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A Smart Microcontroller-Based Iridium Satellite-Communication Architecture for a Remote Renewable Energy Source

IEEE TRANSACTIONS ON POWER DELIVERY 2009年第4期24卷 1869-1875页

作者： Deep, Ujjwal Dahal Petersen, Brent R. Meng, Julian Bhutan Power Corp Thimphu Bhutan Univ New Brunswick Fredericton NB E3B 5A3 Canada

With an increased focus on the utilization of green technologies and greater demands on the electric power grid, renewable energy is an important form of current and future power generation. With remote generation deployments, such as those based on wind energy, a cost-effective communication system with global coverage using satellite technology would be advantageous. The monitoring of remote generators for performance and maintenance issues is certainly necessary for any distributed-generation system. To offer a cost-effective satellite solution, a cost-optimization algorithm for minimizing data transmission while maximizing relevant telemetry data is required. This paper proposes a low-cost smart communications architecture using an Iridium Satellite System 9601 short-burst data transceiver and simple microcontroller technology. The microcontroller allows for simple optimization routines to be performed on the locally stored data. This proposed system was implemented and tested and recommendations are drawn on the usability of the developed communication system for monitoring a remote generation site.

关键词： Iridium microcontroller nonlinear programming renewable energy satellite communications smart systems

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SPECTRAL PROJECTED GRADIENT METHOD WITH INEXACT RESTORATION FOR MINIMIZATION WITH NONCONVEX CONSTRAINTS

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 2009年第3期31卷 1628-1652页

作者： Gomes-Ruggiero, M. A. Martinez, J. M. Santos, S. A. Univ Estadual Campinas Dept Appl Math BR-13083970 Campinas SP Brazil

This work takes advantage of the spectral projected gradient direction within the inexact restoration framework to address nonlinear optimization problems with nonconvex constraints. The proposed strategy includes a convenient handling of the constraints, together with nonmonotonic features to speed up convergence. The numerical performance is assessed by experiments with hard-spheres problems, pointing out that the inexact restoration framework provides an adequate environment for the extension of the spectral projected gradient method for general nonlinearly constrained optimization.

关键词： spectral projected gradients inexact restoration nonlinear programming hard-spheres problems

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Robust Air-Traffic Control Using Ground-Delays and Rerouting of Flights

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2009年第12期6卷 649-674页

作者： Dutta, Parikshit Bhattacharya, Raktim Chakravorty, Suman Texas A&M Univ Dept Aerosp Engn College Stn TX 77843 USA

In this paper we demonstrate that finite horizon optimization of ground-delays and rerouting can provide robustness to the performance of the United States National Airspace System, in the event a center goes down. Our analysis is based on a linear system approximation of the National Airspace System. We use the linear model to analyze the degrading effect of a loss of center on the performance of the air-traffic control. We employ ground-delays and rerouting of flights as mitigation tools and propose optimal sequences of these control actions to restore the performance of the National Airspace System. The optimal sequence is determined by solving a finite horizon optimal control problem. Historical data in the available literature are used to derive the linear approximation of the National Airspace System. From our analysis we observe that both ground-delays and rerouting are able to successfully restore the performance of the National Airspace System. We did not observe significant difference in performance between these two methods. However, the computational complexity associated with rerouting is significantly more than that for ground delays. The simulation plots demonstrate that finite horizon optimization for determining optimal ground-delay or rerouting strategies can mitigate the effects of a center going down in the National Airspace System.

关键词： National Airspace System Optimal Control nonlinear programming Linear Time Invariant System Quadratic programming Aircraft on Ground Airspace Probability Density Functions Air Traffic Flow Management Aircraft to Aircraft

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Allocation of Radar Tracking Resources by Direct Optimization

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JOURNAL OF AEROSPACE COMPUTING INFORMATION AND COMMUNICATION 2009年第9期6卷 523-539页

作者： Ben-Asher, Joseph Z. Cohen, Dror Technion Israel Inst Technol Dept Aerosp Engn IL-32000 Haifa Israel Wales Ltd IL-52522 Ramat Gan Israel

The problem of optimal allocation of radar resources is addressed. Open-loop optimal strategies are obtained by direct optimization. The satisfaction of the Maximum Principle is verified by a noniterative process. The structure of the solutions is investigated by extensive numerical solutions and the main features of the optimal strategies are characterized.

