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A Method for Distributed Transactive Control in Power Systems based on the Projected Consensus Algorithm

IFAC-PapersOnLine 2018年第23期51卷 379-384页

作者： Baron-Prada, Eder Uribe, César A. Mojica-Nava, Eduardo Universidad Nacional de Colombia Colombia ECE Department and Coordinated Science Lab University of Illinois at Urbana-Champaign United States

The shift of power systems toward a smarter grid has brought devices such as distributed generators and smart loads with an increase of the operational challenges for the system operator. These challenges are related to the real-time implementation as well as control and stability issues. We present a distributed transactive control strategy, based on the projected consensus algorithm, to operate the distributed energy resources and smart loads of a power system toward optimal social welfare. We consider two types of agents: Generators, and smart loads. Each agent iteratively optimizes its local utility function based on local information obtained from its neighbors and global information obtained through the network of agents. We show convergence analysis and numerical results for the proposed method. © 2018

关键词： Electric power system control Convergence of numerical methods Distributed parameter control systems Energy resources Iterative methods Real time control Distributed control Distributed Energy Resources Distributed generators Distributed optimization Operational challenges projection algorithms Real time implementations Transactive controls

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A Variable Step-Size Proportionate Affine projection Algorithm for Identification of Sparse Impulse Response

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EURASIP JOURNAL ON ADVANCES IN SIGNAL PROCESSING 2009年第unknown期2009卷 150914-150914页

作者： Liu, Ligang Fukumoto, Masahiro Saiki, Sachio Zhang, Shiyong Kochi Univ Technol Dept Informat Syst Engn Kochi 78285022 Japan Fudan Univ Sch Comp Sci Shanghai 200433 Peoples R China

Proportionate adaptive algorithms have been proposed recently to accelerate convergence for the identification of sparse impulse response. When the excitation signal is colored, especially the speech, the convergence performance of proportionate NLMS algorithms demonstrate slow convergence speed. The proportionate affine projection algorithm (PAPA) is expected to solve this problem by using more information in the input signals. However, its steady-state performance is limited by the constant step-size parameter. In this article we propose a variable step-size PAPA by canceling the a posteriori estimation error. This can result in high convergence speed using a large step size when the identification error is large, and can then considerably decrease the steady-state misalignment using a small step size after the adaptive filter has converged. Simulation results show that the proposed approach can greatly improve the steady-state misalignment without sacrificing the fast convergence of PAPA. Copyright (C) 2009 Ligang Liu et al.

关键词： PAPA NLMS LMS excitation signal Converge Affine PSTPIP1 gene step size nonlinear material projection algorithms IMPULSE RESPONSE Adaptive algorithms steady-state performance adaptive filters In-law

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FEASIBLE DIRECTIONS ALGORITHM FOR OPTIMAL-CONTROL PROBLEMS WITH CONTROL AND TERMINAL INEQUALITY CONSTRAINTS

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IEEE TRANSACTIONS ON AUTOMATIC CONTROL 1977年第5期22卷 741-751页

作者： POLAK, E MAYNE, DQ UNIV CALIF BERKELEY DEPT ELECT ENGN & COMP SCIBERKELEYCA 94720 UNIV LONDON IMPERIAL COLL SCI & TECHNOLDEPT COMP & CONTROLLONDON SW7 2AZENGLAND UNIV CALIF BERKELEY ELECTR RES LABBERKELEYCA 94720

Control constraints, because they are nondifferentiable in the space of control functions, are difficult to cope with in optimization algorithms not of the penalty function type. In feasible directions type algorithms a search direction is obtained by solving a subproblem which has a fixed constraint set S chosen a priori to make this subproblem simple to solve. In this paper control constraints are dealt with by using them to define, at the current control u , a constraint set S(u) for the search direction subproblem. This enables control constraints to be easily handled.

关键词： Optimal control projection algorithms Automatic control Councils Contracts Laboratories Military computing Strain control Linear approximation Costs

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Convergence rates in forward-backward splitting

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SIAM JOURNAL ON OPTIMIZATION 1997年第2期7卷 421-444页

作者： Chen, GHG Rockafellar, RT UNIV WASHINGTON DEPT MATHSEATTLEWA 98195

Forward-backward splitting methods provide a range of approaches to solving large-scale optimization problems and variational inequalities in which structures conducive to decomposition can be utilized. Apart from special cases where the forward step is absent and a version of the proximal point algorithm comes out, efforts at evaluating the convergence potential of such methods have so far relied on Lipschitz properties and strong monotonicity, or inverse strong monotonicity, of the mapping involved in the forward step, the perspective mainly being that of projection algorithms. Here, convergence is analyzed by a technique that allows properties of the mapping in the backward step to be brought in as well. For the first time in such a general setting, global and local contraction rates are derived;moreover, they are derived in a form which makes it possible to determine the optimal step size relative to certain constants associated with the given problem. Insights are thereby gained into the effects of shifting strong monotonicity between the forward and backward mappings when a splitting is selected.

