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Cycle Flow Formulation of Optimal Network Flow Problems and Respective Distributed Solutions

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IEEE/CAA Journal of Automatica Sinica 2019年第5期6卷 1251-1260页

作者： Reza Asadi Solmaz S.Kia the Computer Science Department University of CaliforniaIrvineCA 92697 USA the Mechanical and Aerospace Engineering Department University of CaliforniaIrvineCA 92697 USA

In this paper, we use the cycle basis from graph theory to reduce the size of the decision variable space of optimal network flow problems by eliminating the aggregated flow conservation constraint. We use a minimum cost flow problem and an optimal power flow problem with generation and storage at the nodes to demonstrate our decision variable reduction method.The main advantage of the proposed technique is that it retains the natural sparse/decomposable structure of network flow problems. As such, the reformulated problems are still amenable to Distributed solutions. We demonstrate this by proposing a Distributed alternating direction method of multipliers(ADMM)solution for a minimum cost flow problem. We also show that the communication cost of the Distributed ADMM algorithm for our proposed cycle-based formulation of the minimum cost flow problem is lower than that of a Distributed ADMM algorithm for the original arc-based formulation.

关键词： ADMM cycle basis Distributed optimization optimal network Flow

Distributed Majorization-Minimization for Laplacian Regularized Problems

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IEEE/CAA Journal of Automatica Sinica 2019年第1期6卷 45-52页

作者： Jonathan Tuck David Hallac Stephen Boyd IEEE the Department of Electrical Engineering Stanford University

We consider the problem of minimizing a block separable convex function(possibly nondifferentiable, and including constraints) plus Laplacian regularization, a problem that arises in applications including model fitting, regularizing stratified models, and multi-period portfolio optimization. We develop a Distributed majorization-minimization method for this general problem, and derive a complete, self-contained, general,and simple proof of convergence. Our method is able to scale to very large problems, and we illustrate our approach on two applications, demonstrating its scalability and accuracy.

关键词： Convex optimization Distributed optimization graphical networks Laplacian regularization

Hybrid partition-and network-level scheduling design for Distributed integrated modular avionics systems

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Chinese Journal of Aeronautics 2020年第1期33卷 308-323页

作者： Xuan ZHOU Huagang XIONG Feng HE School of Electronic and Information Engineering Beihang UniversityBeijing 100191China

Distributed Integrated Modular Avionics(DIMA)develops from Integrated Modular Avionics(IMA)and realizes Distributed integration of multiple sub-function areas.Timetriggered network provides effective support for time synchronization and information coordination in DIMA systems.However,inconsistency between processing resources and communication network destroys the time determinism benefiting from partitions and time-triggered mechanism.To ensure such time determinism and achieve guaranteed real-time performance,system design should collectively provide a global communication scheme for messages in network domain and a corresponding execution scheme for partitions in processing domain.This paper firstly establishes a general DIMA model which coordinates partitioned processing and time-triggered communication,and then proposes a hybrid scheduling algorithm using Mixed Integer Programming to produce feasible system schemes.Furthermore,incrementally integrating new functions causes upgrades or reconfigurations of DIMA systems and will generate integration cost.To control such cost,this paper further develops an optimization algorithm based on Maximum Satisfiability Problem and guarantees that the scheduling design for upgraded DIMA systems inherit their original schemes as much as possible.Finally,two typical cases,including a simple fully connected DIMA system case and an industrial DIMA system case,are constructed to illustrate our DIMA model and validate the effectiveness of our hybrid scheduling algorithms.

