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Decision feedback data detection in frequency domain for single carrier cyclic prefix assisted CDMA systems: A sequential quadratic programming approach

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DIGITAL SIGNAL PROCESSING 2009年第4期19卷 678-692页

作者： Madhukumar, A. S. Yang, Kai Chin, Francois Premkumar, A. B. Nanyang Technol Univ Sch Comp Engn Singapore 639798 Singapore Columbia Univ Dept Elect Engn New York NY 10027 USA Inst Infocomm Res Singapore 117674 Singapore

This paper proposes a frequency domain decision feedback data receiver for the uplink transmission of broadband single carrier cyclic prefix-assisted CDMA systems. The optimum data detection problem based on the maximal-likelihood criteria for this system is addressed as a combinatorial optimization problem. A sequential quadratic programming approach is proposed to solve this problem. The parallel gradient projection method and projected successive over relaxation algorithm are proposed to solve the sequential quadratic programming problem, which corresponds to low-complexity nonlinear parallel and successive interference cancellation schemes in frequency domain. The convergence properties and the complexities of these methods are analyzed and compared with conventional methods. The simulation results show that, with a few iterations, the proposed scheme gives near single user performance even for fully loaded systems. (c) 2008 Elsevier Inc. All rights reserved.

关键词： Code division multiple access Multicarrier modulation Multiuser detection sequential quadratic programming

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Pulsed Array of Spiral Antennas for Scanned Energy Pattern with Low Side Lobes

Pulsed Array of Spiral Antennas for Scanned Energy Pattern w...

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IEEE International Symposium on Antennas and Propagation / USNC/URSI National North American Radio Science Meeting

作者： Reyna, Alberto Panduro, Marco A. Univ Autonoma Tamaulipas UAMRR Reynosa Tamaulipas Mexico

ISBN: (纸本)9781479978151

this document presents a design approach of a pulsed antenna array of circularly polarized two-arm log spiral antennas. The design is addressed as an optimization of the antenna positions in order to obtain a scanned energy pattern with low side lobes in time domain. It is utilized the well-known sequential quadratic programming for the optimization. The results revealed good performance of the pulsed antenna array for ultra wide band, circular polarization and scanning properties.

关键词： Pulsed antenna arrays Spiral antenna Energy pattern sequential quadratic programming

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An integrated perturbation analysis and sequential quadratic programming approach for Model Predictive Control

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AUTOMATICA 2009年第10期45卷 2412-2418页

作者： Ghaemi, Reza Sun, Jing Kolmanovsky, Ilya V. Univ Michigan Dept Elect Engn & Comp Sci Ann Arbor MI 48109 USA Univ Michigan Dept Naval Architecture & Marine Engn Ann Arbor MI 48109 USA Ford Motor Co Dearborn MI 48124 USA

Computationally efficient algorithms are critical in making Model Predictive Control (MPC) applicable to broader classes of systems with fast dynamics and limited computational resources. In this paper, we propose an integrated formulation of Perturbation Analysis and sequential quadratic programming (InPA-SQP) to address the constrained optimal control problems. The proposed algorithm combines the complementary features of perturbation analysis and SQP in a single unified framework, thereby leading to improved computational efficiency and convergence property. A numerical example is reported to illustrate the proposed method and its computational effectiveness. (C) 2009 Elsevier Ltd. All rights reserved.

关键词： Nonlinear MPC Fast MPC Neighboring Extremal Optimal Control sequential quadratic programming

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On the Performance of SQP Methods for Nonlinear Optimization

On the Performance of SQP Methods for Nonlinear Optimization

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Conference on Modeling and Optimization - Theory and Applications (MOPTA)

作者： Gill, Philip E. Saunders, Michael A. Wong, Elizabeth Univ Calif San Diego Dept Math La Jolla CA 92093 USA Stanford Univ Dept Management Sci & Engn Syst Optimizat Lab Stanford CA 94305 USA

ISBN: (纸本)9783319236995;9783319236988

This paper concerns some practical issues associated with the formulation of sequential quadratic programming (SQP) methods for large-scale nonlinear optimization. SQP methods find approximate solutions of a sequence of quadratic programming (QP) subproblems in which a quadratic model of the Lagrangian is minimized subject to the linearized constraints. Numerical results are given for 1153 problems from the CUTEst test collection. The results indicate that SQP methods based on maintaining a quasi-Newton approximation to the Hessian of the Lagrangian function are both reliable and efficient for general large-scale optimization problems. In particular, the results show that in some situations, quasi-Newton SQP methods are more efficient than interior methods that utilize the exact Hessian of the Lagrangian. The paper concludes with discussion of an SQP method that employs both approximate and exact Hessian information. In this approach the quadratic programming subproblem is either the conventional subproblem defined in terms of a positive-definite quasi-Newton approximate Hessian or a convexified subproblem based on the exact Hessian.

