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Asian control Conference

作者： Ting Bai Alexander Johansson Shaoyuan Li Karl Henrik Johansson Jonas Må rtensson Integrated Transport Research Lab Digital Futures and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Automation Key Laboratory of System Control and Information Processing Ministry of Education Shanghai Jiao Tong University Shanghai China

We model a platooning system including trucks and a third-party service provider that performs platoon coordination, distributes the platooning profit within platoons, and charges the trucks in exchange for its services. This paper studies one class of pricing rules, where the third-party service provider keeps part of the platooning profit each time a platoon is formed. Furthermore, we propose a platoon coordination solution based on distributed model predictive control in which the pricing rule is integrated. To evaluate the effect of the pricing on the platooning system, we perform a simulation over the Swedish road network. The simulation shows that the platooning rate and profit highly depend on the pricing. This suggests that pricing needs to be set carefully to obtain a satisfactory platooning system in the future.

关键词： Roads Pricing Predictive control

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Quantized Distributed Nonconvex Optimization with Linear Convergence

Quantized Distributed Nonconvex Optimization with Linear Con...

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IEEE Conference on Decision and control

作者： Lei Xu Xinlei Yi Jiayue Sun Yang Shi Karl Henrik Johansson Tao Yang State Key Laboratory of Synthetical Automation for Process Industries Northeastern University Shenyang China Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering University of Victoria Victoria Canada

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

This paper considers distributed nonconvex op-timization for minimizing the average of local cost functions, by using local information exchange over undirected communication networks. Since the communication channels often have limited bandwidth or capacity, we first introduce a quantization rule and an encoder/decoder scheme to reduce the transmission bits. By integrating them with a distributed algorithm, we then propose a distributed quantized nonconvex optimization algorithm. Assuming the global cost function satisfies the Polyak– Łojasiewicz condition, which does not require the global cost function to be convex and the global minimizer is not necessarily unique, we show that the proposed algorithm linearly converges to a global optimal point. Moreover, a low data rate is shown to be sufficient to ensure linear convergence when the algorithm parameters are properly chosen. The theoretical results are illustrated by numerical simulation examples.

关键词： Quantization (signal) Communication channels Bandwidth Cost function Numerical simulation Communication networks Distributed algorithms

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AI Graphical Programming Learning Platform for Children

AI Graphical Programming Learning Platform for Children

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2021 China Automation Congress, CAC 2021

作者： Zhao, Hongxia Liu, Xiwei Gong, Xiaoyan Li, Qiang Jing, Sifeng Xue, Yaofeng The State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China Institute of Smart Education Systems Qingdao Academy of Intelligent Industries Qingdao China University of Chinese Academy of Sciences Beijing China Shanghai Engineering Research Center of Digital Education Equipment Department of Education Information Technology East China Normal University Shanghai China

ISBN: (纸本)9781665426473

In this era of rapid development of artificial intelligence, the truth of competition in the future is the talent. Countries all over the world attach great importance to the programming and artificial intelligence education of children. In the future, the theoretical development and practical application of this emerging field will usher in a period of rapid development. This paper presents an artificial intelligence graphical programming learning platform based on Jetson Nano, which combines artificial intelligence education with modular software programming, provides students with a more open, intelligent, and interesting programming environment through the cross-platform development mode of "cloud service + intelligent hardware", and adopts visual programming to reduce the difficulty of artificial intelligence programming. The platform can fully tap learning resources, reduce education costs, and make artificial intelligence education more intuitive and humanized. © 2021 IEEE

关键词： Computer graphics

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Performance Analysis of Double Reconfigurable Intelligent Surfaces Assisted NOMA Networks

arXiv

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arXiv 2024年

作者： Li, Xuehua Lian, Xuanhao Yue, Xinwei Lu, Zhiping Huang, Chongwen Hou, Tianwei The Key Laboratory of Information and Communication Systems Ministry of Information Industry The Key Laboratory of Modern Measurement & Control Technology Ministry of Education Beijing Information Science and Technology University Beijing100101 China The School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing100876 China State Key Laboratory of Wireless Mobile Communications [CICT Beijing100191 China The College of Information Science and Electronic Engineering Zhejiang University Hangzhou310027 China The School of Electronic and Information Engineering Beijing Jiaotong University Beijing100044 China The Institute for Digital Communications Friedrich-Alexander Universität Erlangen-Nürnberg [FAU Erlangen91054 Germany

