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Youth Academic Annual Conference of Chinese Association of Automation (YAC)

作者： Yao Zou Haojie Zhang Wei He Institute of Artificial Intelligence University of Science and Technology Beijing Beijing P. R. China

ISBN: (数字)9781728176840

ISBN: (纸本)9781728176857

The consensus problem of second-order multivehicle systems with inertias in terms of a general directed network topology is studied. Rather than the current consensus algorithms for multi-vehicle systems with just scalar inertias, we allow the inertias to be matrices. What's more, the inertia matrices are assumed to be heterogeneous as well as unavailable. In particular, a fully distributed consensus algorithm is proposed such that global information is unnecessary for the achievement of the consensus objective. Moreover, a novel adaptive strategy is designed to address the dilemma arising from the heterogeneity and unavailability of the inertia matrices. It is demonstrated that, under the strongly connected graph condition, the designed distributed algorithm ensures the asymptotic convergence of the required consensus objective. The efficacy of the developed distributed algorithm is finally validated by numerical simulations.

关键词： Adaptive systems Network topology Decentralized control Consensus algorithm Numerical simulation distributed algorithms Convergence

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ADMM Algorithm based distributed Energy Management in Active Distribution Network

ADMM Algorithm based Distributed Energy Management in Active...

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National Power Systems Conference (NPSC)

作者： Satish Kumar Singh P. B. S. Kiran Naran M. Pindoriya Discipline of Electrical Engineering IIT Gandhinagar Palaj India

ISBN: (数字)9781728185521

ISBN: (纸本)9781728185552

distributed energy management algorithms are remarkably efficient in resolving load variation issues and addressing a high peak to average power ratio. A distributed algorithm promotes individual participation, bilateral coordination, data privacy, and consumers' economic benefit. This paper presents an alternating direction method of multipliers (ADMM) based distributed algorithm for energy management in a distribution network. It decomposes the centralized energy management problem into a distribution system operator (DSO) and load aggregator (LA) level sub-problems. The DSO objective is to minimize energy cost and power loss in the network, whereas LA intends to reduce its energy consumption cost. The DSO and LA optimization problems are solved independently and coordinated via a central coordinator. The algorithm is tested on a modified 15-node distribution network to substantiate its effectiveness. The simulation results are presented for flexible loads, solar PV generation, and battery energy storage systems. Also, we analyzed the impact of the penalty factor on the algorithm convergence and the network power consumption.

关键词： Distribution networks Convex functions Batteries distributed algorithms Optimization Tuning Convergence

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distributed Heavy-Ball Nash Equilibrium Seeking Algorithm in Aggregative Games

Distributed Heavy-Ball Nash Equilibrium Seeking Algorithm in...

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Chinese Control Conference (CCC)

作者： Chenhui Song Chenpeng Wu Zhongtao Lv Fangshuo Zhang Jingyu Li Shaofu Yang Chien-Shiung Wu College Southeast University Nanjing P. R. China School of Economics and Management Southeast University Nanjing P. R. China School of Computer Science and Engineering Southeast University Nanjing P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In this paper, we address the distributed Nash equilibrium seeking problem in an aggregative game, in which each agent is required to optimize a self-interested objective function that depends on both its own decision and the aggregate of all agents' decisions. By integrating the heavy-ball method with consensus-based gradient method, a novel distributed algorithm is proposed for seeking the Nash equilibrium with an improved convergence rate. Rigorous theoretical analysis is provided to prove the convergence of the algorithm. Finally, detailed numerical simulation results are provided to show the effectiveness and the acceleration performance of our algorithm.

关键词： Games Nash equilibrium distributed algorithms Convergence Acceleration Electronic mail Linear programming

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Nash and Wardrop Equilibria in Aggregative Games With Coupling Constraints

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 2019年第4期64卷 1373-1388页

作者： Paccagnan, Dario Gentile, Basilio Parise, Francesca Kamgarpour, Maryam Lygeros, John Swiss Fed Inst Technol Automat Control Lab CH-8092 Zurich Switzerland MIT Lab Informat & Decis Syst Cambridge MA 02139 USA

We consider the framework of aggregative games, in which the cost function of each agent depends on his own strategy and on the average population strategy. As first contribution, we investigate the relations between the concepts of Nash and Wardrop equilibria. By exploiting a characterization of the two equilibria as solutions of variational inequalities, we bound their distance with a decreasing function of the population size. As second contribution, we propose two decentralized algorithms that converge to such equilibria and are capable of coping with constraints coupling the strategies of different agents. Finally, we study the applications of charging of electric vehicles and of route choice on a road network.