关键词： Distributed integrated modular avionics End-to-end delay Incremental integration cost Maximum satisfiability problem Mixed integer programming Scheduling algorithms

Iterative Learning Control for Distributed Parameter Systems Based on Non-Collocated Sensors and Actuators

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 865-871页

作者： Jianxiang Zhang Baotong Cui Xisheng Dai Zhengxian Jiang Key Laboratory of Advanced Process Control for Light Industry(Ministry of Education) School of Internet of Things EngineeringJiangnan UniversityWuxi 214122China School of Electrical and Information Engineering Guangxi University of Science and TechnologyLiuzhou 545006China School of Science Jiangnan UniversityWuxi 214122China

In this paper, an open-loop PD-type iterative learning control(ILC) scheme is first proposed for two kinds of Distributed parameter systems(DPSs) which are described by parabolic partial differential equations using non-collocated sensors and actuators. Then, a closed-loop PD-type ILC algorithm is extended to a class of Distributed parameter systems with a non-collocated single sensor and m actuators when the initial states of the system exist some errors. Under some given assumptions, the convergence conditions of output errors for the systems can be obtained. Finally, one numerical example for a Distributed parameter system with a single sensor and two actuators is presented to illustrate the effectiveness of the proposed ILC schemes.

关键词： Actuators Distributed parameter system iterative learning control PD-type ILC scheme sensors

Bigflow: A General Optimization Layer for Distributed Computing Frameworks

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Journal of Computer Science & Technology 2020年第2期35卷 453-467页

作者： Yun-Cong Zhang Xiao-Yang Wang Cong Wang Yao Xu Jian-Wei Zhang Xiao-Dong Lin Guang-Yu Sun Gong-Lin Zheng Shan-Hui Yin Xian-Jin Ye Li Li Zhan Song Dong-Dong Miao Baidu Inc. Beijing 100193China Center for Energy-Efficient Computing and Applications Peking UniversityBeijing 100871China

As data volumes grow rapidly, Distributed computations are widely employed in data-centers to provide cheap and efficient methods to process large-scale parallel datasets. Various computation models have been proposed to improve the abstraction of Distributed datasets and hide the details of parallelism. However, most of them follow the single-layer partitioning method, which limits developers to express a multi-level partitioning operation succinctly. To overcome the problem, we present the NDD (Nested Distributed Dataset) data model. It is a more compact and expressive extension of Spark RDD (Resilient Distributed Dataset), in order to remove the burden on developers to manually write the logic for multi-level partitioning cases. Base on the NDD model, we develop an open-source framework called Bigflow, which serves as an optimization layer over computation engines from most widely used processing frameworks. With the help of Bigflow, some advanced optimization techniques, which may only be applied by experienced programmers manually, are enabled automatically in a Distributed data processing job. Currently, Bigflow is processing about 3 PB data volumes daily in the data-centers of Baidu. According to customer experience, it can significantly save code length and improve performance over the intuitive programming style.

关键词： Distributed computing programming model optimization technique

Distributed H∞ filtering of nonlinear systems with random topology by an event-triggered protocol

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Science China(Information Sciences) 2021年第10期64卷 206-220页

作者： Yun CHEN Mengze ZHU Renquan LU Anke XUE Key Lab for IoT and Information Fusion Technology of Zhejiang Hangzhou Dianzi University School of Automation Guangdong University of Technology

Applying an event-triggered protocol, this paper proposes a Distributed Hfilter design for nonlinear perturbed systems under fading measurements with random topology. Nonlinearities in this system obey the one-sided Lipschitz constraint, which embraces the conventional Lipschitz condition as a special case.The sensor network allows random variations of the interconnection strengths between adjacent nodes, and the connection coefficient is determined as the product of a constant and a stochastic variable with a known probabilistic feature. To reduce the unnecessary data transmission and efficiently use the limited bandwidth,the transmissions are orchestrated by an event-triggered regulating strategy. A stochastic bounded real lemma is established for the resulting error dynamics. Based on the presented matrix decomposition, which removes the direct coupling between the statistical information of interconnection strengths and the filter gain, the Distributed Hfilter gain can be explicitly expressed and easily solved. The usefulness of the theoretical method is demonstrated in a simulation study.

