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The Linear Constrained control Problem for Discrete-Time systems: Regulation on the Boundaries 23rd

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The Linear Constrained Control Problem for Discrete-Time Sys...

23rd International Conference on Difference Equations and Applications, ICDEA 2017

作者： Bitsoris, George Olaru, Sorin Vassilaki, Marina Control Systems Laboratory Department of Electrical and Computer Engineering University of Patras Patras26500 Greece Laboratory of Signals and Systems CentraleSupelec University Paris-Saclay ParisGif-sur-Yvette91190 France Department of Electrical and Electronic Engineering Educators ASPETE Athens14121 Greece

ISBN: (纸本)9783030200152

The chapter deals with the problem of regulation of linear systems around an equilibrium lying on the boundary of a polyhedral domain where linear constraints on the control and/or the state vectors are satisfied. In the first part of the chapter, the fundamental limitations for constrained control with active constraints at equilibrium are exposed. Next, based on the invariance properties of polyhedral and semi-ellipsoidal sets, design methods for guaranteeing convergence to the equilibrium while respecting linear control constraints are proposed. To this end, Lyapunov-like polyhedral functions, LMI methods and eigenstructure assignment techniques are applied. © 2019, Springer Nature Switzerland AG.

关键词： Digital control systems

Shifting dynamics of self-immolation in the capital of Iran? The rising trend among young, unmarried, less-educated men

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Burns Open 2025年 11卷 100406-100406页

作者： Shokri, MohammadAli Khalili, SaeedehSadat Vahabie, Abdol-Hossein Ghanbari Jolfaei, Atefeh Keshavarz-Akhlaghi, Amir-Abbas Dehmardei, Mostafa Mirfazeli, Fatemeh Sadat National Brain Centre Iran University of Medical Sciences Tehran Iraq Department of Neuroscience Faculty of Advanced Technologies in Medicine Iran University of Medical Sciences Tehran Iraq Cognitive Systems Laboratory Control and Intelligent Processing Center of Excellence (CIPCE) School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iraq Mental Health Research Center Psychosocial Health Research Institute Department of Psychiatry School of Medicine Iran University of Medical Sciences Tehran Iraq School of Medicine Iran University of Medical Sciences Tehran Iraq Department of Cognitive Sciences Faculty of Psychology and Education University of Tehran Tehran Iraq School of Cognitive Sciences Institute for Research in Fundamental Sciences (IPM) Tehran Iraq

In our study, we aimed to explore the psychiatric disorders, risk factors, and predictors of self-immolation among individuals admitted to Shahid Motahari Hospital in Tehran from 2019 to 2020. This cross-sectional study examines 64 hospitalized patients who received psychiatric counseling following self-immolation incidents. The rate of self-immolation varies significantly based on specific demographics. It is observed that in our population men had a higher rate of being unmarried (70.96 % vs 15.15 %), lower levels of education (70.96 % vs 63.63 % did not have a university degree), higher level of unemployment (54.83 % vs 30.30 %), younger age average with most men aging 15–24 (29.06 (SD = 9.33)) vs women 35–44 (35.27(SD = 10.27)) and higher prevalence of addiction (67.74 % vs 36.36 %) compared to women. On the other hand, women who attempted self-immolation mainly were married, involved in housekeeping, and tended to exhibit higher rates of depression (63.63 % vs 32.25 %) than men. Furthermore, these self-immolation incidents are often impulsive (64.1 %) and occur shortly (under an hour) after experiencing a stressor (39.1 %). Self-immolation accidents are frequently carried out using gasoline (50 %). Geographically, the majority of self-immolation cases of our study are concentrated in the central region of Iran (76.6 %), followed by the western region (15.6 %) this may be due to the proximity of these regions to our center while patients of other regions were hospitalized in their referral hospitals and were rarely transferred to the capital. To effectively address the issue of self-immolation and reduce its prevalence, it is essential to identify vulnerable populations and explore targeted preventive measures. Based on our findings, future pilot studies could investigate the feasibility of specific interventions, such as crisis hotlines to reduce impulsivity-related acts of self-immolation. Additionally, small-scale feasibility projects could explore the effect

关键词： Contributing factors Psychiatric disorders Self-immolation

Possibilities of vehicle state estimation using big data approaches 16

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Possibilities of vehicle state estimation using big data app...

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

作者： Fényes, Dániel Németh, Balázs Gáspár, Péter Asszonyi, Máté Systems and Control Laboratory Computer and Automation Research Institute Kende u. 13-17 Budapest Hungary Department of Control for Transportation and Vehicle Systems Faculty of Transportation Engineering and Vehicle Engineering Budapest University of Technology and Economics Stoczek u. 2 BudapestH-1111 Hungary

Nowadays, the development of the autonomous vehicles is one of the most important challenges for the automotive industry. In general, these vehicles are equipped with numerous sensors, such as onboard-camera, lidar, radar, ultrasonic sensor, accelerometer and gyroscope. These sensors provide information about the environment and other vehicles. This information is not only processed and used directly on the car but also can be stored on internal or cloud-based memory. This collected data might contain hidden information about the motion and the dynamical behaviour of the car. This hidden information can be brought out of the datasets by using big data-based data mining approaches. The aim of the paper is to create a vehicle state estimation model based on the collected sensor data and using data mining tools. In the paper, the sensor data is collected from a high-fidelity simulation software, CarSim. The estimation model is created by the machine-learning software Weka. Finally, the created model is validated through several CarSim simulations. © 2019 Budapest University of Technology and Economics. All rights reserved.

