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Push-Sum Based Algorithm for Constrained convex Optimization Problem and Its Potential Application in Smart Grid

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IEEE/CAA Journal of Automatica Sinica 2022年第10期9卷 1889-1891页

作者： Qian Xu Zao Fu Bo Zou Hongzhe Liu Lei Wang the State Grid Zhejiang Economic Research Institute Hangzhou 310008China Beijing Yinshan Technology Co. LTD.Beijing 100871China

Dear Editor,This letter aims to investigate the optimization problem where the decision variable is contained in a closed convex set.By combing the gradient decent-like method with the push-sum algorithm framework,we design the distributed iterative formulas under the condition that the considered graphs sequence is time-varying and unbalanced.

关键词： set letter convex

Relaxed Stability Criteria for Delayed Generalized Neural Networks via a Novel Reciprocally convex Combination

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IEEE/CAA Journal of Automatica Sinica 2023年第7期10卷 1631-1633页

作者： Yibo Wang Changchun Hua Poo Gyeon Park School of Electrical Engineering Yanshan UniversityQinhuangdao 066004China Department of Electrical Engineering Pohang University of Science and TechnologyPohang 37673South Korea

Dear Editor,This letter examines the stability issue of generalized neural networks(GNNs) with time-varying delay based on a novel reciprocally convex combination(RCC). By considering a new matrix polynomial, the proposed novel reciprocally convex method leads to a tight bound for integral inequality combination and encompasses several existing approaches as special cases.

关键词： convex reciprocal inequality

An Extended convex Combination Approach for Quadratic L_(2)Performance Analysis of Switched Uncertain Linear Systems

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IEEE/CAA Journal of Automatica Sinica 2022年第9期9卷 1706-1709页

作者： Yufang Chang Guisheng Zhai Lianglin Xiong Bo Fu Hubei Collaborative Innovation Center for High-efficiency Utilization of Solar Energy Hubei University of TechnologyWuhan 430068China the Department of Mathematical Sciences Shibaura Institute of TechnologySaitama 337-8570Japan the School of Mathematics and Computer Science Yunnan Minzu UniversityKunming 650500China

Dear Editor,This letter is concerned with quadratic L_(2) performance(quadratic stability and L_(2) gain)for switched uncertain linear systems(SULS)with norm-bounded uncertainties.Assuming that no single uncertain subsystem achieves quadratic L_(2) performanceγbut a convex combination of the subsystems can make it,we propose a state-dependent switching law such that the SULS achieves the desired quadratic L_(2) performance.The discussion is extended to the SULS with state feedback control,and a sufficient condition is proposed to design the state feedback gains and the switching law simultaneously.

关键词： quadratic letter convex

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量子信道的凸优化重建技术

Science Bulletin 2020年第4期65卷 286-292页

作者：黄选纶高俊焦志强严增泉张者勇陈丹扬张晰嵇玲金贤敏 Center for Integrated Quantum Information Technologies(IQIT) School of Physics and Astronomy and State Key Laboratory of Advanced Optical Communication Systems and NetworksShanghai Jiao Tong UniversityShanghai 200240China CAS Center for Excellence and Synergetic Innovation Center in Quantum Information and Quantum Physics University of Science and Technology of ChinaHefei 230026China

对于实际的量子信道,它可能包含一系列非幺正的操作,但是过去的研究基本都集中在幺正或近幺正的情况,对于非幺正过程的研究还是很少.本文借用经典人工智能技术中常用的凸优化方法,将量子过程层析构造成一个最小二乘的优化问题,并且能有... 详细信息