关键词： sensor network Distributed H ∞ filtering one-sided Lipschitz condition event-triggered protocol random topology

Distributed Control of Multiple-Bus Microgrid With Paralleled Distributed Generators

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IEEE/CAA Journal of Automatica Sinica 2019年第3期6卷 676-684页

作者： Bo Fan Jiangkai Peng Jiajun Duan Qinmin Yang Wenxin Liu IEEE the State Key Laboratory of Industrial Control Technology College of Control Science and Engineering Zhejiang University the Smart Microgrid and Renewable Technology (SMRT) Research Laboratory Department of Electrical and Computer Engineering Lehigh University the Global Energy Interconnection Research Institute North America (GEIRINA)

A microgrid is hard to control due to its reduced inertia and increased uncertainties. To overcome the challenges of microgrid control, advanced controllers need to be developed.In this paper, a Distributed, two-level, communication-economic control scheme is presented for multiple-bus microgrids with each bus having multiple Distributed generators(DGs) connected in parallel. The control objective of the upper level is to calculate the voltage references for one-bus subsystems. The objectives of the lower control level are to make the subsystems' bus voltages track the voltage references and to enhance load current sharing accuracy among the local DGs. Firstly, a Distributed consensusbased power sharing algorithm is introduced to determine the power generations of the subsystems. Secondly, a discrete-time droop equation is used to adjust subsystem frequencies for voltage reference calculations. Finally, a Lyapunov-based decentralized control algorithm is designed for bus voltage regulation and proportional load current sharing. Extensive simulation studies with microgrid models of different levels of detail are performed to demonstrate the merits of the proposed control scheme.

关键词： Coordinate control decentralized control multiple-bus microgrid paralleled Distributed generations power sharing algorithm

ADMM-based Distributed Algorithm for Economic Dispatch in Power Systems With Both Packet Drops and Communication Delays

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IEEE/CAA Journal of Automatica Sinica 2020年第3期7卷 842-852页

作者： Qing Yang Gang Chen Ting Wang State Key Laboratory of Power Transmission Equipment and System Security and New Technology and the School of AutomationChongqing UniversityChongqing 400044China IEEE

By virtue of alternating direction method of multipliers(ADMM), Newton-Raphson method, ratio consensus approach and running sum method, two Distributed iterative strategies are presented in this paper to address the economic dispatch problem(EDP) in power systems. Different from most of the existing Distributed ED approaches which neglect the effects of packet drops or/and time delays, this paper takes into account both packet drops and time delays which frequently occur in communication networks. Moreover, directed and possibly unbalanced graphs are considered in our algorithms, over which many Distributed approaches fail to converge. Furthermore, the proposed schemes can address the EDP with local constraints of generators and nonquadratic convex cost functions, not just quadratic ones required in some existing ED approaches. Both theoretical analyses and simulation studies are provided to demonstrate the effectiveness of the proposed schemes.

关键词： Alternating direction method of multipliers(ADMM) average consensus directed graph(digraph) Distributed algorithm economic dispatch packet drops time delays

An application of game theory in Distributed collaborative decision making

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Frontiers of Mechanical Engineering 2019年第1期14卷 85-101页

作者： Angran XIAO Department Mechanical Engineering and Industrial Design Technology New York City College of TechnologyCity University of New YorkBrooklynNY 11201USA

In a Distributed product realization environment,new paradigms and accompanying software systems are necessary to support the collaborative work of geographically dispersed engineering teams from different disciplines who have different knowledge,experience,tools and resources.To verify the concept of collaboration by separation,we propose a generic information communication medium to enable knowledge representation and exchange between engineering teams,a digital interface.Across digital interfaces,each engineering team maintains its own perspective towards the product realization problem,and each controls a subset of design variables and seeks to maximize its own payoff function subject to individual constraints.Hence,we postulate the use of principles from game theory to model the relationships between engineering teams and facilitate collaborative decision making without causing unnecessary information exchange or iteration across digital interfaces.A product design and manufacturing scenario is introduced to demonstrate the efficacy of using game theory to maintain a clean interface between design and manufacturing teams.

关键词： collaboration Distributed product realization game theory digital interface