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Sum-Rate Maximization in Integrated Space-Air-Ground Networks under Backhaul Capacity Constraints

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Sum-Rate Maximization in Integrated Space-Air-Ground Network...

IEEE Conference on Global Communications (GLOBECOM)

作者： Yan Kyaw Tun György Dán Division of Network and Systems Engineering School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden

Integrated space-air-ground (ISAG) networks have emerged as a promising technology for next-generation commu-nication networks, which demand higher throughput and wider coverage. However, several challenges must be addressed, such as wireless resource and interference management, transmit power control, and optimal deployment of unmanned aerial vehicles (UAV s) to achieve higher throughput. To this end, in this paper, we propose the joint transmit power control and the deployment UAV problem in the ISAG network to maximize the sum-rate of devices while guaranteeing the minimum rate requirement of each device and the wireless backhaul link constraints between UAV s and the satellite. However, solving the resulting problem is challenging since it has a non-convex structure. As a solution, we propose to decompose the problem into two subproblems. We then transform the decomposed subproblems into convex forms and solve them using successive convex approximation (SCA). Finally, we conduct extensive simulations to show the effectiveness of the proposed method, and the numerical results show that the proposed method achieves a performance gain: up to 8.35%, and 4.08% in comparison to FPA and C-UAVs schemes.

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Asymmetric Feedback Learning in Online Convex Games

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arXiv 2023年

作者： Wang, Zifan Yi, Xinlei Shen, Yi Zavlanos, Michael M. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Enginnering and Computer Science Kth Royal Institute of Technology Sweden Digital Futures StockholmSE-10044 Sweden The Lab for Information & Decision Systems Massachusetts Institute of Technology United States The Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States

This paper considers online convex games involving multiple agents that aim to minimize their own cost functions using locally available feedback. A common assumption in the study of such games is that the agents are symmetric, meaning that they have access to the same type of information or feedback. Here we lift this assumption, which is often violated in practice, and instead consider asymmetric agents;specifically, we assume some agents have access to first-order gradient feedback and others have access to the zeroth-order oracles (cost function evaluations). We propose an asymmetric feedback learning algorithm that combines the agent feedback mechanisms. We analyze the regret and Nash equilibrium convergence of this algorithm for convex games and strongly monotone games, respectively. Specifically, we show that our algorithm always performs between pure first-order and zeroth-order methods, and can match the performance of these two extremes by adjusting the number of agents with access to zeroth-order oracles. Therefore, our algorithm incorporates the pure first-order and zeroth-order methods as special cases. We provide numerical experiments on an online market problem for both deterministic and risk-averse games to demonstrate the performance of the proposed algorithm. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

Convergence Analysis of the Best Response Algorithm for Time-Varying Games

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arXiv 2023年

作者： Wang, Zifan Shen, Yi Zavlanos, Michael M. Johansson, Karl H. Division of Decision and Control Systems School of Electrical Enginnering and Computer Science KTH Royal Institute of Technology also with Digital Futures StockholmSE-10044 Sweden the Department of Mechanical Engineering and Materials Science Duke University DurhamNC United States

— This paper studies a class of strongly monotone games involving non-cooperative agents that optimize their own time-varying cost functions. We assume that the agents can observe other agents’ historical actions and choose actions that best respond to other agents’ previous actions;we call this a best response scheme. We start by analyzing the convergence rate of this best response scheme for standard time-invariant games. Specifically, we provide a sufficient condition on the strong monotonicity parameter of the time-invariant games under which the proposed best response algorithm achieves exponential convergence to the static Nash equilibrium. We further illustrate that this best response algorithm may oscillate when the proposed sufficient condition fails to hold, which indicates that this condition is tight. Next, we analyze this best response algorithm for time-varying games where the cost functions of each agent change over time. Under similar conditions as for time-invariant games, we show that the proposed best response algorithm stays asymptotically close to the evolving equilibrium. We do so by analyzing both the equilibrium tracking error and the dynamic regret. Numerical experiments on economic market problems are presented to validate our analysis. Copyright © 2023, The Authors. All rights reserved.