This paper introduces double cascaded reconfigurable intelligent surfaces (RISs) to non-orthogonal multiple access (NOMA) networks over cascaded Rician fading and Nakagami-m fading channels, where two kinds of passive RIS (PRIS) and active RIS (ARIS) are taken into consideration, called PRIS-ARIS-NOMA networks. Additionally, new closed-form and asymptotic expressions for outage probability and ergodic data rate of two non-orthogonal users are derived with the imperfect/perfect successive interference cancellation schemes. The scenario is modelled around two non-orthogonal users and focuses on analyzing their communication characteristics. Based on the approximate results, the diversity orders and ergodic data rate slopes of two users are obtained in the high signal-to-noise ratios. In addition, the system throughput of PRIS-ARIS-NOMA in delay-limited mode and delay-tolerant mode are discussed according to the outage probability and ergodic data rate. The simulation results verify the correctness of the formulas and yields the following insights: 1) The outage behaviors of PRIS-ARIS-NOMA outperforms than that of PRIS-ARIS assisted orthogonal multiple access (OMA);2)Use of PRIS-ARIS-NOMA is better than use of PRIS-ARIS-OMA in small transmit power threshold scenarios 3) By increasing the number of reflecting elements of RISs, the PRIS-ARIS-NOMA is able to achieve the enhanced outage performance;and 4) The PRIS-ARIS-NOMA has the higher ergodic data rate and system throughput than double PRISs-NOMA. Copyright © 2024, The Authors. All rights reserved.

关键词： Fading channels

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Feedback Design for Devising Optimal Epidemic control Policies

arXiv

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arXiv 2022年

作者： Niazi, Muhammad Umar B. Paré, Philip E. Johansson, Karl H. Laboratory for Information and Decision Systems Massachusetts Institute of Technology 77 Massachusetts Avenue CambridgeMA02139 United States Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Elmore Family School of Electrical and Computer Engineering Purdue University IN United States

This paper proposes a feedback design that effectively copes with uncertainties for reliable epidemic monitoring and control. There are several optimization-based methods to estimate the parameters of an epidemic model by utilizing past reported data. However, due to the possibility of noise in the data, the estimated parameters may not be accurate, thereby exacerbating the model uncertainty. To address this issue, we provide an observer design that enables robust state estimation of epidemic processes, even in the presence of uncertain models and noisy measurements. Using the estimated model and state, we then devise optimal control policies by minimizing a predicted cost functional. To demonstrate the effectiveness of our approach, we implement it on a modified SIR epidemic model. The results show that our proposed method is efficient in mitigating the uncertainties that may arise in epidemic monitoring and control. © 2022, CC BY.

关键词： Robust control

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Parallel System-Based Predictive control for Traffic Signals in Large-Scale Road Networks

Parallel System-Based Predictive Control for Traffic Signals...

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International Conference on Intelligent Transportation

作者： Xingyuan Dai Yan Zhang Yiqing Tang Hongrui Chen Jiaming Sun Fei Cong Yanan Lu Yisheng Lv School of Artificial Intelligence University of Chinese Academy of Sciences Beijing China State Key Laboratory for Management and Control of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing China China Telecom Digital City Technology Co. Ltd Xiong'an China School of Information Engineering China University of Geosciences (Beijing) Beijing China

This paper proposes a parallel system-based predictive control (PPC) method to address the problem of active traffic signal control in large-scale urban road networks. The method leverages simulated artificial transportation systems to infer the short-term future operating states of the real transportation system. During the inference process, an efficient predictive learning-based multi-agent reinforcement learning (RL) algorithm is employed to optimize the cooperative control policies. The optimized policies are then deployed to the real transportation system at fixed intervals to adapt to the real-time and dynamic traffic flow. Experimental results demonstrate that PPC outperforms traditional traffic control methods and some multi-agent RL benchmarks in large-scale road network control scenarios with nearly two hundred intersections, showcasing superior generalization capabilities.

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A Swing-Up and Stable control Strategy for Pendubot Based on Nonlinear Model Predictive Method

A Swing-Up and Stable Control Strategy for Pendubot Based on...

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Chinese Automation Congress (CAC)

作者： Lejun Wang Yiqin Liu Ruihuan Zhang Zixin Huang Zhen Cai School of Automation/School of Industrial Internet Chongqing University of Posts and Telecommunications Chongqing China Hubei Key Laboratory of Advanced Control and Intelligent Automation for Complex Systems Wuhan China Engineering Research Center of Intelligent Technology for Geo-Exploration Ministry of Education Wuhan China Hubei Key Laboratory of Digital Textile Equipment Wuhan Textile University Wuhan China School of Electrical and Information Engineering Wuhan Institute of Technology Wuhan China School of Information Engineering Wuhan City Polytechnic Wuhan China

The control objective of Pendubot is to stabilise the system in a vertically upward position by swinging up from a vertically downward position. Facing various physical constraints in practical applications, this paper proposes a swing-up stabil-isation control strategy based on a nonlinear model prediction method to accomplish the above control objective. On the basis of the system dynamics model, the forward Euler method is used to construct a nonlinear prediction model of the system. According to the control objectives and physical constraints of the system, the performance index function is designed, and then the control inputs of each sampling cycle are obtained through rolling optimisation and feedback correction, so that the system state gradually converges to the target trajectory, thus achieving the motion control objective. Based on the simulation results, it can be seen that the strategy proposed in this paper is efficient and robust under external disturbances.

