Multi agent systems

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Incorporating the Com-B Model for Behavior Change into an Agent-Based Model of Smoking Behaviors: An Object-Oriented Design 24

Incorporating the Com-B Model for Behavior Change into an Ag...

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Proceedings of the Winter Simulation Conference

作者： David Tian Hazel Y. Squires Charlotte Buckley Duncan Gillespie Harry Tattan-Birch Lion Shahab Robert West Alan Brennan Jamie Brown Robin C. Purshouse Dept. of Automatic Control and Systems Engineering University of Sheffield UK Sheffield Centre for Health and Related Research School of Medicine and Population Health University of Sheffield UK Institute of Epidemiology and Health University College London UK

ISBN: (纸本)9798331534202

Modeling trajectories in cigarette smoking prevalence, initiation and quitting for populations and subgroups of populations is important for policy planning and evaluation. This paper proposes an agent-based model (ABM) design for simulating the smoking behaviors of a population using the Capability, Opportunity, Motivation - Behavior (COM-B) model. Capability, Opportunity and Motivation are modeled as latent composite attributes which are composed of observable factors associated with smoking behaviors. Three forms of the COM-B model are proposed to explain the transitions between smoking behaviors: initiating regular smoking uptake, making a quit attempt and quitting successfully. The ABM design follows object-oriented principles and extends an existing generic software architecture for mechanism-based modeling. The potential of the model to assess the impact of smoking policies is illustrated and discussed.

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Adaptive Output Regulation of MIMO LTI Systems with Unmodeled Input Dynamics

Adaptive Output Regulation of MIMO LTI Systems with Unmodele...

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IEEE Conference on Decision and control

作者： Oleg Borisov Alberto Isidori Anton Pyrkin Faculty of Control Systems and Robotics ITMO University St. Petersburg Russia Dept. of Computer Control and Management Engineering University “Sapienza” Rome Italy

This paper addresses the problem of adaptive output regulation of a minimum-phase MIMO LTI system in the presence of un-modeled (fast) input dynamics. The adoption of a post-processing tunable internal model makes it possible to implement standard methods for the analysis of two-time-scale systems. The proposed adaptation law guarantees, under suitable hypotheses, convergence to zero of the regulation error as well as of the parameter estimation error.

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Computationally Efficient Predictive control Based on ANN State-Space Models

Computationally Efficient Predictive Control Based on ANN St...

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IEEE Conference on Decision and control

作者： Jan H. Hoekstra Bence Cseppento Gerben I. Beintema Maarten Schoukens Zsolt Kollár Roland Tóth Dept. of Electrical Engineering at the Eindhoven Control Systems group University of Technology The Netherlands Dept. of Measurement and Information Systems Budapest University of Technology and Economics Hungary Institute for Computer Science and Control Budapest Hungary

Artificial neural networks (ANN) have been shown to be flexible and effective function estimators for the identification of nonlinear state-space models. However, if the resulting models are used directly for nonlinear model predictive control (NMPC), the resulting nonlinear optimization problem is often overly complex due to the size of the network, requires the use of high-order observers to track the states of the ANN model, and the overall control scheme does not exploit the available autograd tools for these models. In this paper, we propose an efficient approach to auto-convert ANN statespace models to linear parameter-varying (LPV) form and solve predictive control problems by successive solutions of linear model predictive problems, corresponding to quadratic programs (QPs). Furthermore, we show how existing deep-learning methods, such as SUBNET that uses a state encoder, enable efficient implementation of MPCs on identified ANN models. Performance of the proposed approach is demonstrated by a simulation study on an unbalanced disc system.

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Study of the Shock Loads Effect on the Operation of Multi-Motor Electric Drives of a Rolling Mill with a Second-order Elastic Coupling 5

Study of the Shock Loads Effect on the Operation of Multi-Mo...

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5th IEEE International Conference on Modern Electrical and Energy System, MEES 2023

作者： Tytiuk, Valerii Kalinin, Alexey Druzhinin, Valeriy Kuznetsov, Vitalii Chornyi, Oleksii Busher, Victor Kryvyi Rih National University Department of Electromechanics Kryvyi Rih Ukraine Abylkas Saginov Karaganda Technical University Npjsc Department of Informative Computer Systems Karaganda Kazakhstan Karaganda Industrial University Npjsc Department of Power Engineering Temirtau Kazakhstan Ukrainian State University of Science and Technologies Department of the Electrical Engineering Dnipro Ukraine National University Institute of Electromechanics Energy Saving and Automatic Control Systems Kremenchuk Mykhailo Ostrogradskyi Kremenchuk Ukraine National University "odessa Maritime Academy" Dept. of Electrical Engineering and Electronics Odessa Ukraine

