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Augmented input estimation in multiple maneuvering target tracking

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Journal of systems engineering and Electronics 2019年第5期30卷 841-851页

作者： HADAEGH Mahmoudreza KHALOOZADEH Hamid BEHESHTI Mohammadtaghi Department of Electrical and Computer Engineering Science and Research BranchIslamic Azad UniversityTehran ***Iran Department of Systems and Control K.N.Toosi University of TechnologyTehran ***Iran Department of Electrical Engineering Control GroupTarbiat Modares UniversityTehran 14115111Iran

This paper presents augmented input estimation(AIE)for multiple maneuvering target ***-target tracking(MTT)is based on two main parts,data association and *** data association(DA),the best observations are assigned to the considered *** real conditions,the number of observations is more than targets and also locations of observations are often so scattered that the association between targets and observations cannot be done *** this case,for general MTT problems with unknown numbers of targets,we present a Markov chain Monte-Carlo DA(MCMCDA)algorithm that approximates the optimal Bayesian filter with low complexity in *** DA,estimation and tracking should be *** in general cases,many targets can have maneuvering motions,then AIE is proposed to cover both the non-maneuvering and maneuvering parts of motion and the maneuver detection procedure is *** model with an input estimation(IE)approach is a special augmentation in the state space model which considers both the state vector and the unknown input vector as a new augmented state *** comparisons based on the Monte-Carlo simulations are also made to evaluate the performances of the proposed method and other older methods in MTT.

关键词： multi-target tracking (MTT) Markov chain Monte-Carlodata association (MCMCDA) data association (DA) augmentedinput estimation (AIE)

Quantized Distributed Nonconvex Optimization with Linear Convergence

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Quantized Distributed Nonconvex Optimization with Linear Con...

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

Suppressing the endemic equilibrium in SIS epidemics: A state dependent approach

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arXiv 2021年

作者： Wang, Yuan Gracy, Sebin Ishii, Hideaki Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Digital Futures Stockholm Sweden Department of Computer Science Tokyo Institute of Technology

This paper considers the susceptible-infected-susceptible (SIS) epidemic model with an underlying network structure and focuses on the effect of social distancing to regulate the epidemic level. We demonstrate that if each subpopulation is informed of its infection rate and reduces interactions accordingly, the fraction of the subpopulation infected stays below half for all time instants. To this end, we first modify the basic SIS model by introducing a state dependent parameter representing the frequency of interactions between subpopulations. Thereafter, we show that for this modified SIS model, the spectral radius of a suitably-defined matrix being not greater than one causes all the agents, regardless of their initial sickness levels, to converge to the healthy state;assuming non-trivial disease spread, the spectral radius being greater than one leads to the existence of a unique endemic equilibrium, which is also asymptotically stable. Finally, by leveraging the aforementioned results, we show that the fraction of (sub)populations infected never exceeds half. Copyright © 2021, The Authors. All rights reserved.

关键词： Epidemiology

2-D Directed Formation control Based on Bipolar Coordinates

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arXiv 2021年

作者： Mehdifar, Farhad Bechlioulis, Charalampos P. Hendrickx, Julien M. Dimarogonas, Dimos V. The Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden The Division of Systems and Control The Department of Electrical and Computer Engineering University of Patras Patra Greece INMA ICTEAM institute UCLouvain Louvain-la-Neuve Belgium

This work proposes a novel 2-D formation control scheme for acyclic triangulated directed graphs (a class of minimally acyclic persistent graphs) based on bipolar coordinates with (almost) global convergence to the desired shape. Prescribed performance control is employed to devise a decentralized control law that avoids singularities and introduces robustness against external disturbances while ensuring predefined transient and steady-state performance for the closed-loop system. Furthermore, it is shown that the proposed formation control scheme can handle formation maneuvering, scaling, and orientation specifications simultaneously. Additionally, the proposed control law is implementable in agents' arbitrarily oriented local coordinate frames using only low-cost onboard vision sensors, which are favorable for practical applications. Finally, a formation maneuvering simulation study verifies the proposed approach. Copyright © 2021, The Authors. All rights reserved.