关键词： Aggregative games coupling constraints generalized Nash equilibrium distributed algorithms large-scale systems electric vehicles vehicle routing

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distributed Nash Equilibrium Seeking of Aggregative Games for High-Order Systems

Distributed Nash Equilibrium Seeking of Aggregative Games fo...

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Chinese Control Conference (CCC)

作者： Zhongqing Zheng Yanqiong Zhang Bin Zhang Rui Yin School of Information and Electronic Engineering Zhejiang Gongshang University Hangzhou P. R. China School of Automation Hangzhou Dianzi University Hangzhou P. R. China College of Information and Communication National University of Defense and Technology P. R. China School of Electronics and Communication Engineering Zhejiang University City College Hangzhou P. R. China

ISBN: (数字)9789881563903

ISBN: (纸本)9781728165233

In this paper, the Nash equilibrium seeking (NES) problem of aggregative games is investigated for high-order multiagents systems, where the cost function for each agent depends on its decision variable and the aggregate of all other decisions. To solve the problem, we employ the embedded technology to decouple the primal problem into two parts: decision planning and tracking. We first construct a single integrator system for the NES to generate the optimal reference decision trajectory, and then we propose the distributed algorithms to make the nonlinear Euler-Lagrange (EL) systems and the general high-order linear system track the optimal reference decision path, respectively. Finally, simulations are given to validate the effectiveness of the theoretical analysis.

关键词： Games Nash equilibrium distributed algorithms Cost function Linear systems Planning Electronic mail

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distributed Optimization for Linear Multi-Agent Systems Subject to DoS Attacks

Distributed Optimization for Linear Multi-Agent Systems Subj...

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IEEE Conference on Decision and Control

作者： Dan Liu Rong Su School of Electrical and Electronic Engineering Nanyang Technological University Singapore

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

This paper discussed the distributed optimization problem where interagent communication is subject to DoS attacks. An event-based communication strategy is adopted to determine the signal transmission time, and then a resilient control algorithm is put forward to achieve consensus and meanwhile minimize the global objective function. By means of a positive invariant set and a quadratic Lyapunov functional, the convergence of the developed algorithm is guaranteed. The effectiveness of the theoretical result is illustrated by a simulation example.

关键词： Optimization distributed algorithms Convergence Stability analysis Radio frequency Multi-agent systems Linear programming

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Bounding the locality of distributed routing algorithms

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distributed COMPUTING 2013年第1期26卷 39-58页

作者： Bose, Prosenjit Carmi, Paz Durocher, Stephane Carleton Univ Sch Comp Sci Ottawa ON K1S 5B6 Canada Ben Gurion Univ Negev Dept Comp Sci Beer Sheva Israel Univ Manitoba Dept Comp Sci Winnipeg MB R3T 2N2 Canada

We examine bounds on the locality of routing. A local routing algorithm makes a sequence of distributed forwarding decisions, each of which is made using only local information. Specifically, in addition to knowing the node for which a message is destined, an intermediate node might also know (1) its local neighbourhood (the subgraph corresponding to all network nodes within hops of itself, for some fixed ), (2) the node from which the message originated, and (3) the incoming port (which of its neighbours last forwarded the message). Our objective is to determine, as varies, which of these parameters are necessary and/or sufficient to permit local routing on a network modelled by a connected undirected graph. In particular, we establish tight bounds on for the feasibility of deterministic -local routing for various combinations of these parameters, as well as corresponding bounds on dilation (the worst-case ratio of actual route length to shortest path length).

关键词： distributed algorithms Local routing Dilation

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distributed Computation of Nash Equilibria for Monotone Aggregative Games via Iterative Regularization

Distributed Computation of Nash Equilibria for Monotone Aggr...