ISBN: (纸本)9798350359787

This paper presents a study for optimizing a hot rolling mill. The paper is devoted to the study of ways to reduce the effect of shock loads of synchronous electric drives of the roughing mill group on the relative lengthening of the metal strip in the inter-stand gap of the rolling stands of the finishing mill group. The elasticity of the metal strip in the inter-stand gap of the rolling mill has a significant impact on the movement of intercoupled multi-motor electric drives of the finishing mill group. Another crucial route of exposure that influences the motion of the electric drives within the finishing mill group involves the electromagnetic connection between the drives in the roughing and finishing mill groups. The impact of the electromagnetically connected circuits is evident through the effect of shock loads from synchronous electric drives on the angular velocity of the direct current electric drives within the finishing mill group. The characteristics of the electromagnetic communication circuit are established by the power grid arrangement and equipment specifications. To assess the quality of work of electric drives of the finishing mill group, it is proposed to use the relative lengthening of the metal strip in the inter-stand gap, which is an important indirect indicator of the quality of rolling. The mathematical model of a hot rolling mill that takes into account both the elasticity of the metal strip that connects the DC electric drives of the finishing group, and the electromagnetic coupling circuit that takes into account the impact loads of synchronous electric drives of the roughing group on the example of the mill 1700 of ArcelorMittal Temirtau JSC was proposed in this paper. Using the mathematical model developed in Simulink software using the methods of planning the experiment, regression models were obtained to establish the dependence of the parameters of overexcitation of a synchronous motor on the magnitude of the voltage sag in the no

关键词： Electric loads

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control of Deterministic Chaotic Modes in Power Systems

Control of Deterministic Chaotic Modes in Power Systems

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Smart Information Systems and Technologies (SIST), IEEE International Conference on

作者： Mamyrbek Beisenbi Ainur Satpayeva Shugla Mussabayeva Gulnara Mussina Meruert Tlegen Dept. of System Analysis and Control L.N. Gumilyov Eurasian National University Astana Kazakhstan Dept. of Computer Engineering Astana IT University Astana Kazakhstan

The paper examines a new approach to controlling deterministic dynamical chaotic mode of power system with two electric generate-sources. A control law is synthesized in the class of one-parameter structurally stable mappings from catastrophe theory. Analytical calculations and a numerical experiment in MatLab showed that the proposed system excludes the generation of a deterministic chaotic mode for any changes in the uncertain system parameters. The study of the control system is carried out by the gradient-velocity method Lyapunov vector functions

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Robotic Teleoperation control Using PSO-Tuned Fractional Order Active Disturbance Rejection

Robotic Teleoperation Control Using PSO-Tuned Fractional Ord...

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IEEE SSD International Multi-Conference on Systems, Signals and Devices

作者： Omar Gad R. Fareh J. Ghommam M. Nasir S. Khadraoui M. Bettayeb Dept. of Electrical Engineering University of Sharjah UAE Research Inst. of Sciences and Engineering University of Sharjah UAE Dept. of Electrical and Computer Engineering Sultan Qaboos University Oman Control and Energy Management Laboratory (CEM Lab) Ecole National d'Ingenieur de Sfax Tunisia

ISBN: (数字)9798331542726

ISBN: (纸本)9798331542733

Bilateral teleoperation systems have become essential for enabling precise remote manipulation in fields such as robotic surgery and hazardous material handling. However, these systems face significant challenges, including time delays, environmental uncertainties, and nonlinear dynamics, which can affect their stability and performance. This research aims to investigate the application of Active Disturbance Rejection control (ADRC) to address these challenges. ADRC is chosen for its real-time estimation and compensation for disturbances, even with limited knowledge of the system model. Additionally, the study incorporates enhancements such as Fractional-Order control and optimization techniques, including Particle Swarm Optimization (PSO), for parameter tuning. A simulation study is conducted to assess the performance of the proposed controller in tracking control of bilateral teleoperation systems with 3-DOF and 4-DOF manipulators. Results illustrate the superiority of the fractional order ADRC in disturbance rejection and trajectory tracking compared to linear ADRC, making it a promising solution for teleoperation applications.

关键词： Robust control Uncertainty Trajectory tracking Simulation 3-DOF Surgery Manipulators Stability analysis Particle swarm optimization Tuning

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Feedback Optimizing MPC for Load Frequency control and Economic Dispatch

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IFAC-PapersOnLine 2023年第2期56卷 10935-10940页

作者： Amba Asuk Paul Trodden National Grid ESO Faraday House Warwick CV34 6DA UK Dept. of Automatic Control & Systems Engineering University of Sheffield S1 3JD UK

With increasing renewable generation, demand response, and deregulation, power networks are becoming more uncertain, time-varying, and strongly coupled. As a result, the conventional approach of performing separate economic dispatch (ED) and load-frequency control (LFC) operations may no longer guarantee smooth and cost-efficient regulation of frequency across interconnected power networks. To address this, we present a tracking model predictive control (MPC) algorithm which simultaneously achieves economic dispatch and secondary frequency control in a multi-area power network. A unique feature of the proposed algorithm is that it exploits the implicit feedback in MPC to regulate the interconnected power system towards steady-state equilibria that solve a multi-area economic dispatch problem, without explicitly computing the latter as a reference to be followed or estimating the unknown disturbances. This feedback-based optimization approach endows the algorithm with inherent robustness to uncertainty (such as unknown step changes in the demand). Simulation results for a two-area power network show improved steady-state economic performance compared to standard MPC-based frequency control schemes, and better dynamic performance compared to other feedback-based optimization schemes.

关键词： control and optimization of power systems Renewable energy sources Smart grids control of energy storage systems Power system planning and operation

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