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arXiv 2020年

作者： Nugraha, Yurid Cetinkaya, Ahmet Hayakawa, Tomohisa Ishii, Hideaki Zhu, Quanyan Department of Systems and Control Engineering Tokyo Institute of Technology Tokyo152-8552 Japan Information Systems Architecture Science Research Division National Institute of Informatics Tokyo101-8430 Japan Department of Computer Science Tokyo Insitute of Technology Yokohama226-8502 Japan Department of Electrical and Computer Engineering New York University BrooklynNY11201 United States

A cyber security problem in a networked system formulated as a resilient graph problem based on a game-theoretic approach is considered. The connectivity of the underlying graph of the network system is reduced by an attacker who removes some of the edges whereas the defender attempts to recover them. Both players are subject to energy constraints so that their actions are restricted and cannot be performed continuously. For this two-stage game, which is played repeatedly over time, we characterize the optimal strategies for the attacker and the defender in terms of edge connectivity and the number of connected components of the graph. The resilient graph game is then applied to a multi-agent consensus problem. We study how the attacks and the recovery on the edges affect the consensus process. Finally, we also provide numerical simulation to illustrate the results. Copyright © 2020, The Authors. All rights reserved.

关键词： Multi agent systems

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Artificial Intelligence and Statistical Techniques in Short-Term Load Forecasting: A Review

arXiv

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arXiv 2021年

作者： Nassif, Ali Bou Soudan, Bassel Azzeh, Mohammad Attilli, Imtinan AlMulla, Omar Department of Computer Engineering University of Sharjah Sharjah27272 United Arab Emirates Data Analytics and Cybersecurity Research Centre RISE University of Sharjah Sharjah27272 United Arab Emirates Department of Computer Engineering University of Sharjah Sharjah27272 United Arab Emirates Sustainable Energy & Power Systems Research Centre RISE University of Sharjah Sharjah27272 United Arab Emirates Department of Data Science Princess Sumaya University for Technology Amman11941 Jordan Department of Electrical Engineering University of Sharjah Sharjah27272 United Arab Emirates Distribution Control Centre Dubai Water and Electricity Authority Dubai United Arab Emirates

Electrical utilities depend on short-term demand forecasting to proactively adjust production and distribution in anticipation of major variations. This systematic review analyzes 240 works published in scholarly journals between 2000 and 2019 that focus on applying Artificial Intelligence (AI), statistical, and hybrid models to short-term load forecasting (STLF). This work represents the most comprehensive review of works on this subject to date. A complete analysis of the literature is conducted to identify the most popular and accurate techniques as well as existing gaps. The findings show that although Artificial Neural Networks (ANN) continue to be the most commonly used standalone technique, researchers have been exceedingly opting for hybrid combinations of different techniques to leverage the combined advantages of individual methods. The review demonstrates that it is commonly possible with these hybrid combinations to achieve prediction accuracy exceeding 99%. The most successful duration for short-term forecasting has been identified as prediction for a duration of one day at an hourly interval. The review has identified a deficiency in access to datasets needed for training of the models. A significant gap has been identified in researching regions other than Asia, Europe, North America, and Australia. Copyright © 2021, The Authors. All rights reserved.

关键词： Neural networks

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Camera-based lateral driver modelling for vehicle control design purposes 16

Camera-based lateral driver modelling for vehicle control de...

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16th Mini Conference on Vehicle System Dynamics, Identification and Anomalies, VSDIA 2018

作者： Dalvári, Máté Fényes, Dániel Mihály, András Németh, Balázs Gáspár, Péter Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Műegyetem rkp. 3 BudapestH-1111 Hungary Institute for Computer Science and Control Hungarian Academy of Sciences BudapestH-1111 Hungary

The paper proposes the modeling of a driver behavior in lateral vehicle control design purposes. Nowadays significant emphasis is placed on the development of autonomous vehicle systems which motivates to research in this area. Using a properly designed driver model during cornering ensures the comfort of the passengers and provides predictable motions for the drivers of conventional vehicles and pedestrians. In this paper the vehicle control is based on picture frames provided by an onboard mono-camera, which is used by an image processing algorithm to calculate the present and the predicted lateral errors. The identified driver model defines the instantaneous steering angle using the calculated errors and several dynamic parameters of the vehicle. One of the dynamic variables, the longitudinal speed was used as a scheduling variable to determine the actual operating region of the system. The formulated driver model is verified through a real-time running simulator software, where the measured values of the steering angles can be compared with calculated ones. The simulation showed the accuracy and reliability of the formulated driver model. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： Cameras