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IEEE Conference on Decision and Control

作者： Jinlong Lei Uday V. Shanbhag Jie Chen Tongji University Shanghai China Shanghai Institute of Intelligent Science and Technology Tongji University Shanghai China Pennsylvania State University University Park PA USA

ISBN: (数字)9781728174471

ISBN: (纸本)9781728174488

This work considers an aggregative game over time-varying graphs, where each player's cost function depends on its own strategy and the aggregate of its competitors' strategies. Though the aggregate is unknown to any given player, each player may interact with its neighbors to construct an estimate of the aggregate. We design a distributed iterative Tikhonov regularization method in which each player may independently choose its steplengths and regularization parameters while meeting some overall coordination requirements. Under a monotonicity assumption on the concatenated player-specific gradient map, we prove that the generated sequence converges to the least-norm Nash equilibrium (i.e., a Nash equilibrium with the smallest two-norm) and validate the proposed method on a networked Nash-Cournot equilibrium problem.

关键词： Games Aggregates Nash equilibrium distributed algorithms Cost function Stochastic processes Standards

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Stability and convergence of distributed algorithms for the OPF problem

Stability and convergence of distributed algorithms for the ...

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IEEE Annual Conference on Decision and Control

作者： Eoin Devane Ioannis Lestas Cambridge Centre for Analysis Centre for Mathematical Sciences University of Cambridge Wilberforce Road Cambridge CB3 OWA United Kingdom Department of Engineering University of Cambridge Trumpington Street Cambridge CB2 1PZ United Kingdom

ISBN: (纸本)9781467357159

Many modern power networks are partitioned in nature, with disjoint components of the overall network controlled by competing operators. The problem of solving the Optimal Power Flow (OPF) problem in a distributed manner is therefore of significant interest. For networks in which the high-level structure has tree topology, we analyze a dual decomposition approach to solving a recent convex relaxation of the OPF problem for the overall network in a distributed manner. Incorporating higher-order dynamics in terms of local auxiliary variables, we prove a result of guaranteed convergence to the solution set for sufficiently small values of the step size.

关键词： distributed algorithms Converge step size Power grids Tree Topology level structure Network Solution Set

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distributed Online algorithms for the Agent Migration Problem in WSNs

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MOBILE NETWORKS & APPLICATIONS 2013年第5期18卷 622-638页

作者： Tziritas, Nikos Lalis, Spyros Khan, Samee Ullah Loukopoulos, Thanasis Xu, Cheng-Zhong Lampsas, Petros Chinese Acad Sci Beijing Peoples R China Univ Thessaly Thessaly Greece IRETETH CERTH Thessaly Greece N Dakota State Univ Fargo ND 58105 USA Technol Educ Inst Lamia Lamia Greece Wayne State Univ Detroit MI USA

The mobile agent paradigm has been adopted by several systems in the area of wireless sensor networks as it enables a flexible distribution and placement of application components on nodes, at runtime. Most agent placement and migration algorithms proposed in the literature, assume that the communication rates between agents remain stable for a sufficiently long time to amortize the migration costs. Then, the problem is that frequent changes in the application-level communication may lead to several non-beneficial agent migrations, which may actually increase the total network cost, instead of decreasing it. To tackle this problem, we propose two distributed algorithms that take migration decisions in an online fashion, trying to deal with fluctuations in agent communication. The first algorithm is more of theoretical value, as it assumes infinite storage to keep information about the message exchange history of agents, while the second algorithm is a refined version that works with finite storage and limited information. We describe these algorithms in detail, and provide proofs for their competitive ratio vs. an optimal oracle. In addition, we evaluate the performance of the proposed algorithms for different parameter settings through a series of simulated experiments, also comparing their results with those achieved by an optimal static placement that is computed with full (a posteriori) knowledge of the execution scenarios. Our theoretical and experimental results are a strong indication for the robustness and effectiveness of the proposed algorithms.

关键词： distributed algorithms Online algorithms Optimizing network cost Wireless sensor and actuator networks Agent placement Agent migration Agent-based programming

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