关键词： Radar Tracking Closed Loop nonlinear programming Kalman Filter Boundary Value Problems Lagrange Multipliers Iterative Algorithm Optimal Control

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New global optimization methods for ship design problems

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OPTIMIZATION AND ENGINEERING 2009年第4期10卷 533-555页

作者： Campana, Emilio Fortunato Liuzzi, Giampaolo Lucidi, Stefano Peri, Daniele Piccialli, Veronica Pinto, Antonio INSEAN I-00128 Rome Italy Univ Roma La Sapienza Dipartimento Informat & Sistemist A Ruberti I-00185 Rome Italy CNR Ist Anal Sistemi & Informat A Ruberti I-00185 Rome Italy Univ Roma Tor Vergata Dipartimento Ingn Impresa I-00133 Rome Italy

The aim of this paper is to solve optimal design problems for industrial applications when the objective function value requires the evaluation of expensive simulation codes and its first derivatives are not available. In order to achieve this goal we propose two new algorithms that draw inspiration from two existing approaches: a filled function based algorithm and a Particle Swarm Optimization method. In order to test the efficiency of the two proposed algorithms, we perform a numerical comparison both with the methods we drew inspiration from, and with some standard Global Optimization algorithms that are currently adopted in industrial design optimization. Finally, a realistic ship design problem, namely the reduction of the amplitude of the heave motion of a ship advancing in head seas (a problem connected to both safety and comfort), is solved using the new codes and other global and local derivative-free optimization methods. All the numerical results show the effectiveness of the two new algorithms.

关键词： nonlinear programming Global optimization Simulation based design

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An extended mathematical programming framework

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COMPUTERS & CHEMICAL ENGINEERING 2009年第12期33卷 1973-1982页

作者： Ferris, Michael C. Dirkse, Steven P. Jagla, Jan-H. Meeraus, Alexander Univ Wisconsin Dept Comp Sci Madison WI 53706 USA GAMS Corp Washington DC 20007 USA GAMS Software GmbH D-50933 Cologne Germany

Extended mathematical programs are collections of functions and variables joined together using specific optimization and complementarity primitives. This paper outlines a mechanism to describe such an extended mathematical program by means of annotating the existing relationships within a model to facilitate higher level structure identification. The structures, which often involve constraints on the solution sets of other models or complementarity relationships. can be exploited by modern large scale mathematical programming algorithms for efficient solution. A specific implementation of this framework is outlined that communicates structure from the GAMS modeling system to appropriate solvers in a computationally beneficial manner. Example applications are taken from chemical engineering. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Modeling Complementarity nonlinear programming Variational inequalities

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Ordinal optimisation approach for locating and sizing of distributed generation

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IET GENERATION TRANSMISSION & DISTRIBUTION 2009年第8期3卷 713-723页

作者： Jabr, R. A. Pal, B. C. Notre Dame Univ Elect Comp & Commun Engn Dept Zouk Mikhael Zouk Mosbeh Lebanon Univ London Imperial Coll Sci Technol & Med Dept Elect & Elect Engn London SW7 2BT England

This study presents an ordinal optimisation (OO) method for specifying the locations and capacities of distributed generation (DG) such that a trade-off between loss minimisation and DG capacity maximisation is achieved. The OO approach consists of three main phases. First, the large search space of potential combinations of DG locations is represented by sampling a relatively small number of alternatives. Second, the objective function value for each of the sampled alternatives is evaluated using a crude but computationally efficient linear programming model. Third, the top-s alternatives from the crude model evaluation are simulated via an exact non-linear programming optimal power flow (OPF) programme to find the best DG locations and capacities. OO theory allows computing the size s of the selected subset such that it contains at least k designs from among the true top-g samples with a pre-specified alignment probability AP. This study discusses problem-specific approaches for sampling, crude model implementation and subset size selection. The approach is validated by comparing with recently published results of a hybrid genetic algorithm OPF applied to a 69-node distribution network operating under Ofgem (UK) financial incentives for distribution network operators.

