Finite-time stability and stabilization problem is first investigated for continuous-time polynomial fuzzy systems. The concept of finite-time stability and stabilization is given for polynomial fuzzy systems based on...
详细信息
The increasing penetration of renewable energy sources in the electricity grid brings new operational challenges. This brings up the need for effective means to provide demand response in spite of its distributed natu...
详细信息
The increasing penetration of renewable energy sources in the electricity grid brings new operational challenges. This brings up the need for effective means to provide demand response in spite of its distributed nature throughout the grid. Aggregators can be created to manage a set of such demand response resources, but deciding how to allocate an aggregator's resources is an important problem. One of the aspects that needs more attention is the impact of the transmission system on these decisions. In this paper, we propose a short-term optimization model for allocating demand response(DR) resources as well as generation resources to supply external demand that is offered after the scheduling decision is made. The DR resources will only be available for use after the scheduling decision is made. Finally, our work also considers the impact of congestion in the transmission system when allocating DR. We propose the use of a semidefinite relaxation to provide a good initial point to solve our model with the aim of guaranteeing that we will find an optimal solution. Results from numerical tests with the IEEE 96-RTS and the ACTIVSG500 test grids are reported. We found that DR resources mitigates congestion management, allowing the generators to supply more of the external demand that is offered. Besides that, we observe that using our proposed solution methodology, we were able to obtain optimal solution for both cases studies, which is not the case when solving the original formulation for the ACTIVSG500 grid.
When almost all underlying assets suddenly lose a certain part of their nominal value in a market crash, the diversification effect of portfolios in a normal market condition no longer works. We integrate the crash ri...
详细信息
When almost all underlying assets suddenly lose a certain part of their nominal value in a market crash, the diversification effect of portfolios in a normal market condition no longer works. We integrate the crash risk into portfolio management and investigate performance measures, hedging and optimization of portfolio selection involving derivatives. A suitable convex conic programming framework based on parametric approximation method is proposed to make the problem a tractable one. Simulation analysis and empirical study are performed to test the proposed approach. (C) 2020 Elsevier B.V. All rights reserved.
This paper proposes downside risk measure models in portfolio selection that captures uncertainties both in distribution and in parameters. The worst-case distribution with given information on the mean value and the ...
详细信息
This paper proposes downside risk measure models in portfolio selection that captures uncertainties both in distribution and in parameters. The worst-case distribution with given information on the mean value and the covariance matrix is used, together with ellipsoidal and polytopic uncertainty sets, to build-up this type of downside risk model. As an application of the models, the tracking error portfolio selection problem is considered. By lifting the vector variables to positive semidefinite matrix variables, we obtain semidefinite programming formulations of the robust tracking portfolio models. Numerical results are presented in tracking SSE50 of the Shanghai Stock Exchange. Compared with the tracking error variance portfolio model and the equally weighted strategy, the proposed models are more stable, have better accumulated wealth and have much better Sharpe ratio in the investment period for the majority of observed instances. (C) 2013 Elsevier B.V. All rights reserved.
The design of multivariable PID controllers which guarantee the stability of closed loop systems, have a fixed attenuation degree, and robust performance specifications is described. The design of such a multivariable...
详细信息
The design of multivariable PID controllers which guarantee the stability of closed loop systems, have a fixed attenuation degree, and robust performance specifications is described. The design of such a multivariable PID controller is transformed to a static output feedback (SOF) problem. The problem of system control is converted into a semi-definite programming problem with LMI constraints, and then by using linear matrix inequalities (LMI) and bilinear matrix inequalities (BMI), the required algorithm is derived and the parameters of the PID controllers can be obtained by further transforms. The validity and robustness of the algorithm is demonstrated by simulation of a numerical example in chemical industry process control.
Recently, convex "moment" relaxations developed from the Lasserre hierarchy for polynomial optimization problems have been shown capable of globally solving many optimal power flow (OPF) problems. The moment...