关键词： forward-backward splitting numerical optimization variational inequalities projection algorithms matrix splitting operator splitting convex programming

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SURVEY: SIXTY YEARS OF DOUGLAS-RACHFORD

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JOURNAL OF THE AUSTRALIAN MATHEMATICAL SOCIETY 2021年第3期110卷 333-370页

作者： LINDSTROM, S. C. O. T. T. B. SIMS, B. R. A. I. L. E. Y. Univ Newcastle Callaghan NSW Australia

The Douglas-Rachford method is a splitting method frequently employed for finding zeros of sums of maximally monotone operators. When the operators in question are normal cone operators, the iterated process may be used to solve feasibility problems of the following form: Find x is an element of boolean AND(N)(k=1) S-k. The success of the method in the context of closed, convex, nonempty sets S-1, ..., S-N is well known and understood from a theoretical standpoint. However, its performance in the nonconvex context is less well understood, yet it is surprisingly impressive. This was particularly compelling to Jonathan M. Borwein who, intrigued by Elser, Rankenburg and Thibault's success in applying the method to solving sudoku puzzles, began an investigation of his own. We survey the current body of literature on the subject, and we summarize its history. We especially commemorate Professor Borwein's celebrated contributions to the area.

关键词： Douglas-Rachford feasibility projection algorithms iterative methods discrete dynamical systems

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Robust Diffusion Affine projection Algorithm With Variable Step-Size Over Distributed Networks

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IEEE ACCESS 2019年 7卷 150484-150491页

作者： Song, Pucha Zhao, Haiquan Zeng, Xiangping Southwest Jiaotong Univ Sch Elect Engn Key Lab Magnet Suspens Technol & Maglev Vehicle Minist Educ Chengdu 610031 Sichuan Peoples R China

The estimation performance of the standard diffusion affine projection algorithm may be degraded when the distributed network nodes are disturbed by impulsive noise. To overcome the limitation, a diffusion affine projection M-estimate (DAPM) algorithm is proposed for distributed estimation in the adaptive diffusion networks. This algorithm uses a robust cost function based on M-estimate function to eliminate the adverse effects of impulsive noise on distributed diffusion network nodes. In order to further enhance the performance of the DAPM algorithm, namely fast convergence rate and low steady-state error, a variable step-size diffusion affine projection M-estimate (VSS-DAPM) algorithm is presented. In addition, the convergence range of the step-size is deduced to ensure the convergence of the proposed algorithms. Computer simulations show that the proposed DAPM and VSS-DAPM algorithms have good convergence performance for distributed estimation in the adaptive diffusion networks. More importantly, the proposed VSS-DAPM algorithm improves convergence rate and the network mean square deviation (MSD) as compared to the DAPM algorithm in the distributed estimation.

关键词： Estimation Convergence Adaptive systems Cost function projection algorithms Standards Steady-state Affine projection algorithm impulsive noise M-estimate variable step-size distributed estimation

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Iterative Greedy LMI for Sparse Control

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IEEE CONTROL SYSTEMS LETTERS 2022年 6卷 986-991页

作者： Nagahara, Masaaki Ogura, Masaki Yamamoto, Yutaka Univ Kitakyushu Inst Environm Sci & Technol Fukuoka 8080139 Japan Osaka Univ Grad Sch Informat Sci & Technol Suita Osaka 5650871 Japan Kyoto Univ Grad Sch Informat Kyoto 6068501 Japan

In this letter, we propose a novel method to find matrices that satisfy sparsity and LMI (linear matrix inequality) constraints at the same time. This problem appears in sparse control design such as sparse representation of the state feedback gain, sparse graph representation with fastest mixing, and sparse FIR (finite impulse response) filter design, to name a few. We propose an efficient algorithm for the solution based on Dykstra's projection algorithm. We then prove a convergence theorem of the proposed algorithm, and show some control examples to illustrate merits and demerits of the proposed method.