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Temporal Logic Trees for Model Checking and control Synthesis of Uncertain Discrete-time systems

arXiv

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arXiv 2020年

作者： Gao, Yulong Abate, Alessandro Jiang, Frank J. Giacobbe, Mirco Xie, Lihua Johansson, Karl H. Division of Decision and Control Systems Royal Institute of Technology Stockholm Sweden Department of Computer Science University of Oxford United Kingdom School of Electrical and Electronic Engineering Nanyang Technological University Singapore

We propose algorithms for performing model checking and control synthesis for discrete-time uncertain systems under linear temporal logic (LTL) specifications. We construct temporal logic trees (TLT) from LTL formulae via reachability analysis. In contrast to automaton-based methods, the construction of the TLT is abstraction-free for infinite systems, that is, we do not construct discrete abstractions of the infinite systems. Moreover, for a given transition system and an LTL formula, we prove that there exist both a universal TLT and an existential TLT via minimal and maximal reachability analysis, respectively. We show that the universal TLT is an underapproximation for the LTL formula and the existential TLT is an overapproximation. We provide sufficient conditions and necessary conditions to verify whether a transition system satisfies an LTL formula by using the TLT approximations. As a major contribution of this work, for a controlled transition system and an LTL formula, we prove that a controlled TLT can be constructed from the LTL formula via control-dependent reachability analysis. Based on the controlled TLT, we design an online control synthesis algorithm, under which a set of feasible control inputs can be generated at each time step. We also prove that this algorithm is recursively feasible. We illustrate the proposed methods for both finite and infinite systems and highlight the generality and online scalability with two simulated examples. Copyright © 2020, The Authors. All rights reserved.

关键词： Temporal logic

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Author Correction: H∞ observer-based control for fuzzy Hadamard fractional-order systems

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Computational and Applied Mathematics 2025年第5期44卷 1-1页

作者： Rhaima, Mohamed Gassara, Hamdi Mchiri, Lassaad Hajjaji, Ahmed El Makhlouf, Abdellatif Ben Department of Statistics and Operations Research College of Science King Saud University Riyadh Saudi Arabia Laboratory of Sciences Techniques of Automatic Control and Computer Engineering National School of Engineering of Sfax University of Sfax Sfax Tunisia Panthéon-Assas University Paris II Paris France Modeling Information and Systems Laboratory University of Picardie Jules Verne UFR of Sciences Amiens France Department of Mathematics Faculty of Sciences Sfax University Sfax Tunisia

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Trading accuracy for power with a configurable approximate adder

Trading accuracy for power with a configurable approximate a...

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作者： Sato, Toshinori Yang, Tongxin Ukezono, Tomoaki Department of Electronics Engineering and Computer Science Fukuoka University Fukuoka-shi814-0180 Japan Graduate School of Information and Control Systems Fukuoka University Fukuoka-shi814-0180 Japan

Approximate computing is a promising paradigm to realize fast, small, and low power characteristics, which are essential for modern applications, such as Internet of Things (IoT) devices. This paper proposes the Carry-Predicting Adder (CPredA), an approximate adder that is scalable relative to accuracy and power consumption. The proposed CPredA improves the accuracy of a previously studied adder by performing carry prediction. Detailed simulations reveal that, compared to the existing approximate adder, accuracy is improved by approximately 50% with comparable energy efficiency. Two application-level evaluations demonstrate that the proposed approximate adder is sufficiently accurate for practical use. Copyright © 2019 The Institute of Electronics, Information and Communication Engineers.

关键词： Adders

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AI and Reading Fluency for Brazilian Portuguese: A Preliminary Study

SSRN

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SSRN 2023年

作者： Rodrigues, Aline Do Nascimento Ribeiro, Gabriela L. Silva, Victor H.A. Carvalho, Wesley S. Ramírez, Miguel A. Alves, Luciana M. Finger, Marcelo Navas, Ana Luiza G.P. Ribeiro, Carlos H.C. Computer Science Division Aeronautics Institute of Technology Praça Mal. Eduardo Gomes 50 SP Sao Jose dos Campos12228-900 Brazil Federal University of Minas Gerais Medicine Faculty Department of Speech Therapy Av. Prof. Alfredo Balena 190 MG Belo Horizonte30130-100 Brazil University of Sao Paulo Escola Politecnica Department of Telecommunications and Control Engineering Av. Prof. Luciano Gualberto trav. 3 158 SP Sao Paulo05508-010 Brazil University of Sao Paulo Institute of Mathematics and Statistics Department of Computer Science Rua do Matao 1010 SP Sao Paulo05508-090 Brazil University of Sao Paulo Escola Politecnica Department of Electronic Systems Engineering Av. Prof. Luciano Gualberto trav. 3 158 SP Sao Paulo05508-010 Brazil School of Medical Sciences of Santa Casa de Sao Paulo Department of Speech Therapy R. Dr. Cesario Motta Jr. 61 SP Sao Paulo01221-020 Brazil

