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Evacuation control of Crowds of Pedestrians: Distributed or Decentralized? ⁎

IFAC-PapersOnLine 2020年第5期53卷 318-323页

作者： Kecai Cao YangQuan Chen Chenglin Liu Nanjing Institute of Technology Nanjing 211167 China Mechatronics Embedded Systems and Automation Lab School of Engineering University of California Merced CA USA 95343 Key Laboratory of Advanced Process Control for Light Industry (Ministry of Education) Institute of Automation Jiangnan University Wuxi 214122 China

Evacuation of crowds in a corridor with only one exit has been considered in this paper where distributed controllers have been constructed to regulate the crowd’s evacuation speed so that stampede tragedy can be avoided. Macroscopic model for crowds of pedestrians has been firstly derived based on inspiration of LWR (Lighthill-Whitham and Richards) model and Greenshields model from traffic system where finite volume method has been introduced to simplify the obtained PDEs into finite ODEs. Distributed evacuation controllers have been constructed based on inspiration of multi-agent system and stability analysis of obtained closed-loop system has been simplified to linear system with the delicate controllers proposed. Comparisons between distributed evacuation controllers and previous evacuation controllers have also been presented to show the advantages and disadvantages of different controllers under different initial density of crowds so that tragedy of crowd stampede can be effectively avoided with appropriate selection of different controllers.

关键词： Distributed evacuation controller Decentralized evacuation controller Stampede

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Zeroth-order algorithms for stochastic distributed nonconvex optimization

arXiv

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arXiv 2021年

作者： Yi, Xinlei Zhang, Shengjun Yang, Tao Johansson, Karl H. Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm10044 Sweden Department of Electrical Engineering University of North Texas DentonTX76203 United States State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang110819 China

In this paper, we consider a stochastic distributed nonconvex optimization problem with the cost function being distributed over n agents having access only to zeroth-order (ZO) information of the cost. This problem has various machine learning applications. As a solution, we propose two distributed ZO algorithms, in which at each iteration each agent samples the local stochastic ZO oracle at two points with a time-varying smoothing parameter. We show that the proposed algorithms achieve the linear speedup convergence rate O(√p=(nT)) for smooth cost functions under the state-dependent variance assumptions which are more general than the commonly used bounded variance and Lipschitz assumptions, and O(p=(nT)) convergence rate when the global cost function additionally satisfies the Polyak-Lojasiewicz (P-L) condition in addition, where p and T are the dimension of the decision variable and the total number of iterations, respectively. To the best of our knowledge, this is the first linear speedup result for distributed ZO algorithms, which enables systematic processing performance improvements by adding more agents. We also show that the proposed algorithms converge linearly under the relative bounded second moment assumptions and the P-L condition. We demonstrate through numerical experiments the efficiency of our algorithms on generating adversarial examples from deep neural networks in comparison with baseline and recently proposed centralized and distributed ZO algorithms. Copyright © 2021, The Authors. All rights reserved.

关键词： Cost functions

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

arXiv

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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

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Regret and cumulative constraint violation analysis for online convex optimization with long term constraints

arXiv

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arXiv 2021年

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

This paper considers online convex optimization with long term constraints, where constraints can be violated in intermediate rounds, but need to be satisfied in the long run. The cumulative constraint violation is used as the metric to measure constraint violations, which excludes the situation that strictly feasible constraints can compensate the effects of violated constraints. A novel algorithm is first proposed and it achieves an O(Tmax{c,1-c}) bound for static regret and an O(T (1-c)/2) bound for cumulative constraint violation, where c ϵ (0, 1) is a user-defined trade-off parameter, and thus has improved performance compared with existing results. Both static regret and cumulative constraint violation bounds are reduced to O(log(T )) when the loss functions are strongly convex, which also improves existing results. In order to achieve the optimal regret with respect to any comparator sequence, another algorithm is then proposed and it achieves the optimal O( p T (1 + PT )) regret and an O(√T) cumulative constraint violation, where PT is the path-length of the comparator sequence. Finally, numerical simulations are provided to illustrate the effectiveness of the theoretical results. Copyright © 2021, The Authors. All rights reserved.

关键词： Comparators (optical)

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Preface——Special Issue on New Directions in Nonlinear and Distributed control

引用

Journal of systems Science & Complexity 2018年第1期31卷 1-3页

作者： LIU Tengfei XIN Bin JIANG Zhong-Ping State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang 110819 China School of Automation State Key Laboratory of Intelligent Control and Decision of Complex Systems Beijing Advanced Innovation Center for Intelligent Robots and Systems Beijing Institute of Technology Beijing 100081 China Tandon School of Engineering New York University Brooklyn NY 11201 USA

Nonlinearity is ubiquitous in engineering and natural *** development of nonlinear control can be traced back to decades *** date,the research has reached the stage that emphasizes developing methodologies that can ha... 详细信息

关键词：控制问题非线性分布式工程应用程序电子物理自然系统生产线相互作用

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Stochastic Optimization for Energy-Efficient Cooperative Platooning

Stochastic Optimization for Energy-Efficient Cooperative Pla...