详细信息
Recently, convex "moment" relaxations developed from the Lasserre hierarchy for polynomial optimization problems have been shown capable of globally solving many optimal power flow (OPF) problems. The moment relaxations, which take the form of semidefinite programs (SDP), generalize a previous SDP relaxation of the OPF problem. This paper presents an approach for improving the computational performance of the moment relaxations for many problems. This approach enforces second-order cone programming (SOCP) constraints that establish necessary (but not sufficient) conditions for satisfaction of the SDP constraints arising from the higher-order moment relaxations. The resulting "mixed SDP/SOCP" formulation implements the first-order relaxation using SDP constraints and the higher-order relaxations using SOCP constraints. Numerical results demonstrate that this mixed SDP/SOCP relaxation is capable of solving many problems for which the first-order moment relaxation fails to yield a global solution. For several examples, the mixed SDP/SOCP relaxation improves computational speed by factors from 1.13 to 18.7.
The track-to-track association problem is to determine the pairing of sensor-level tracks that correspond to the same true target from which the sensor-level tracks originated. This problem is crucial for multisensor ...
详细信息
ISBN:
(纸本)9780982443804
The track-to-track association problem is to determine the pairing of sensor-level tracks that correspond to the same true target from which the sensor-level tracks originated. This problem is crucial for multisensor data fusion and is complicated by the presence of individual sensor biases, random errors, false tracks, and missed tracks. A popular approach to performing track-to-track association between two sensor systems is to jointly optimize the a posteriori relative bias estimate between the sensors and the likelihood of track-to-track association. Algorithms that solve this problem typically generate the K best bias-association hypotheses and corresponding bias-association likelihoods. In this paper, we extend the above approach in two ways. First, we derive a closed-form expression for computing "pure" track-to-track association likelihoods, as opposed to bias-association likelihoods which are weighted by a unique relative bias estimate. Second, we present an alternative formulation of the track-to-track association problem in which we optimize solely with respect to association likelihoods. These results facilitate what is commonly known as system-level track ambiguity management.
Considering a dense small-cell network with simultaneous wireless information and power transfer (SWIPT), this work jointly designs transmit beamformers at the base stations (BSs) and receive power splitting ratios at...
详细信息
ISBN:
(纸本)9781479975921
Considering a dense small-cell network with simultaneous wireless information and power transfer (SWIPT), this work jointly designs transmit beamformers at the base stations (BSs) and receive power splitting ratios at the users (UEs). Our objectives is to maximize the minimum UE signal-to-interference-plus-noise-ratio (SINR) under BS transmit power and UE minimum harvested energy constraints. This problem is highly nonconvex, for which semidefinite programming (SDP) relaxation may even fail to locate a feasible solution. We propose an efficient spectral optimization method by expressing the rank-one constraints as a single reverse convex nonsmooth constraint and incorporating it in the optimization objective. The proposed algorithm practically achieves the theoretical bound given by SDP relaxation with almost similar complexity.
In this paper, we propose a novel transceiver architecture at relay for multiple input, multiple output two-way relay channel (TWRC). This transceiver architecture consists of the analog beamforming in RF domain and t...
详细信息
ISBN:
(纸本)9781467376884
In this paper, we propose a novel transceiver architecture at relay for multiple input, multiple output two-way relay channel (TWRC). This transceiver architecture consists of the analog beamforming in RF domain and the MMSE based digital processing at baseband, which is simplified as RF-MDP-MIMO architecture. Under the RF-MDP-MIMO architecture, the objective of this paper is to find the optimal relay transmit and receive beamformings that can achieve the boundary of the optimal capacity region with limited relay power. Specifically, by formulating the original optimization problem into two semidefinite programing (SDP) problems with rank-one constraints which can be effectively solved by the penalty function method, we can optimize relay transmit and receive beamformings alternatively. Then, the maximum achievable sum rate of TWRC can be obtained with the bisection method. Further, the achievable capacity region is realized. Numerical experiments are conducted to show that our proposed RF-MDP-MIMO architecture outperforms the RF-MIMO architecture in terms of the optimal achievable capacity region.
We study general geometric techniques for bounding the spectral gap of a reversible Markov chain. We show that the best bound obtainable using these techniques can be computed in polynomial time via semidefinite progr...
详细信息
暂无评论