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Stochastic Stability of Discrete-time Phase-coupled Oscillators over Uncertain and Random Networks

arXiv

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arXiv 2021年

作者： Jafarian, Matin Mamduhi, Mohammad H. Johansson, Karl H. The Delft Center for Systems and Control Delft University of Technology Netherlands The Automatic Control Laboratory ETH Zürich Switzerland The Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Digital Futures Sweden

This article studies stochastic relative phase stability, i.e., stochastic phase-cohesiveness, of discrete-time phase-coupled oscillators. Stochastic phase-cohesiveness in two types of networks is studied. First, we consider oscillators coupled with 2π-periodic odd functions over underlying undirected graphs subject to both multiplicative and additive stochastic uncertainties. We prove stochastic phase-cohesiveness of the network with respect to two specific, namely in-phase and anti-phase, sets by deriving sufficient coupling conditions. We show the dependency of these conditions on the size of the mean values of additive and multiplicative uncertainties, as well as the sign of the mean values of multiplicative uncertainties. Furthermore, we discuss the results under a relaxation of the odd property of the coupling function. Second, we study an uncertain network in which the multiplicative uncertainties are governed by the Bernoulli process representing the well-known Erdös-Rényi network. We assume constant exogenous frequencies and derive sufficient conditions for achieving both stochastic phase-cohesive and phase-locked solutions, i.e., stochastic phase-cohesiveness with respect to the origin. For the latter case, where identical exogenous frequencies are assumed, we prove that any positive probability of connectivity leads to phase-locking. Thorough analyses are provided, and insights obtained from stochastic analysis are discussed, along with numerical simulations to validate the analytical results. © 2021, CC BY.

关键词： Stochastic systems

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Algal Bloom Front Tracking Using an Unmanned Surface Vehicle: Numerical Experiments Based on Baltic Sea Data

Algal Bloom Front Tracking Using an Unmanned Surface Vehicle...

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OCEANS

作者： Joana Fonseca Miguel Aguiar João Borges de Sousa Karl H. Johansson Division of Decision and Control Systems School of Electrical Engineering and Computer Science and Digital Futures KTH Royal Institute of Technology Stockholm Sweden Underwater Systems and Technology Laboratory (LSTS) University of Porto Portugal

ISBN: (纸本)9781665427883

We consider the problem of tracking moving algal bloom fronts using an unmanned surface vehicle (USV) equipped with a sensor that measures the concentration of chlorophyll a. Chlorophyll a is a green pigment found in plants, and its concentration is an indicator of phytoplankton abundance. Our algal bloom front tracking mission consists of three stages: deployment, data collection, and front tracking. At the deployment stage, a satellite collects an image of the sea from which the location of the front, the reference value for the concentration at this front and, consequently, the appropriate initial position for the USV are determined. At the data collection stage, the USV collects data points to estimate the local algal gradient as it crosses the front. Finally, at the front tracking stage, an adaptive algorithm based on recursive least squares fitting using recent past sensor measures is executed. We evaluate the performance of the algorithm and its sensitivity to measurement noise through MATLAB simulations. We also present an implementation of the algorithm on the DUNE onboard software platform for marine robots and validate it using simulations with satellite model forecasts from Baltic sea data.

关键词： Water Temperature measurement Satellites Software algorithms Sea measurements Predictive models Robot sensing systems

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A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games

A Zeroth-Order Momentum Method for Risk-Averse Online Convex...

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IEEE Conference on Decision and control

作者： Zifan Wang Yi Shen Zachary I. Bell Scott Nivison Michael M. Zavlanos Karl H. Johansson Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Mechanical Engineering and Materials Science Duke University Durham NC USA Air Force Research Laboratory Eglin AFB FL USA

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

We consider risk-averse learning in repeated unknown games where the goal of the agents is to minimize their individual risk of incurring significantly high cost. Specifically, the agents use the conditional value at risk (CVaR) as a risk measure and rely on bandit feedback in the form of the cost values of the selected actions at every episode to estimate their CVaR values and update their actions. A major challenge in using bandit feedback to estimate CVaR is that the agents can only access their own cost values, which, however, depend on the actions of all agents. To address this challenge, we propose a new risk-averse learning algorithm with momentum that utilizes the full historical information on the cost values. We show that this algorithm achieves sub-linear regret and matches the best known algorithms in the literature. We provide numerical experiments for a Cournot game that show that our method outperforms existing methods.

关键词： Costs Estimation Games Numerical simulation Standards

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