引用

IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Alexander Wasserburger Alexander Schirrer Christoph Hametner Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria Divison of Process Control and Automation TU Wien Vienna Austria

Following another vehicle can be automated by controlling the inter-vehicle distance using cooperative adaptive cruise control systems (CACC). On the one hand, this distance should be as small as possible in order to reduce aerodynamic drag which decreases fuel consumption. On the other hand, a minimal spacing can increase the probability and severity of collisions. In order to ensure a satisfying performance in the presence of various information topologies and relevant uncertainties such as errors in data transmission or extreme maneuvers of the lead vehicle, a stochastic optimization approach is suggested and demonstrated for a preexisting CACC scheme. Simulation experiments show the performance and the potential energy savings achieved by the robust calibration of the controller.

关键词： Optimization Lead Trajectory Uncertainty Energy consumption Safety Acceleration

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Delays in Model Reduction of Chemical Reaction Networks

引用

IFAC-PapersOnLine 2018年第14期51卷 100-105页

作者： Lipták, György Hangos, Katalin M. Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 BudapestH-1518 Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

A novel engineering model reduction method is proposed in this paper that can be applied to a chemical reaction network (CRN) with chains of linear reactions. The reduced model is a delayed CRN with possibly different delays but with less state variables than the original model. As the first step of the model reduction, a decomposition method is also developed to transform chains with joint reactions into independent chains of linear reactions. The well known example of McKeithan's network is used as a case study to illustrate the basic concepts and the design method. © 2018

关键词： Reduction

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Distributed delay model of the McKeithan’s network

引用

IFAC-PapersOnLine 2019年第7期52卷 33-38页

作者： György Lipták Katalin M. Hangos Process Control Research Group Systems and Control Laboratory Computer and Automation Research Institute Hungarian Academy of Sciences P.O. Box 63 H-1518 Budapest Hungary Department of Electrical Engineering and Information Systems University of Pannonia Veszprém Hungary

In this paper CRNs containing linear reaction chains with multiple joint complexes were considered in order to obtain an equivalent reduced order delayed CRN model with distributed time delays. For this purpose, our earlier method (Lipták and Hangos (2018)) for decomposing the chains of linear reactions with multiple joint complexes was used together with the "linear chain trick". An analytical expression for the kernel function of the distributed delay was also derived from the reaction rate coefficients of the linear reaction chains. Our approach was demonstrated using the example of the well known McKeithan’s network model of kinetic proofreading.

关键词： process control Delay Chemical Reaction Networks

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Dead-Time Compensator for State-delay Stable systems

引用

IFAC-PapersOnLine 2018年第18期51卷 672-677页

作者： Albertos, P. García, P. Chen, Q. Luan, X. Department of Systems Engineering Control Instituto de Automática e Informática Industrial Universitat Politècnica deValència Spain Key Laboratory of Advance Process Control for Light Industries Institute of Automation Jiangnan University China

This paper deals with the control of simple process models with state-delays. A pre-compensator is used to cancel the delay. Due to the cancellation of some terms, the process as well as its undelayed part should be stable. Although the approach is general, in order to simplify the notation, second order systems are considered to describe the procedure. The proposed methodology is applied to compensate the delay in a recycled reactor as well as to control a pure state-delayed academic example. © 2018

关键词： process control Delay control systems Recycling control design Dead time compensator Dead time compensation Pre compensator Second order systemss Stable systems State delay Time delay systems

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Optimal Current Excitation for the Time-Domain Estimation of the Electrochemical Impedance

Optimal Current Excitation for the Time-Domain Estimation of...

引用

IEEE Conference on Vehicle Power and Propulsion (VPPC)

作者： Daniel Ritzberger Christoph Hametner Stefan Jakubek Institute of Mechanics and Mechatronics Control and Process Automation TU Wien Vienna Austria Christian Doppler Laboratory for Innovative Control and Monitoring of Automotive Powertrain Systems TU Wien Vienna Austria

For the real-time fault detection of electrochemical cells in automotive applications, time-domain based impedance estimation schemes, together with broad-band current excitation signals, have been developed. Whereas the appropriate choice of the estimator is necessary as to prevent a systematic estimation bias, the choice of the applied excitation signal is of equal crucial importance as thereby the covariance of the estimate, and therefore the resulting accuracy of the estimation scheme, is directly influenced. In this work, an optimization of the applied current excitation signal, based on the Fisher information matrix, is proposed and its influence on the estimation accuracy is investigated.

关键词： Estimation Optimization Impedance Time-domain analysis Noise measurement Integrated circuit modeling Equivalent circuits

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