关键词： Cost functions

Approximate Dynamic Programming for Platoon Coordination under Hours-of-Service Regulations

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Approximate Dynamic Programming for Platoon Coordination und...

IEEE Conference on decision and control

作者： Ting Bai Alexander Johansson Karl Henrik Johansson Jonas Mårtensson Integrated Transport Research Lab and Division of Decision and Control Systems School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Stockholm Sweden

ISBN: (数字)9781665467612

ISBN: (纸本)9781665467629

Truck drivers are required to stop and rest with a certain regularity according to the driving and rest time regulations, also called Hours-of-Service (HoS) regulations. This paper studies the problem of optimally forming platoons when considering realistic HoS regulations. In our problem, trucks have fixed routes in a transportation network and can wait at hubs along their routes to form platoons with others while fulfilling the driving and rest time constraints. We propose a distributed decision-making scheme where each truck controls its waiting times at hubs based on the predicted schedules of others. The decoupling of trucks’ decision-makings contributes to an approximate dynamic programming approach for platoon coordination under HoS regulations. Finally, we perform a simulation over the Swedish road network with one thousand trucks to evaluate the achieved platooning benefits under the HoS regulations in the European Union (EU). The simulation results show that, on average, trucks drive in platoons for 37% of their routes if each truck is allowed to be delayed for 5 % of its total travel time. If trucks are not allowed to be delayed, they drive in platoons for 12 % of their routes.

关键词： Schedules Simulation Roads decision making Europe Regulation Dynamic programming

Distributionally Robust control for Chance-Constrained Signal Temporal Logic Specifications

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arXiv 2024年

作者： Kordabad, Arash Bahari Vlahakis, Eleftherios E. Lindemann, Lars Dimarogonas, Dimos V. Soudjani, Sadegh Max Planck Institute for Software Systems Kaiserslautern Germany Division of Decision and Control Systems KTH Royal Institute of Technology Stockholm Sweden Thomas Lord Department of Computer Science Viterbi School of Engineering University of Southern California Los Angeles United States

We consider distributionally robust optimal control of stochastic linear systems under signal temporal logic (STL) chance constraints when the disturbance distribution is unknown. By assuming that the underlying predicate functions are Lipschitz continuous and the noise realizations are drawn from a distribution having a concentration of measure property, we first formulate the underlying chance-constrained control problem as stochastic programming with constraints on expectations and propose a solution using a distributionally robust approach based on the Wasserstein metric. We show that by choosing a proper Wasserstein radius, the original chance-constrained optimization can be satisfied with a user-defined confidence level. A numerical example illustrates the efficacy of the method. © 2024, CC BY-NC-ND.

关键词： Stochastic systems

Real Time Nanoscale Cleaning Phenomenon Observation During Enforcing MHz Wave By Evanescent Field 241

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Real Time Nanoscale Cleaning Phenomenon Observation During E...

241st ECST Meeting

作者： Terayama, Yutaka Khajornrungruang, Panart Suzuki, Keisuke Mori, Ryotaro Hamada, Satomi Wada, Yutaka Hiyama, Hirokuni Mechanical Science and Technology Division Graduate School of Computer Science and Systems Engineering Kyushu Institute of Technology Fukuoka iizuka820-8502 Japan Mechanical Science and Technology Division Department of Intelligent and Control Systems Ebara Corporation Ltd. Kanagawa fujisawa144-8510 Japan

ISBN: (纸本)9781607685395

Post-CMP Cleaning phenomenon is considered as the detachment of the nanoparticle from the substrate surface to be cleaned, and the occasional reattachment of the nanoparticle to surface in nanoscale. However, residual contamination on the substrate has been usually inspected only after the cleaning process. Therefore, the cleaning mechanism of nanoparticles has not already clearly known. Hence, we have established dynamically observation of cleaning phenomena near the surface by applying the evanescent light which occurred a few hundred nm from the surface. In this article, detachments of φ30, 50, 70 nm silica particles and the acoustic cavitation effect were observed during enforcing 1.1 MHz waves in 60 frames per second. The main phenomenon was described that some of each silica nanoparticles were randomly intermittently detached from the surface when the cavitation effect repeatedly irregularly occurs and decays near the surface or remained on the surface during enforcing MHz wave. © 2022 ECS - The Electrochemical Society.