关键词： Nonlinear programming sequential quadratic programming SQP methods Interior methods Convexification Active-set methods quadratic programming

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Constrained particle swarm optimisation for sequential quadratic programming

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INTERNATIONAL JOURNAL OF MODELLING IDENTIFICATION AND CONTROL 2009年第4期8卷 361-367页

作者： Richards, Zach D. United Launch Alliance Littleton CO 80127 USA

sequential quadratic programming (SQP) methods are commonly used to solve constrained non-linear optimisation problems. However, in recent years there has been great improvement in using evolutionary algorithms to solve non-linear optimisations problems. The difficulty has been determining a correct method for implementing evolutionary algorithm for a non-linear optimisation problem with constraints. In this paper, we are combining the strengths of the traditional SQP method with an evolutionary algorithm, particle swarm optimisation (PSO) for solving a constrained non-linear optimisation problem with equality and inequality constraints. We propose a constrained PSO algorithm be used to solve the quadratic programming (QP) subproblem within the SQP method.

关键词： non-linear optimisation particle swarm sequential quadratic programming SQP infeasibility function quadratic subproblem hybrid optimisation non-linear constrained particle swarm optimisation algorithm NLCPSOA

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Hybrid PSO-SQP Algorithm for Solving System Reliability Allocation Optimization

Hybrid PSO-SQP Algorithm for Solving System Reliability Allo...

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2015 International Conference on Materials Engineering and Information Technology Applications(MEITA 2015)

作者： TANG Cheng GUO Shu-xiang MO Yan-yu Science College Air Force Engineering University Aeronautics and Astronautics Engineering College Air Force Engineering University

ISBN: (纸本)9781510812055

System reliability allocation is an important ingredient in system reliability design, and it is also a decision-making issue of reliability engineering. To achieve the optimization of system reliability allocation, an optimization model for system reliability allocation, which takes the system cost as the objective function, is constructed through the general cost function. In order to overcome the shortcomings of particle swarm optimization(PSO) appearing in reliability allocation optimization, the premature and/or slow speed of convergence in later period, the sequential quadratic programming(SQP) was introduced to improve the PSO algorithm. The algorithm uses PSO as the global optimizer while the SQP is employed for accelerating the local search. Thus, the particles are able to search the whole space while searching for local optimization fast, which not only assures the convergence of the algorithm, but also increases the probability of obtaining the global optimum. Applied the algorithm to the problem of system reliability allocation, the simulation results show that it has excellent global search capability and provides rational optimization results compared to the existing approaches.

关键词： system reliability reliability allocation particle swarm optimization sequential quadratic programming

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The Structural Optimization of Gearbox Based on sequential quadratic programming Method

The Structural Optimization of Gearbox Based on Sequential Q...

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2nd International Conference on Intelligent Computation Technology and Automation

作者： Huang Wei Fu Lingling Liu Xiohuai Wen Zongyin Zhao Leisheng Guangxi Univ Coll Mech Engn Nanning 530004 Peoples R China Guangxi Commun Vocat & Tech Inst Nanning Peoples R China

ISBN: (纸本)9780769538044

Taking the gearbox of medium-sized motor truck for example and According to structural features and design requirements of the gearbox, the mathematical model of optimization which takes the basic design parameters of gearbox as design variable and takes weight loss as the target was established. Optimization tool box of MATLAB and sequential quadratic programming (SQP) method were used to optimize the gearbox and good optimization results were obtained, thus the design efficiency is improved and the production cost of enterprises was reduced.