关键词： computer software

Deep learning-aided model predictive control of wind farms for AGC considering the dynamic wake effect

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arXiv 2020年

作者： Chen, Kaixuan Lin, Jin Qiu, Yiwei Liu, Feng Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100087 China Department of Electrical and Computer Engineering University of Macau 999078 China

To provide automatic generation control (AGC) service, wind farms (WFs) are required to control their operation dynamically to track the time-varying power reference. Wake effects impose significant aerodynamic interactions among turbines, which remarkably influence the WF dynamic power production. The nonlinear and high-dimensional nature of dynamic wake model, however, brings extremely high computation complexity and obscure the design of WF controllers. This paper overcomes the control difficulty brought by the dynamic wake model by proposing a novel control-oriented reduced order WF model and a deep-learning-aided model predictive control (MPC) method. Leveraging recent advances in computational fluid dynamics (CFD) to provide high-fidelity data that simulates WF dynamic wake flows, two novel deep neural network (DNN) architectures are specially designed to learn a dynamic WF reduced-order model (ROM) that can capture the dominant flow dynamics. Then, a novel MPC framework is constructed that explicitly incorporates the obtained WF ROM to coordinate different turbines while considering dynamic wake interactions. The proposed WF ROM and the control method are evaluated in a widely-accepted high-dimensional dynamic WF simulator whose accuracy has been validated by realistic measurement data. A 9-turbine WF case and a larger 25-turbine WF case are studied. By reducing WF model states by many orders of magnitude, the computational burden of the control method is reduced greatly. Besides, through the proposed method, the range of AGC signals that can be tracked by the WF in the dynamic operation is extended compared with the existing greedy controller. Copyright © 2020, The Authors. All rights reserved.

关键词： Model predictive control

Fast Monte Carlo Simulation of Dynamic Power systems under Continuous Random Disturbances

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arXiv 2020年

作者： Qiu, Yiwei Lin, Jin Chen, Xiaoshuang Liu, Feng Song, Yonghua State Key Laboratory of Control and Simulation of Power Systems and Generation Equipment Department of Electrical Engineering Tsinghua University Beijing100084 China Department of Electrical and Computer Engineering University of Macau 999078 China

—Continuous-time random disturbances from the renewable generation pose a significant impact on power system dynamic behavior. In evaluating this impact, the disturbances must be considered as continuous-time random processes instead of random variables that do not vary with time to ensure accuracy. Monte Carlo simulation (MCs) is a nonintrusive method to evaluate such impact that can be performed on commercial power system simulation software and is easy for power utilities to use, but is computationally cumbersome. Fast samplings methods such as Latin hypercube sampling (LHS) have been introduced to speed up sampling random variables, but yet cannot be applied to sample continuous disturbances. To overcome this limitation, this paper proposes a fast MCs method that enables the LHS to speed up sampling continuous disturbances, which is based on the Itô process model of the disturbances and the approximation of the Itô process by functions of independent normal random variables. A case study of the IEEE 39-Bus System shows that the proposed method is 47.6 and 6.7 times faster to converge compared to the traditional MCs in evaluating the expectation and variance of the system dynamic response. Copyright © 2020, The Authors. All rights reserved.

关键词： Monte Carlo methods

Toolbox for discovering dynamic system relations via TAG guided genetic programming

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arXiv 2020年

作者： Nechita, Stefan-Cristian Tóth, Roland Khandelwal, Dhruv Schoukens, Maarten Department of Electrical Engineering Eindhoven University of Technology Eindhoven University of Technology Eindhoven Netherlands Systems and Control Laboratory Institute for Computer Science and Control Kende u. 13-17 BudapestH-1111 Hungary

Data-driven modeling of nonlinear dynamical systems often require an expert user to take critical decisions a priori to the identification procedure. Recently an automated strategy for data driven modeling of single-input single-output (SISO) nonlinear dynamical systems based on Genetic Programming (GP) and Tree Adjoining Grammars (TAG) has been introduced. The current paper extends these latest findings by proposing a multi-input multi-output (MIMO) TAG modeling framework for polynomial NARMAX models. Moreover we introduce a TAG identification toolbox in Matlab that provides implementation of the proposed methodology to solve multi-input multi-output identification problems under NARMAX noise assumption. The capabilities of the toolbox and the modelling methodology are demonstrated in the identification of two SISO and one MIMO nonlinear dynamical benchmark models. © 2020, CC BY-NC-ND.