关键词： Silica nanoparticles

Delay-Agnostic Asynchronous Distributed Optimization

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Delay-Agnostic Asynchronous Distributed Optimization

IEEE Conference on decision and control

作者： Xuyang Wu Changxin Liu Sindri Magnusson Mikael Johansson Division of Decision and Control Systems School of EECS KTH Royal Institute of Technology Stockholm Sweden Department of Computer and System Science Stockholm University Stockholm Sweden

Existing asynchronous distributed optimization algorithms often use diminishing step-sizes that cause slow practical convergence, or fixed step-sizes that depend on an assumed upper bound of delays. Not only is such a delay bound hard to obtain in advance, but it is also large and therefore results in unnecessarily slow convergence. This paper develops asynchronous versions of two distributed algorithms, DGD and DGD-ATC, for solving consensus optimization problems over undirected networks. In contrast to alternatives, our algorithms can converge to the fixed point set of their synchronous counterparts using step-sizes that are independent of the delays. We establish convergence guarantees under both partial and total asynchrony. The practical performance of our algorithms is demonstrated by numerical experiments.

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Resilient Set-based State Estimation for Linear Time-Invariant systems Using Zonotopes

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arXiv 2022年

作者： Niazi, Muhammad Umar B. Alanwar, Amr Chong, Michelle S. Johansson, Karl Henrik Division of Decision and Control Systems Digital Futures School of Electrical Engineering and Computer Science KTH Royal Institute of Technology Stockholm Sweden Department of Computer Science and Electrical Engineering Jacobs University Bremen Germany Control Systems Technology Section Department of Mechanical Engineering Eindhoven University of Technology Netherlands

This paper considers the problem of set-based state estimation for linear time-invariant (LTI) systems under time-varying sensor attacks. Provided that the LTI system is stable and observable via every single sensor and that at least one sensor is uncompromised, we guarantee that the true state is always contained in the estimated set. We use zonotopes to represent these sets for computational efficiency. However, we show that intelligently designed stealthy attacks may cause exponential growth in the algorithm’s worst-case complexity. We present several strategies to handle this complexity issue and illustrate our resilient zonotope-based state estimation algorithm on a rotating target system. Copyright © 2022, The Authors. All rights reserved.

关键词： Linear time-invariant system

Survey of Distributed Algorithms for Resource Allocation over Multi-Agent systems

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arXiv 2024年

作者： Doostmohammadian, Mohammadreza Aghasi, Alireza Pirani, Mohammad Nekouei, Ehsan Zarrabi, Houman Keypour, Reza Rikos, Apostolos I. Johansson, Karl H. Faculty of Mechanical Engineering Semnan University Semnan Iran Department of Electrical Engineering and Computer Science Oregon State University United States Department of Mechanical Engineering University of Ottawa OttawaON Canada City University of Hong Kong China Tehran Iran Faculty of Electrical Engineering Semnan University Semnan Iran Department of Electrical and Computer Engineering Division of Systems Engineering Boston University BostonMA United States Division of Decision and Control Systems KTH Royal Institute of Technology Sweden

Resource allocation and scheduling in multi-agent systems present challenges due to complex interactions and decentralization. This survey paper provides a comprehensive analysis of distributed algorithms for addressing the distributed resource allocation (DRA) problem over multi-agent systems. It covers a significant area of research at the intersection of optimization, multiagent systems, and distributed consensus-based computing. The paper begins by presenting a mathematical formulation of the DRA problem, establishing a solid foundation for further exploration. Real-world applications of DRA in various domains are examined to underscore the importance of efficient resource allocation, and relevant distributed optimization formulations are presented. The survey then delves into existing solutions for DRA, encompassing linear, nonlinear, primal-based, and dual-formulation-based approaches. Furthermore, this paper evaluates the features and properties of DRA algorithms, addressing key aspects such as feasibility, convergence rate, and network reliability. The analysis of mathematical foundations, diverse applications, existing solutions, and algorithmic properties contributes to a broader comprehension of the challenges and potential solutions for this domain. © 2024, CC BY.

关键词： Multi agent systems