关键词： Directed graphs

Retraction Note: EoT-driven hybrid ambient assisted living framework with naïve Bayes–firefly algorithm

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Neural Computing and Applications 2024年第24期36卷 15215-15215页

作者： Hassan, Mohammed K. Desouky, Ali I. El Badawy, Mahmoud M. Sarhan, Amany M. Elhoseny, Mohamed Gunasekaran, M. Department of Computer Engineering and Systems Faculty of Engineering Mansoura University Mansoura City Egypt Department of Computer Engineering and Automatic Control Faculty of Engineering Tanta University Tanta Egypt Faculty of Computers and Information Mansoura University Mansoura Egypt University of California Davis USA

Distributed Optimal Allocation with Quantized Communication and Privacy-Preserving Guarantees

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arXiv 2021年

作者： Nylöf, Jakob Rikos, Apostolos I. Gracy, Sebin Johansson, Karl Henrik Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology and Digital Futures Stockholm Sweden Department of Electrical and Computer Engineering Rice University HoustonTX United States

In this paper, we analyze the problem of optimally allocating resources in a distributed and privacy-preserving manner. We propose a novel distributed optimal resource allocation algorithm with privacy-preserving guarantees, which operates over a directed communication network. Our algorithm converges in finite time and allows each node to process and transmit quantized messages. Our algorithm utilizes a distributed quantized average consensus strategy combined with a privacy-preserving mechanism. We show that the algorithm converges in finite-time, and we prove that, under specific conditions on the network topology, nodes are able to preserve the privacy of their initial state. Finally, to illustrate the results, we consider an example where test kits need to be optimally allocated proportionally to the number of infections in a region. It is shown that the proposed privacy-preserving resource allocation algorithm performs well with an appropriate convergence rate under privacy guarantees. © 2021, CC BY.

关键词： Resource allocation

Highway Traffic control via Smart e-Mobility – Part II: Dutch A13 Case Study

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arXiv 2021年

作者： Cenedese, Carlo Cucuzzella, Michele Scherpen, Jacquelien M.A. Grammatico, Sergio Cao, Ming Department of Information Technology and Electrical Engineering ETH Zürich Zurich Switzerland Department of Electrical Computer and Biomedical Engineering University of Pavia Pavia Italy Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Netherlands Delft Center for Systems and Control TU Delft Netherlands

In this paper, we study how to alleviate highway traffic congestions by encouraging plug-in electric and hybrid vehicles to stop at charging stations around peak congestion times. Specifically, we focus on a case study and simulate the adoption of a dynamic charging price depending on the traffic congestion. We use real traffic data of the A13 highway stretch between The Hague and Rotterdam, in The Netherlands, to identify the Cell Transmission Model. Then, we apply the algorithm proposed in [1](Part I: Theory) to different scenarios, validating the theoretical results and showing the benefits of our strategy in terms of traffic congestion alleviation. Finally, we carry out a sensitivity analysis of the proposed algorithm and discuss how to optimize its performance. Copyright © 2021, The Authors. All rights reserved.

关键词： Traffic congestion

Highway Traffic control via Smart e-Mobility - Part I: Theory

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arXiv 2021年

—In this paper, we study how to alleviate highway traffic congestion by encouraging plug-in hybrid and electric vehicles to stop at a charging station around peak congestion times. Specifically, we design a pricing policy to make the charging price dynamic and dependent on the traffic congestion, predicted via the cell transmission model, and the availability of charging spots. Furthermore, we develop a novel framework to model how this policy affects the drivers’ decisions by formulating a mixed-integer potential game. Technically, we introduce the concept of "road-to-station" (r2s) and "station-to-road" (s2r) flows, and show that the selfish actions of the drivers converge to charging schedules that are individually optimal in the sense of Nash. In the second part of this work, submitted as a separate paper (Part II: Case Study), we validate the proposed strategy on a simulated highway stretch between The Hague and Rotterdam, in The Netherlands. Copyright © 2021, The Authors. All rights reserved.

关键词： Roads and streets

Joint Optimization of Wind Farm Layout Considering Optimal control

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arXiv 2021年

作者： Chen, Kaixuan Lina, 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

The wake effect is one of the leading causes of energy losses in offshore wind farms (WFs). Both turbine placement and cooperative control can influence the wake interactions inside the WF and thus the overall WF power production. Traditionally, greedy control strategy is assumed in the layout design phase. To exploit the potential synergy between the WF layout and control so that a system-level optimal layout can be obtained with the greatest energy yields, the layout optimization should be performed with cooperative control considerations. For this purpose, a novel two-stage WF layout optimization model is developed in this paper. Cooperative WF control of both turbine yaw and axis-induction are considered in the WF layout design. However, the integration of WF control makes the layout optimization much more complicated and results in a large-scale nonconvex problem, hindering the application of current layout optimization methods. To increase the computational efficiency, we leverage the hierarchy and decomposability of the joint optimization problem and design a decomposition-based hybrid method (DBHM). Instead of manipulating all the variables simultaneously, the joint optimization problem is decomposed into several subproblems and their coordination. Case studies are carried out on different WFs. It is shown that WF layouts with higher energy yields can be obtained by the proposed joint optimization compared to traditional separate layout optimization. Moreover, the computational advantages of the proposed DBHM on the considered joint layout optimization problem are also demonstrated. © 2021, CC BY.

关键词： Electric utilities