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Disturbance Attenuation via Nonlinear Feedback for Chemical Reaction Networks

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IFAC-PapersOnLine 2020年第2期53卷 11497-11502页

作者： Lőrinc Márton Katalin M. Hangos Gábor Szederkényi Department of Electrical Engineering Sapientia Hungarian University of Transylvania Tirgu Mures Romania Systems and Control Laboratory Institute for Computer Science and Control Budapest Hungary Faculty of Information Technology and Bionics Pázmány Péter Catholic University Budapest Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

This paper deals with the setpoint control of Chemical Reaction Networks (CRNs) in the presence of disturbances. The addressed control problem is traced back to the output feedback-based stabilization of passive systems. First, the passivity properties of complex balanced CRNs are discussed. Second, it is shown that, by combining the kinetic feedback based control with the passivity theory-based output feedback approach, arbitrary disturbance attenuation in controlled CRNs can be achieved. A case study is provided to demonstrate the applicability of the proposed control design approach.

关键词： Chemical Reaction Networks Passivity Setpoint control Disturbance Attenuation

A Parallel Education Based Intelligent Tutoring systems Framework

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A Parallel Education Based Intelligent Tutoring Systems Fram...

2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Jing, Sifeng Tang, Ying Liu, Xiwei Gong, Xiaoyan Cui, Wei Liang, Joleen State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100190 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States Squirrel Ai Learning Shanghai200030 China

ISBN: (纸本)9781728168531

although online education has improved efficiency of learners' access to high-quality educational resources, realtime interaction between instructors and learners have not yet been achieved in online personalized learning. Intelligent Tutoring systems (ITS) provides a feasible way to realize realtime personalized learning guidance and resource recommendations by applying AI to capture and analyze online learners' characteristics and behaviors. In this paper, reviews and trends of ITS are discussed and three challenges of ITS research development are pointed out: learner model, guidance mechanism and human-computer interaction mechanism. In order to address these issues, parallel intelligence theory is introduced and a parallel intelligence education based ITS framework is proposed. © 2020 IEEE.

关键词： computer aided instruction

K-9 Artificial Intelligence Education in Qingdao: Issues, Challenges and Suggestions

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K-9 Artificial Intelligence Education in Qingdao: Issues, Ch...

2020 IEEE International Conference on Networking, Sensing and control, ICNSC 2020

作者： Gong, Xiaoyan Tang, Ying Liu, Xiwei Jing, Sifeng Cui, Wei Liang, Joleen Wang, Fei-Yue State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing100084 China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao266044 China Department of Electrical and Computer Engineering Rowan University GlassboroNJ08028 United States Squirrel Ai Learning Shanghai200030 China

ISBN: (纸本)9781728168531

Nowadays, AI education from Kindergarten to 9th grade(K-9) is in full swing in China, but many challenges exist, such as fragmented AI curricula, ineffective teaching tools, and uneven educational resources in urban and rural areas, etc. So this paper presents an in-depth study of the current status of K-9 AI education in Qingdao area through questionnaires, expert discussions, and field visits to sort out existing problems and then put forward corresponding advice and suggestions. Collected data is then analyzed from the perspectives of government, schools, teachers, students and parents, respectively. Results show that AI-related educational activities have been carried out in Qingdao area to improve students' AI literacy. But efforts are still needed to make such education more systematic, standardized, and personalized. Finally the paper made a list of recommendations corresponding to these needed efforts. © 2020 IEEE.

关键词： Curricula

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

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

A global to local double embedding method for multi-person pose estimation

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arXiv 2021年

作者： Xu, Yiming Li, Jiaxin Peng, Yiheng Ding, Yan Wei, Hualiang Yingcai Honors College University of Electronic Science and Technology of China Chengdu China Key Laboratory of Dynamics and Control of Flight Vehicle Ministry of Education School of Aerospace Engineering Beijing Institute of Technology Beijing100081 China School of Computer Science and Technology Donghua University Shanghai China Department of Automatic Control and Systems Engineering University of Shefield ShefieldS1 3JD United Kingdom

Multi-person pose estimation is a fundamental and challenging problem to many computer vision tasks. Most existing methods can be broadly categorized into two classes: top-down and bottom-up methods. Both of the two types of methods involve two stages, namely, person detection and joints detection. Conventionally, the two stages are implemented separately without considering their interactions between them, and this may inevitably cause some issue intrinsically. In this paper, we present a novel method to simplify the pipeline by implementing person detection and joints detection simultaneously. We propose a Double Embedding (DE) method to complete the multi-person pose estimation task in a global-to-local way. DE consists of Global Embedding (GE) and Local Embedding (LE). GE encodes different person instances and processes information covering the whole image and LE encodes the local limbs information. GE functions for the person detection in top-down strategy while LE connects the rest joints sequentially which functions for joint grouping and information processing in A bottom-up strategy. Based on LE, we design the Mutual Refine Machine (MRM) to reduce the prediction difficulty in complex scenarios. MRM can effectively realize the information communicating between keypoints and further improve the accuracy. We achieve the competitive results on benchmarks MSCOCO, MPII and CrowdPose, demonstrating the effectiveness and generalization ability of our method. Copyright © 2021, The Authors. All rights reserved.

关键词： Embeddings

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

Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

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arXiv 2021年

作者： Yi, Xinlei Li, Xiuxian Yang, Tao Xie, Lihua Chai, Tianyou Johansson, Karl H. The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden The Digital Futures Stockholm10044 Sweden The Department of Control Science and Engineering College of Electronics and Information Engineering The Shanghai Research Institute for Intelligent Autonomous Systems Tongji University Shanghai China The State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China School of Electrical and Electronic Engineering Nanyang Technological University 50 Nanyang Avenue Singapore639798 Singapore

This paper considers the distributed online convex optimization problem with time-varying constraints over a network of agents. This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions. At each round, each agent selects a decision from the decision set, and then only a portion of the loss function and a coordinate block of the constraint function at this round are privately revealed to this agent. The goal of the network is to minimize the network-wide loss accumulated over time. Two distributed online algorithms with full-information and bandit feedback are proposed. Both dynamic and static network regret bounds are analyzed for the proposed algorithms, and network cumulative constraint violation is used to measure constraint violation, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. In particular, we show that the proposed algorithms achieve O(T max{κ,1-κ}) static network regret and O(T 1-κ/2) network cumulative constraint violation, where T is the time horizon and κ ∈ (0, 1) is a user-defined trade-off parameter. Moreover, if the loss functions are strongly convex, then the static network regret bound can be reduced to O(T κ). Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Economic and social effects