关键词： crude model evaluation nonlinear programming distribution network operator distributed power generation Distribution networks load flow ordinal optimisation approach linear programming model distributed generation capacity maximisation linear programming Optimisation techniques alignment probability nonlinear programming optimal power flow

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An interval fuzzy robust nonlinear program for the planning of municipal solid waste management systems under uncertainty

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ENGINEERING OPTIMIZATION 2009年第11期41卷 989-1016页

作者： Sun, Y. Huang, G. H. Li, Y. P. Xu, Y. Cao, M. F. N China Elect Power Univ Sino Canada Ctr Energy & Environm Res Beijing 102206 Peoples R China Univ Regina Fac Engn Regina SK S4S 0A2 Canada Peking Univ Coll Urban & Environm Sci Beijing 100871 Peoples R China

An interval fuzzy robust nonlinear program (IFRNLP) is developed and applied to a municipal solid waste (MSW) management planning problem. The method improves upon existing fuzzy robust programming and interval nonlinear programming by considering dual uncertainties and the effects of economies of scale on the MSW system. The proposed IFRNLP can explicitly address system uncertainties with complex presentations, such as fuzzy sets, interval numbers, and their combinations. The developed IFRNLP is then applied to the planning of a MSW management. The results indicate that reasonable solutions have been generated. They reflect a compromise between optimality and stability of the study system, and are realistic reflections of system complexities such as nonlinear and dual uncertainties. Moreover, when compared with existing methods of interval nonlinear programming and interval fuzzy robust linear programming, IFRNLP can provide a more effective means of reflecting system cost variations and may, therefore, generate more realistic and applicable solutions.

关键词： environment interval optimization nonlinear programming robust programming solid waste planning uncertainty

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Incremental Global Parameter Estimation in Dynamical Systems

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INDUSTRIAL & ENGINEERING CHEMISTRY RESEARCH 2009年第11期48卷 5489-5497页

作者： Michalik, Claas Chachuat, Benoit Marquardt, Wolfgang Rhein Westfal TH Aachen AVT Proc Syst Engn D-52064 Aachen Germany Ecole Polytech Fed Lausanne Lab Automat CH-1015 Lausanne Switzerland

Estimating the parameters of a dynamical system based on measurements is an important task in industrial and scientific practice. Since a model's quality is directly linked to its parameter values, obtaining globally rather than locally optimal values is especially important in this context. In practice, however, local methods, are used almost exclusively. This is mainly due to the high computational cost of global dynamic parameter estimation, which limits its application to relatively small problems comprising no more than a few equations and parameters. In addition, there is still a lack of software packages that allow global parameter estimation in dynamical systems without expert knowledge. Therefore, we propose an efficient computational method for obtaining globally optimal parameter estimates of dynamical systems using well-established, user-friendly software packages. The method is based on the so-called incremental identification procedure, in combination with deterministic global optimization tools for nonlinear programs.

关键词： DYNAMICAL SYSTEMS computational methods Industrial Expert Opinion Parameter estimation nonlinear programming optimal parameter Software packages dynamic parameter Population parameter

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Three-Dimensional Trajectory Optimization Satisfying Waypoint and No-Fly Zone Constraints

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2009年第2期32卷 551-572页

作者： Jorris, Timothy R. Cobb, Richard G. USAF Inst Technol Dept Aeronaut & Astronaut Wright Patterson AFB OH 45433 USA

To support the U.S. Air Force's global reach concept, a Common Aero, Vehicle is being designed to support the global strike mission. Waypoints are specified for reconnaissance or multiple payload deployments and no-fly zones are specified for geopolitical restrictions or threat avoidance. Because of time critical targets and multiple scenario analysis, an autonomous solution is preferred over a time-intensive, manually Iterative one. Thus, it real-time or near real-time autonomous trajectory optimization technique is presented to minimize the flight time, satisfy terminal and Intermediate constraints, and remain within the specified vehicle heating and control limitations. This research uses the hypersonic cruise vehicle as a simplified two-dimensional platform to compute an optimal analytical solution. An up-and-coming numerical technique is it direct solution method involving discretization and then dualization, with pseudospectral methods and nonlinear programming used to converge to the optimal solution. This numerical technique Is first compared to the previously derived 2-D hypersonic cruise vehicle analytical results to demonstrate convergence to the optimal solution. Then, the numerical approach is applied to the 3-D Common Aero Vehicle as the test platform for the flat Earth three-dimensional reentry trajectory optimization problem. The culmination of this research is the verification or the optimality or this proposed numerical technique, as shown for both the two-dimensional and three-dimensional models. Additionally, user Implementation strategies art, presented to improve accuracy, enhance solution convergence, and facilitate autonomous implementation.

关键词： Pseudospectral Optimal Control Gauss Pseudospectral Method nonlinear programming Earth Air Forces Flight Path Angle Aerodynamic Drag Stagnation Point Lagrange Multipliers Angle of Attack

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