关键词： Optimization Sparse matrices projection algorithms Linear matrix inequalities Finite impulse response filters Eigenvalues and eigenfunctions Power system dynamics Greedy algorithms linear matrix inequalities sparse control network theory

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An Area-Based projection Algorithm for SAR Radiometric Terrain Correction and Geocoding

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING 2022年 60卷

作者： Shiroma, Gustavo H. X. Lavalle, Marco Buckley, Sean M. CALTECH Jet Prop Lab Pasadena CA 91109 USA

This article describes a projection algorithm between radar and map coordinates based on the representation of radar samples as area elements (AEs) rather than point elements. Each AE on the map grid (geographic grid) is associated with a number of radar grid samples that intersect completely or partially the AE. The association enables the geocoding (i.e., the map projection of radar imagery) with adaptive multilooking, accurately accounting for all radar samples contributing to the geocoded elements according to topography and radar geometry. By using averaging rather than interpolation, the proposed projection does not suffer from interpolation overfitting. The area-based geocoding also enables the generation of the geocoded polarimetric covariance matrix (GCOV) and geocoded synthetic aperture radar (SAR) interferograms with adaptive multilooking. Analogously, the slant-range projection of geocoded data is improved by projecting geographic grid pixels onto the radar grid according to their corresponding location based on the radar geometry without leaving gaps. This approach is used to reduce the computation time of previously published radiometric terrain correction (RTC) algorithms, performing 3.6-6.5 times faster over multilooked data and up to 26.3 times faster over single-look data. We demonstrate the strengths of the proposed area projection (AP) algorithm for RTC and geocoding using Uninhabited Aerial Vehicle SAR (UAVSAR), Sentinel-1B, and ALOS-2/PALSAR-2 data, and evaluate the results in the context of the upcoming NASA-ISRO SAR (NISAR) mission.

关键词： Radar Spaceborne radar Synthetic aperture radar projection algorithms Radar polarimetry Interpolation Radiometry C-band covariance matrix geocoded polarimetric covariance matrix (GCOV) interferometric synthetic aperture radar (SAR) (InSAR) L-band NASA-ISRO SAR (NISAR) polarimetric SAR (PolSAR) radiometric terrain correction (RTC) SAR SAR interferometry

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A Hardware Implementation of an Orthorectification Process

A Hardware Implementation of an Orthorectification Process

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IEEE National Aerospace and Electronics Conference (NAECON)

作者： Shaffer, Daniel A. Kordik, Andrew M. Walker, David M. Balster, Eric J. Turri, William F. Univ Dayton Res Inst 300 Coll Pk Dayton OH 45469 USA Univ Dayton Dept Elect & Comp Engn Kettering Lab Dayton OH 45469 USA

ISBN: (纸本)9781467375658

This paper presents a hardware implementation of an image orthorectification process using the back-projection algorithm. Image orthorectification is integral to effective analysis and exploitation of aerial imagery and is often one of the largest processing bottlenecks. As imaging sensors grow in pixel count and associated target footprint, the image orthorectification process requires an associated increase in compute capability. In order to support size, weight, and power ( SWaP) constrained processing environments, such as on-board systems for unmanned aerial vehicles ( UAVs), efficient and scalable solutions must be developed. Moreover, in surveillance applications minimizing latency is paramount. This paper presents an integer-based high performance FPGA implementation of a back-projection algorithm for orthorectification. A 2.4x speedup is achieved over software processing with an associated 15x reduction in total power draw.

关键词： Image registration projection algorithms field programmable gate arrays hardware

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A novel algorithm for computing rank reduced matrix approximations 3

A novel algorithm for computing rank reduced matrix approxim...

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3rd IEEE Workshop on Signal Processing Advances in Wireless Communications (SPAWC 01)

作者： Manton, JH Hua, YB Univ Melbourne Dept Elect & Elect Engn Parkville Vic 3010 Australia

ISBN: (纸本)0780367200

The problem of approximating a matrix by one of lower rank occurs in a number of signal processing problems, including reduced rank Wiener filtering and reduced rank maximum likelihood estimation. This paper derives a novel algorithm for computing the optimal rank reduced approximation of a given matrix under an arbitrary weighted norm. Simulations demonstrate the advantages of the algorithm over the traditional alternating projections algorithm.

关键词： Algorithm design and analysis Approximation algorithms Computational efficiency Computational modeling Cost function Geometry Maximum likelihood estimation projection algorithms Signal processing algorithms Wiener filter

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