关键词： Dynamical systems

Compositional Synthesis of Symbolic Models for Infinite Networks ⁎

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IFAC-PapersOnLine 2020年第2期53卷 1868-1873页

作者： Abdalla Swikir Navid Noroozi Majid Zamani Department of Electrical and Computer Engineering Technical University of Munich Germany Laboratory for Systems Theory and Automatic Control Otto-von-Guericke University Magdeburg Germany Computer Science Department University of Colorado BoulderUSA. Institute of Informatics Ludwig Maximilian University Munich Germany

In this paper, we provide a compositional method for the construction of symbolic models (a.k.a. finite abstractions) for infinite networks of discrete-time control systems. The concrete infinite network and its symbolic model are related by a so-called alternating simulation function which allows one to quantify the mismatch between the output behavior of the infinite interconnection of concrete subsystems and that of their symbolic models. We show that such an alternating simulation function can be obtained compositionally by assuming some small-gain type conditions and composing so-called local alternating simulation functions constructed for subsystems. Assuming certain stability property of concrete subsystems, we also provide a technique to synthesize their symbolic models together with their corresponding local alternating simulation functions. Finally, we apply our results to a traffic network divided into infinitely many cells.

关键词： Compositionality interconnected systems small-gain condition infinite networks symbolic models

On PID control for synchronization of complex dynamical network with delayed nodes

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Science China(Technological Sciences) 2019年第8期62卷 1412-1422页

作者： GU HaiBo Lv JinHu LIN ZongLi Key Laboratory of Systems and Control Academy of Mathematics and Systems Science Chinese Academy of Sciences Beijing 100190 China School of Mathematical Sciences University of Chinese Academy of Sciences Beijing 100049 China School of Automation Science and Electrical Engineering State Key Laboratory of Software Development Environment and Beijing Advanced Innovation Center for Big Data and Brain Machine Intelligence Beihang University Beijing 100083 China Charles L. Brown Department of Electrical and Computer Engineering University of Virginia Charlottesville VA 22904-4743 USA

Over the past two decades, synchronization, as an interesting collective behavior of complex dynamical networks, has been attracting much attention. To reveal and analyze the inherent mechanism of synchronization in complex dynamical networks with time delays in nodes, this paper attempts to use PD and PI control protocols to achieve synchronization. Based on a classical network model, we investigate the PD and PI control for synchronization of complex dynamical networks with delayed nodes and obtain some sufficient conditions. By using Lyapunov functions and appropriate state transformations, we prove that global synchronization can be achieved via the above control protocols. Finally, some simulation examples are illustrated to validate the effectiveness of the proposed theoretical results.

关键词： synchronization PID control complex dynamical network networked control system delayed node

Efficient Pyramid Channel Attention Network for Pathological Myopia Recognition

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arXiv 2023年

作者： Zhang, Xiaoqing Zhao, Jilu Li, Yan Wu, Hao Zhou, Xiangtian Liu, Jiang Research Institute of Trustworthy Autonomous Systems Department of Computer Science and Engineering Southern University of Science and Technology Shenzhen518055 China Center for High Performance Computing Shenzhen Key Laboratory of Intelligent Bioinformatics Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China National Clinical Research Center for Ocular Diseases Eye Hospital Wenzhou Medical University Wenzhou325027 China State Key Laboratory of Ophthalmology Optometry and Visual Science Eye Hospital Wenzhou Medical University Wenzhou325027 China Research Unit of Myopia Basic Research and Clinical Prevention and Control Chinese Academy of Medical Sciences Wenzhou325027 China Singapore Eye Research Institute 169856 Singapore

Pathological myopia (PM) is the leading ocular disease for impaired vision worldwide. Clinically, the characteristic of pathology distribution in PM is global-local on the fundus image, which plays a significant role in assisting clinicians in diagnosing PM. However, most existing deep neural networks focused on designing complex architectures but rarely explored the pathology distribution prior of PM. To tackle this issue, we propose an efficient pyramid channel attention (EPCA) module, which fully leverages the potential of the clinical pathology prior of PM with pyramid pooling and multi-scale context fusion. Then, we construct EPCA-Net for automatic PM recognition based on fundus images by stacking a sequence of EPCA modules. Moreover, motivated by the recent pretraining-and-finetuning paradigm, we attempt to adapt pre-trained natural image models for PM recognition by freezing them and treating the EPCA and other attention modules as adapters. In addition, we construct a PM recognition benchmark termed PM-fundus by collecting fundus images of PM from publicly available datasets. The comprehensive experiments demonstrate the superiority of EPCA-Net over state-of-the-art methods in the PM recognition task. For example, EPCA-Net achieves 97.56% accuracy and outperforms ViT by 2.85% accuracy on the PM-fundus dataset. The results also show that our method based on the pretraining-and-finetuning paradigm achieves competitive performance through comparisons to part of previous methods based on traditional fine-tuning paradigm with fewer tunable parameters, which has the potential to leverage more natural image foundation models to address the PM recognition task in limited medical data regime. Copyright © 2023, The Authors. All rights reserved.

关键词： Pathology