对于实际的量子信道,它可能包含一系列非幺正的操作,但是过去的研究基本都集中在幺正或近幺正的情况,对于非幺正过程的研究还是很少.本文借用经典人工智能技术中常用的凸优化方法,将量子过程层析构造成一个最小二乘的优化问题,并且能有效地缩小过程矩阵与实际实验结果之间的误差.作者首先选择了海水量子信道来测试该方法的可行性.对比经典的线性变换方法,该方法更准确地体现了海水量子信道的实际操作,并且能很好地保持量子过程的物理性.另外,作者在7个经典的量子门上进行了实验,分别对比了线性变换方法和范数优化的方法.对于线性变换,精度提高了1个量级;对于范数优化,减去了?参数的调优,精确度更高,鲁棒性更好.除此之外,作者还制备了非幺正的量子信道进行检验.对比以往常用的过程层析技术,在非幺正的情况,该方法依然能准确地还原量子过程,准确率达99.5%,进一步证明了其优越性.

关键词： Quantum information Quantum process tomography convex optimization Quantum channel

Quadratic Stabilization of Switched Uncertain Linear Systems: A convex Combination Approach

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IEEE/CAA Journal of Automatica Sinica 2019年第5期6卷 1116-1126页

作者： Yufang Chang Guisheng Zhai Bo Fu Lianglin Xiong the School of Electrical and Electronic Engineering Hubei University of TechnologyWuhan 430068China the Department of Mathematical Sciences Shibaura Institute of TechnologySaitama 337-8570Japan the School of Mathematics and Computer Science Yunnan Minzu UniversityKunming 650500China

We consider quadratic stabilization for a class of switched systems which are composed of a finite set of continuoustime linear subsystems with norm bounded uncertainties. Under the assumption that there is no single quadratically stable subsystem, if a convex combination of subsystems is quadratically stable, then we propose a state-dependent switching law, based on the convex combination of subsystems, such that the entire switched linear system is quadratically stable. When the state information is not available, we extend the discussion to designing an outputdependent switching law by constructing a robust Luenberger observer for each subsystem.

关键词： convex combination limear matrix inequalities (LMIs) norm bounded uncertainties output-dependent switching, quadratic stabilization state-dependent switching switched uncertain linear systems(SULS)

Multiple-constraint cooperative guidance based on two-stage sequential convex programming

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Chinese Journal of Aeronautics 2020年第1期33卷 296-307页

作者： Wei DONG Qiuqiu WEN Qunli XIA Shengjiang YANG School of Aerospace Engineering Beijing Institute of TechnologyBeijing 100081China Beijing Aerospace Technology Institute Beijing 100074China

An improved approach is presented in this paper to implement highly constrained cooperative guidance to attack a stationary target.The problem with time-varying Proportional Navigation(PN)gain is first formulated as a nonlinear optimal control problem,which is difficult to solve due to the existence of nonlinear kinematics and nonconvex constraints.After convexification treatments and discretization,the solution to the original problem can be approximately obtained by solving a sequence of Second-Order Cone Programming(SOCP)problems,which can be readily solved by state-of-the-art Interior-Point Methods(IPMs).To mitigate the sensibility of the algorithm on the user-provided initial profile,a Two-Stage Sequential convex Programming(TSSCP)method is presented in detail.Furthermore,numerical simulations under different mission scenarios are conducted to show the superiority of the proposed method in solving the cooperative guidance problem.The research indicated that the TSSCP method is more tractable and reliable than the traditional methods and has great potential for real-time processing and on-board implementation.

关键词： convex optimization Cooperative guidance Guidance Multiple constraints Second-order cone programming Sequential convex programming

Effects of the convex Topography on Railway Environmental Vibrations

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Computer Modeling in Engineering & Sciences 2019年第1期118卷 177-205页

作者： Huaxi Lu Zhicheng Gao Luyao Xu Bitao Wu Department of Civil Engineering East China Jiaotong UniversityNanchang330013China.

