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Identification of Structured LTI MIMO State-Space Models

Identification of Structured LTI MIMO State-Space Models

引用

IEEE Annual Conference on Decision and Control

作者： Chengpu Yu Michel Verhaegen Shahar Kovalsky Ronen Basri Delft Center for Systems and Control Delft University Delft 2628CD Netherlands Weizmann Institute of Science Department of Computer Science and Applied Mathematics

ISBN: (纸本)9781479978878

The identification of structured state-space model has been intensively studied for a long time but still has not been adequately addressed. The main challenge is that the involved estimation problem is a non-convex (or bilinear) optimization problem. This paper is devoted to developing an identification method which aims to find the global optimal solution under mild computational burden. Key to the developed identification algorithm is to transform a bilinear estimation to a rank constrained optimization problem and further a difference of convex programming (DCP) problem. The initial condition for the DCP problem is obtained by solving its convex part of the optimization problem which happens to be a nuclear norm regularized optimization problem. Since the nuclear norm regularized optimization is the closest convex form of the low-rank constrained estimation problem, the obtained initial condition is always of high quality which provides the DCP problem a good starting point. The DCP problem is then solved by the sequential convex programming method. Finally, numerical examples are included to show the effectiveness of the developed identification algorithm.

关键词： Identification methods Non-convex convex programming LTI INITIAL CONDITIONS Authentication bilinearity

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Cognitive Radio Enabled Transmission for State Estimation in Industrial Cyber-physical Systems

Cognitive Radio Enabled Transmission for State Estimation in...

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IEEE Global Communications Conference

作者： Ling Lyu Cailian Chen Yao Li Feilong Lin Lingya Liu Xinping Guan Department of Automation Shanghai Jiao Tong University

ISBN: (纸本)9781479959532

State estimation, which computes the best possible approximation for the system state based on the perceived information transmitted from sensors to the estimators, is vital for control system performance in industrial cyber-physical systems (ICPSs) with the integrated techniques of control, communication and computing. Thus the performance of state estimation relies on the communication reliability. In order to improve the reliability, redundant channels/slots are reserved for the data transmission in industrial wireless techniques, such as WirelessHART. However, the redundancy scheme burdens the increasingly over-crowded ISM spectrum band due to the envisioned emerging ubiquitous industrial wireless monitoring in the architecture of ICPS in the near future. The cognitive radio (CR) technology can intelligently explore the available spectrum opportunities on licensed channels, and it motivates this paper to consider the redundant transmission through the opportunistically available licensed channels to guarantee the transmission reliability for state estimation. Unfortunately, spectrum sensing takes extra energy consumption, thus it is necessary to take into account the energy efficiency for the battery-powered IWSN. Then a CR enabled energy-efficiency maximization problem is formulated by regarding the convergence of state estimation as a constraint of the resource allocation problem. In order to solve the non-convex and mixed integer programming, the Dinkelbach and Lagrangian relaxation techniques are adopted to transform the problem into a convex programming and furthermore reduce the computational complexity. Numerical results demonstrate that the CR technology can significantly release the spectrum for the redundancy design from the ISM band while guarantee the reliability for the effective state estimation.

关键词： State estimation Cognitive radio communication reliability ISM band power transmission reliability Energy efficiency convex programming data transmission Spectra Wireless monitoring energy consumption Industrial Resource utilization chromium Non-convex

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Cooperative Energy Trading in CoMP Systems Powered by Smart Grids

Cooperative Energy Trading in CoMP Systems Powered by Smart ...

引用

IEEE Global Communications Conference

作者： Jie Xu Rui Zhang ECE Department National University of Singapore

ISBN: (纸本)9781479935130

This paper studies the energy management in the coordinated multi-point (CoMP) systems powered by smart grids, where each base station (BS) with local renewable energy generation is allowed to implement the two-way energy trading with the grid. Due to the unevenly generated renewable energy over distributed BSs and the difference in the prices for buying/selling energy from/to the gird, it is in general beneficial for the cooperative BSs to jointly manage their energy trading with the grid and energy consumption in CoMP based communication for reducing the total energy cost. We consider the downlink transmission in one CoMP cluster by jointly optimizing the BSs' purchased/sold energy units from/to the grid and their cooperative transmit beamforming, so as to minimize the total energy cost subject to the given quality of service (QoS) constraints for the users. By applying techniques from convex optimization and uplink-downlink duality, we propose an efficient algorithm to solve this problem optimally. Through simulations, we show the performance gain achieved by our proposed joint energy trading and communication cooperation scheme in terms of cost reduction, as compared to a baseline scheme with the separate designs of communication cooperation and energy trading.