关键词： Gearbox Optimum design sequential quadratic programming

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Optimal Placement of Phasor Measurement Units with Linear and Non-linear Models

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第4期43卷 357-373页

作者： Theodorakatos, Nikolaos P. Manousakis, Nikolaos M. Korres, George N. Natl Tech Univ Athens ECE Dept Athens Greece

Abstract-This article presents a non-linear programming-based model for the optimal placement of phasor measurement units. The optimal phasor measurement units placement is formulated to minimize the number of phasor measurement units required for full system observability and to maximize the measurement redundancy at all buses in a power system. A sequential quadratic programming algorithm is used for the solution of the proposed model. The existence of power flow and injection measurements, the limited phasor measurement units channel capacity, the lack of communication facilities in substations, and the single phasor measurement units loss are also incorporated into the initial proposed formulation. The non-linear programming model is applied to IEEE 14- and 118-bus test systems in MATLAB. The accuracy and the effectiveness of the proposed method is verified by comparing the simulation results to those obtained by a binary integer programming model also implemented in MATLAB. The comparative study shows that the proposed non-linear programming model yields the same number of phasor measurement units as the binary integer programming model. A remarkable advantage of the non-linear programming against binary integer linear programming is its capability to give more than one optimal solution, each one having the same minimum number of phasor measurement units (same minimum objective value), but at different locations.

关键词： binary integer linear programming optimization mixed integer linear programming Phasor measurement unit observability sequential quadratic programming optimal placement non-linear programming

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An automated approach to magnetic divertor configuration design

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NUCLEAR FUSION 2015年第1期55卷 013001-013001页

作者： Blommaert, M. Dekeyser, W. Baelmans, M. Gauger, N. R. Reiter, D. Forschungszentrum Julich Inst Energy & Climate Res Plasma Phys IEK 4 D-52425 Julich Germany Katholieke Univ Leuven Dept Mech Engn B-3001 Louvain Belgium Rhein Westfal TH Aachen Dept Math D-52062 Aachen Germany Rhein Westfal TH Aachen Ctr Computat Engn Sci D-52062 Aachen Germany

Automated methods based on optimization can greatly assist computational engineering design in many areas. In this paper an optimization approach to the magnetic design of a nuclear fusion reactor divertor is proposed and applied to a tokamak edge magnetic configuration in a first feasibility study. The approach is based on reduced models for magnetic field and plasma edge, which are integrated with a grid generator into one sensitivity code. The design objective chosen here for demonstrative purposes is to spread the divertor target heat load as much as possible over the entire target area. Constraints on the separatrix position are introduced to eliminate physically irrelevant magnetic field configurations during the optimization cycle. A gradient projection method is used to ensure stable cost function evaluations during optimization. The concept is applied to a configuration with typical Joint European Torus (JET) parameters and it automatically provides plausible configurations with reduced heat load.

关键词： divertor design edge plasma modelling magnetic topology power deposition sequential quadratic programming parameter optimization

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Large-Scale Multidisciplinary Optimization of a Small Satellite's Design and Operation

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JOURNAL OF SPACECRAFT AND ROCKETS 2014年第5期51卷 1648-1663页

作者： Hwang, John T. Lee, Dae Young Cutler, James W. Martins, Joaquim R. R. A. Univ Michigan Dept Aerosp Engn Ann Arbor MI 48109 USA

The design of satellites and their operation is a complex task that involves a large number of variables and multiple engineering disciplines. Thus, it could benefit from the application of multidisciplinary design optimization, but previous efforts have been hindered by the complexity of the modeling and implementation, discontinuities in the design space, and the wide range of time scales. We address these issues by applying a new mathematical framework for gradient-based multidisciplinary optimization that automatically computes the coupled derivatives of the multidisciplinary system via a generalized form of the adjoint method. The modeled disciplines are orbit dynamics, attitude dynamics, cell illumination, temperature, solar power, energy storage, and communication. Many of these disciplines include functions with discontinuities and nonsmooth regions that are addressed to enable a numerically exact computation of the derivatives for all of the modeled variables. The wide-ranging time scales in the design problem, spanning 30 s to one year, are captured through a combination of multipoint optimization and the use of a small time step in the analyses. Optimizations involving over 25,000 design variables and 2.2 million state variables require 100 h to converge three and five orders of magnitude in optimality and feasibility, respectively. The results show that the geometric design variables yield a 40% improvement in the total data downloaded, which is the objective function, and the operational design variables yield another 40% improvement. This demonstrates not only the value in this approach for the design of satellites and their operation, but also promise for its application to the design of other large-scale engineering systems.

关键词： Small Satellites MDO Attitude Control System Energy Storage Solar Power Ground Station Earth Reaction Wheels sequential quadratic programming Power Generation

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