The railway environmental vibration caused by high-speed railways is harmful to the human health,the structural safety of adjacent buildings,and the normal use of precision instruments.At the same time,it occurs frequently.In this case,the railway environmental vibration has drawn much attention with the rapid development of highspeed railways.Studies in Earthquake Engineering show that a convex topography has a great impact on ground vibrations,however,there is no consideration about the convex topographic effect in the study of the railway environmental vibration when the convex topography is near the roadway.In this paper,the influence of a convex topography on the railway environmental vibration was investigated.Two-dimensional(2D)finite element models consist of subgrade-convex topography and subgrade-flat topography are established using the finite element method.The length and the height of the analysis model are taken as 200 m and 41.3 m,respectively.The external soil of the calculation model is simulated via the artificial boundary.By comparison with measured results,the 2D finite element models were verified to be effective.The convex topographic effect is studied by conducting parameter investigations,such as the bottom width,cross-sectional shape,height-width ratio and the foundation soil properties.Results show that the dimension and cross-section shape of the convex topography and the foundation soil properties have significant effect on the convex topographic effect.

关键词： Railway environmental vibration convex topography ground acceleration ground displacement frequency spectra.

A UNIFIED ALGORITHMIC FRAMEWORK OF SYMMETRIC GAUSS-SEIDEL DECOMPOSITION BASED PROXIMAL ADMMS FOR convex COMPOSITE PROGRAMMING

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Journal of Computational Mathematics 2019年第6期37卷 739-757页

作者： Liang Chen Defeng Sun Kim-Chuan Toh Ning Zhang College of Mathematics and Econometrics Hunan UniversityChangsha 410082China Department of Applied Mathematics The Hong Kong Polytechnic UniversityHong KongChina Department of Mathematics and Institute of Operations Research and AnalyticsNational University of Singapore10 Lower Kent Ridge RoadSingapore School of Computer Science and Technology Dongguan University of TechnologyDongguanChina

This paper aims to present a fairly accessible generalization of several symmetric Gauss-Seidel decomposition based multi-block proximal alt ernating direction met hods of multipliers(ADMMs)for convex composite optimization problems.The proposed method unifies and refines many constructive techniques that were separately developed for the computational efficiency of multi-block ADMM-type algor计hms.Specifically,the majorized augmented Lagrangian functions,the indefinite proximal terms,the inexact symmetrie Gauss-Seidel decomposition theorem,the tolerance criteria of approximately solving the subproblems,and the large dual step-lengths,are all incorporated in one algoi?计hmic framework,which we named as sGS-imiPADMM.From the popularity of convergent variants of multi-block ADMMs in recent years,especially for high-dimensional multi-block convex composite conic programming problems,the unification presen ted in this paper,as well as the corresponding convergence results,may have the great potential of facilitating the implemen tation of many multi-block ADMMs in various problem set tings.

关键词： convex optimization Multi-block Alternating direction method of multipliers Symmetric Gauss-Seidel decomposition Majorization

convex decomposition of concave clouds for the ultra-short-term power prediction of distributed photovoltaic system

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High Technology Letters 2016年第3期22卷 305-312页

作者：蔡世波 Tong Jianjun Bao Guanjun Pan Guobing Zhang Libin Xu Fang Key Laboratory of E&M(Zhejiang University of Technology) Ministry of Education & Zhejiang Province

Concave clouds will cause miscalculation by the power prediction model based on cloud features for distributed photovoltaic( PV) plant. The algorithm for decomposing concave cloud into convex images is proposed. Adopting minimum polygonal approximation( MPP) to demonstrate the contour of concave cloud,cloud features are described and the subdivision lines of convex decomposition for the concave clouds are determined by the centroid point scattering model and centroid angle function,which realizes the convex decomposition of concave cloud. The result of MATLAB simulation indicates that the proposed algorithm can accurately detect cloud contour corners and recognize the concave points. The proposed decomposition algorithm has advantages of less time complexity and decomposition part numbers compared to traditional algorithms. So the established model can make the convex decomposition of complex concave clouds completely and quickly,which is available for the existing prediction algorithm for the ultra-short-term power output of distributed PV system based on the cloud features.

关键词： distributed photovoltaic(PV) system cloud features model centroid point scattering model convex decomposition