关键词： convex programming cooperative communication energy management systems smart power grids CoMP systems base station convex optimization cooperative energy trading cooperative transmit beamforming coordinated multipoint systems downlink transmission joint energy trading and communication cooperation scheme local renewable energy generation quality of service constraints smart grids two-way energy trading uplink-downlink duality Array signal processing Downlink Interference Quality of service Renewable energy sources Signal to noise ratio Vectors

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OPTIMIZING PORTFOLIO TAIL MEASURES: ASYMPTOTICS AND EFFICIENT SIMULATION OPTIMIZATION 08

OPTIMIZING PORTFOLIO TAIL MEASURES: ASYMPTOTICS AND EFFICIEN...

引用

Winter Simulation Conference (WSC 2008)

作者： Sandeep Juneja Tata Institute of Fundamental Research Mumbai India

ISBN: (纸本)9781424427086

We consider a portfolio allocation problem where the objective function is a tail event such as probability of large portfolio losses. The dependence between assets is captured through multi-factor linear model. We address this optimization problem using two broad approaches. We show that a suitably scaled asymptotic of the probability of large losses can be developed that is a simple convex function of the allocated resources. Thus, asymptotically, portfolio allocation problem is approximated by a convex programming problem whose solution is easily computed and provides significant managerial insight. We then solve the original problem using sample average simulation optimization. Since rare events are involved, naive simulation may perform poorly. To remedy this, we introduce change-of-variable based importance sampling technique and develop a single change of measure that asymptotically optimally estimates tail probabilities across the entire space of feasible allocations.

关键词： asymptotic BRIEFCASE simulating convex function original problem convex programming Objective function

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A Distributed Algorithm with Event-Triggered Communication for Resource Allocation Problem

A Distributed Algorithm with Event-Triggered Communication f...

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American Control Conference

作者： Xiasheng Shi Ronghao Zheng Tao Yang Zhiyun Lin Gangfeng Yan College of Electrical Engineering Zhejiang University Hangzhou China University of North Texas Denton USA School of Automation Hangzhou Dianzi University Hangzhou China Colleg

ISBN: (纸本)9781538679012;9781538679265

This paper focuses on the distributed resource allocation problem in continuous-time multi-agent systems over undirected networks, in which each agent has a local convex cost function only known by itself and all agents are required to converge to the global optimizer of the sum of the local cost functions under constraints. A gradient-based distributed algorithm is proposed for solving the problem. Furthermore, the step-size of gradient is a constant. A sufficient condition is given which guarantees that the proposed algorithm can achieve the global optimization. Moreover, in order to avoid continuous communication, an event-triggered communication control strategy is designed. Finally, an example of the economic dispatch problem in smart grid is presented to validate and illustrate the feasibility of the proposed algorithm.

关键词： continuous time systems convex programming distributed algorithms gradient methods multi-agent systems power engineering computing power generation dispatch resource allocation smart power grids

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Optimal Time Allocation for Dynamic-TDMA-based Wireless Powered Communication Networks

Optimal Time Allocation for Dynamic-TDMA-based Wireless Powe...

引用

IEEE Global Communications Conference

作者： Xin Kang Chin Keong Ho Sumei Sun Institute for Infocomm Research

ISBN: (纸本)9781479935130

In this paper, we consider a wireless communication network with a hybrid access point (HAP) and a set of wireless users with energy harvesting capabilities. The HAP is assumed to have two antennas: one for transferring wireless energy in the downlink and one for receiving wireless information in the uplink. Without fixed energy sources, users first have to harvest energy from the wireless signals broadcast by the HAP, and then using the harvested energy to transmit their individual information to the HAP through dynamic-time-division-multiple-access (D-TDMA). We investigate the optimal time allocation to maximize the throughput of the proposed system subject to a total time constant. The formulated throughput maximization problem is proved to be a convex optimization problem. By using convex optimization techniques, the optimal time allocation strategy is obtained in closed-form expression. We show that the optimal time allocation can be obtained with linear complexity. It is then shown by simulations that the total throughput of the network increases with the number of users. It is also shown by simulations that the users with low SNR should be scheduled to transmit first.

关键词： antenna arrays convex programming energy harvesting inductive power transmission radio networks time division multiple access HAP SNR antenna closed-form expression convex optimization problem dynamic-TDMA-based wireless powered communication network energy source hybrid access point optimal time allocation strategy time-division-multiple-access wireless energy transfer wireless information receiver wireless signal broadcasting convex functions Energy harvesting Resource management Throughput Uplink Wireless communication Wireless sensor networks

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Global Optimization for Estimating a BRDF with Multiple Specular Lobes

Global Optimization for Estimating a BRDF with Multiple Spec...