Automatic assessment of oral reading fluency — either for completely autonomous operation or as a facilitator for human decision making — is a likely requirement for timely interventions regarding educational policies for Literacy, especially at the initial years of formal Education. Countries with huge populations such as Brazil have a more urgent demand for such automated procedures, considering the scale of the evaluation needs and the disproportional lack of specialized personnel, compared to more advanced countries. Nevertheless, computational methods as educational aids for Literacy evaluation have been developed mainly for English and other languages associated with those high income countries. Therefore there is an obvious need for studies on languages and countries (especially those with large educational populations) that are less developed. We report on a computational model for fluency assessment based on an automatic speech recognizer (ASR) readily available in the software literature, trained via a deep learning model on a publicly available dataset for Brazilian Portuguese. The model was previously trained for ASR purposes, and therefore was not designed for Literacy assessment of children, this aspect was dealt with through a series of pre and post-processing of the audio samples. Extensive comparative results on reading oral fluency for standardized assessment texts considering the proposed automated process compared to a benchmark by human expert annotations showed a high matching for measures on word and word error rates, despite the fact that the learning model did not include samples from the target population. © 2023, The Authors. All rights reserved.

关键词： Computational methods

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Preface

Lecture Notes in Networks and Systems

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Lecture Notes in Networks and systems 2024年 1076 LNNS卷 v-vii页

作者： Biele, Cezary Kacprzyk, Janusz Kopeć, Wieslaw Możaryn, Jakub Owsiński, Jan W. Romanowski, Andrzej Sikorski, Marcin National Information Processing Institute Warszaw Poland Polish Academy of Sciences Systems Research Institute Warsaw Poland Polish-Japanese Academy of Information Technology Warsaw Poland Institute of Automatic Control and Robotics Faculty of Mechatronics Warsaw University of Technology Warsaw Poland Institute of Applied Computer Science Faculty of Electrical Electronic Computer and Control Engineering Lódż University of Technology LODZ Poland Department of Applied Informatics in Management Faculty of Management and Economics Gdańsk University of Technology Gdańsk Poland

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Network-level optimal control for public bus operation

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IFAC-PapersOnLine 2020年第2期53卷 15003-15010页

作者： Balázs Varga Tamás Péni Balázs Kulcsár Tamás Tettamanti Budapest University of Technology and Economics Faculty of Transportation Engineering and Vehicle Engineering Department of Control for Transportation and Vehicle Systems Hungary H-1111 Budapest Műegyetem rkp. 3 Institute for Computer Science and Control (SZTAKI) Hungary H-1111 Budapest. Kende u. 13-17 Department of Electrical Engineering Chalmers University of Technology Hörsalsvägen 9-11 SE-412-96 Gothenburg Sweden

The paper presents modeling, control and analysis of an urban public transport network. First, a centralized system description is given, built up from the dynamics of individual buses and bus stops. Aiming to minimize three conflicting goals (equidistant headways, timetable adherence, and minimizing passenger waiting times), a reference tracking model predictive controller is formulated based on the piecewise-affine system model. The closed-loop system is analyzed with three methods. Numerical simulations on a simple experimental network showed that the temporal evolution of headways and passenger numbers could maintain their periodicity with the help of velocity control. With the help of randomized simulation scenarios, sensitivity of the system is analyzed. Finally, infeasible regions for the bus network control was sought using by formulating an explicit model predictive controller.

关键词： Urban systems Public transport Centralised control Model predictive control Piecewise-affine systems Scenario based methods Set theory

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Linear System Identification Under Multiplicative Noise from Multiple Trajectory Data

Linear System Identification Under Multiplicative Noise from...

引用

American control Conference

作者： Yu Xing Ben Gravell Xingkang He Karl Henrik Johansson Tyler Summers Key Lab of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences and School of Mathematical Sciences University of Chinese Academy of Sciences Beijing P. R. China Department of Mechanical Engineering The University of Texas at Dallas Richardson TX USA Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

ISBN: (数字)9781538682661

ISBN: (纸本)9781538682678

The study of multiplicative noise models has a long history in control theory but is re-emerging in the context of complex networked systems and systems with learning-based control. We consider linear system identification with multiplicative noise from multiple state-input trajectory data. We propose exploratory input signals along with a least-squares algorithm to simultaneously estimate nominal system parameters and multiplicative noise covariance matrices. The asymptotic consistency of the least-squares estimator is demonstrated by analyzing first and second moment dynamics of the system. The results are illustrated by numerical simulations.

关键词： Trajectory Covariance matrices Linear systems Heuristic algorithms Optimal control Mathematical model

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