引用

IEEE Conference on Computer Vision and Pattern Recognition

作者： Chanki Yu Yongduek Seo Sang Wook Lee Dept. of Media Technology Sogang University

ISBN: (纸本)9781424469840;9781424469857

This paper presents a global minimization framework for estimating analytical BRDF model parameters using the techniques of convex programming and branch and bound. Traditional local minimization suffers from local minima and requires a large number of initial conditions and supervision for successful results especially when a model is highly complex and nonlinear. We consider the Cook-Torrance model, a parametric model with the Gaussian-like Beckmann distributions for specular reflectances. Instead of optimizing the multiple parameters simultaneously, we search over all possible surface roughness values based on a branch-and-bound algorithm, and reduce the estimation problem to convex minimization with known fixed surface roughness. Our algorithm guarantees globally optimal solutions. Experiments have been carried out for isotropic surfaces to validate the method using the extensive high-precision measurements from the MERL BRDF database.

关键词： Global optimization convex programming branches model parameters Lobe Regulated industries INITIAL CONDITIONS Surface roughness

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Design of Perfect-Reconstruction Hybrid Filter Banks: A Second-Order Cone programming Approach

Design of Perfect-Reconstruction Hybrid Filter Banks: A Seco...

引用

2010 IEEE International Conference on Intelligent Computing and Intelligent Systems(2010 IEEE 智能计算与智能系统国际会议 ICIS 2010)

作者： ZhenHao Cai HongYi Yu Institute of Zhengzhou Information Science and Technology Zhengzhou 450002 P.R.China

ISBN: (纸本)9781424465828

In this paper, we present a new convex programming design methodology for hybrid filter banks (HFB) by solving a linear equation system derived from the perfect reconstruction (PR) conditions. The relationship between the PR conditions and each different solution situations are discussed regarding the consistent and inconsistent equation case, the general solution and the lower bound to the error of reconstruction are given. A second order cone programming (SOCP) based algorithms for designing PR HFB is proposed to get the exact solution with the constrained of stopband energy minimum which can also be used to calculate the minimizing norm solution of the equation. Finally, we consider some design examples and evaluate their performance.

关键词： convex programming hybrid filter banks second order cone programming

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Robust estimation of structured covariance matrix for heavy-tailed distributions

Robust estimation of structured covariance matrix for heavy-...

引用

IEEE International Conference on Acoustics, Speech and Signal Processing

作者： Y. Sun P. Babu D. P. Palomar Dept. of Electron. & Comput. Eng. Hong Kong Univ. of Sci. & Technol. Hong Kong China

ISBN: (纸本)9781467369985

In this paper, we consider the robust covariance estimation problem in the non-Gaussian set-up. In particular, Tyler's M-estimator is adopted for samples drawn from a heavy-tailed elliptical distribution. For some applications, the covariance matrix naturally possesses certain structure. Therefore, incorporating the prior structure information in the estimation procedure is beneficial to improving estimation accuracy. The problem is formulated as a constrained minimization of the Tyler's cost function, where the structure is characterized by the constraint set. A numerical algorithm based on majorization-minimization is derived for general structures that can be characterized as a convex set, where a sequence of convex programming is solved. For the set of matrices that can be decomposed as the sum of rank one positive semidefinite matrices, which has a wide range of applications, the algorithm is modified with much lower complexity. Simulation results demonstrate that the proposed structure-constrained Tyler's estimator achieves smaller estimation error than the unconstrained case.

关键词： Robust estimation Tyler's scatter estimator majorization-minimization structure constraint estimation theory variance covariance matrix Covariance matrix assessment procedure convex programming matrices

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Price sensitivity based demand function for power flow in congested transmission lines

Price sensitivity based demand function for power flow in co...

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Michael Faraday IET International Summit 2020 (MFIIS 2020)

作者： P. Saha S. Banerjee B. Paul C. Kumar Chanda Narula Institute of Technology Agarpara Kolkata India Gargi Memorial Institute of Technology Baruipur Kolkata India Indian Institute of Engineering Science and Technology Shibpur Howrah India

In an open power market having elastic loads the remote generators needed to compete with local generators to provide power at a competitive price. The price for transmission of power depends upon the LMP (Locational Marginal Price) of each generator located within the network. Price sensitivity represented by LMP is of utmost importance to maintain the proper functionality of the power market. convex quadratic function for the amount of power transmitted is used by transition owners. These obtained revenues marks up the price that both the power produces and power users needed to pay for using the power network. In this paper a five bus system is considered, the LMPs at each busses are calculated correspondingly demand functions for each of the transmission has been obtained which computes the revenue obtained at maximum point for maintain the optimal transmission capacity in the system.

关键词： power transmission economics pricing power markets load flow convex programming quadratic programming power generation economics power transmission lines

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