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AN EFFICIENT NUMERICAL METHOD FOR THE SOLUTION OF THE L₂ OPTIMAL MASS TRANSFER PROBLEM

SIAM JOURNAL ON SCIENTIFIC COMPUTING 2010年第1期32卷 197-211页

作者： Haber, Eldad Rehman, Tauseef Tannenbaum, Allen Emory Univ Dept Math & Comp Sci Atlanta GA 30322 USA Georgia Inst Technol Sch Elect & Comp Engn Atlanta GA 30332 USA Georgia Inst Technol Sch Elect & Comp Atlanta GA 30332 USA Georgia Inst Technol Sch Biomed Engn Atlanta GA 30332 USA

In this paper we present a new computationally efficient numerical scheme for the minimizing flow approach for the computation of the optimal L-2 mass transport mapping. In contrast to the integration of a time dependent partial differential equation proposed in [S. Angenent, S. Haker, and A. Tannenbaum, SIAM J. Math. Anal., 35 (2003), pp. 61-97], we employ in the present work a direct variational method. The efficacy of the approach is demonstrated on both real and synthetic data.

关键词： optimal mass transport sequential quadratic programming variational formulation

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quadratic programming solver for structural optimisation using SQP algorithm

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ADVANCES IN ENGINEERING SOFTWARE 2002年第7-10期33卷 669-674页

作者： Horowitz, B Afonso, SMB Univ Fed Pernambuco Dept Civil Engn BR-50740 Recife PE Brazil

The dual quadratic programming algorithm of Goldfarb and Idnani is implemented as a solver for a sequential quadratic programming algorithm. Initially the algorithm is briefly described. As the algorithm requires the inverse of the Cholesky factor of the Hessian matrix at each iteration a procedure is presented to directly obtain a matrix that multiplied by its transpose gives the BFGS update of the Hessian. A procedure is then presented to triangularise the updated factor using two series of Givens rotations. In order to increase efficiency a 'warm start' strategy is proposed whereby the choice of constraints to enter the active set is based on information of previous SQP iterations. Finally two examples are given to demonstrate the efficiency and robustness of the implementation. (C) 2002 Civil-Comp Ltd and Elsevier Science Ltd. All rights reserved.

关键词： optimisation structural design mathematical programming sequential quadratic programming quadratic programming finite elements

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Swarm Intelligence-based Stochastic programming Model for Dynamic Asset Allocation

Swarm Intelligence-based Stochastic Programming Model for Dy...

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2010 IEEE World Congress on Computational Intelligence

作者： Dang, Jing Edelman, David Hochreiter, Ronald Brabazon, Anthony Univ Coll Dublin Nat Comp Res & Applicat Grp Sch Business Dublin Ireland WU Vienna Univ Econom & Business Dept Math & Stat Vienna Austria

ISBN: (纸本)9781424481262

Asset allocation is critical for the portfolio management process. In this paper, we solve a dynamic asset allocation problem through a multiperiod stochastic programming model. The objective is to maximise the expected utility of wealth at the end of the planning period. To improve the optimisation process of the model, we employ swarm intelligent optimisers, the Bacterial Foraging Optimisation (BFO) and the Particle Swarm Optimisation (PSO) algorithm. A hybrid optimiser using the BFO for initialisation and the sequential quadratic programming (SQP) for searching the decision variables is also suggested. The results are compared with the stand-alone SQP and the canonical Genetic Algorithm. We have performed numerical experiments on 2-asset and 4-asset allocation problem respectively. The numerical results suggest that the hybrid method provides a better result especially for the 4-asset case, with improved fitness value and robustness than using BFO, PSO, GA, or SQP alone.

关键词： bacterial foraging optimisation canonical genetic algorithm dynamic asset allocation financial management hybrid optimiser optimisation process particle swarm optimisation particle swarm optimisation planning period portfolio management process quadratic programming robustness sequential quadratic programming stochastic programming stochastic programming model swarm intelligent optimiser

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Predictive velocity control in a hilly terrain over a long look-ahead horizon

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IFAC-PapersOnLine 2018年第31期51卷 485-492页

作者： Hamednia A. Murgovski N. Fredriksson J. Department of Electrical Engineering Chalmers University of Technology Gothenburg 41296 Sweden

This paper presents a computationally efficient velocity control of vehicles driving in a possibly hilly terrain and over long look-ahead horizons that may stretch to hundreds of kilometers. The controller decouples gear scheduling into an offline optimization problem, from the remaining optimization problem that governs two real-valued states. One of the states, the travel time, is adjoined to the objective by applying the necessary optimality conditions, which results into an online optimization problem that has kinetic energy as the single state. Finally an inner approximation is proposed for the online problem to obtain a quadratic program that can be solved efficiently. The efficiency of the proposed controller is shown for different horizon lengths. © 2018

关键词： Cruise control Offline gear scheduling Predictive control sequential quadratic programming

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Multi-Agent Based Optimal Power Flow Solution

Multi-Agent Based Optimal Power Flow Solution

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Asia-Pacific Power and Energy Engineering Conference (APPEEC)

作者： Leeton, Uthen Kulworawanichpong, Thanatchai Suranaree Univ Technol Sch Elect Engn Inst Engn Power Syst Res Unit Nakhon Ratchasima 30000 Thailand

ISBN: (纸本)9781457705472;9781457705465

This paper describes multi-agent based optimal power flow solution in which total production cost is used as the problem objective to be minimized. In this work, simulation of peer-to-peer device coordination has been developed using Java Agent Development (JADE) software package. JADE provides a FIPA-compliant agent platform and a package to develop multi-agent systems used in this paper. Six agent types are established. They are i) load agent ii) power generating plants agent, iii) transformer tap-setting agent iv) reactive power agent v) optimal load-flow agent and vi) management agent. In this paper each agent has been modeled as an intelligent agent, which joins to a container to form the multi agent system for solving optimal power flow problems. In this paper, the standard IEEE 6-bus test power system was employed. The results of this proposed system showed that the use of multi-agent systems enables possibility of applying optimal power flow in real-world applications.

关键词： optimal power flow multi-agent system sequential quadratic programming

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Optimal Placement of Phasor Measurement Units with Linear and Non-linear Models (vol 43, pg 357, 2015)

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ELECTRIC POWER COMPONENTS AND SYSTEMS 2015年第6期43卷 721-721页

作者： Nikolaos, Theodorakatos Korres, George Manousakis, Nikolaos ECE Department National Technical University of Athens Athens Greece

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

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Optimal Operation of Microgrid with Photovoltaics and Gas Turbines in Demand Response

Optimal Operation of Microgrid with Photovoltaics and Gas Tu...

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International Conference on Power System Technology (PowerCon)

作者： Pei, Wei Du, Yan Xiao, Hao Shen, Ziqi Deng, Wei Yang, Yanhong Chinese Acad Sci Inst Elect Engn Beijing 100190 Peoples R China Univ Chinese Acad Sci Beijing Peoples R China

ISBN: (纸本)9781479950324

The development of smart grid and distributed energy resources makes it possible for the large number of distributed gas turbines and photovoltaics in cities to interact with the utility grid and provide ancillary services via different demand response programs. By implementing the two-part real-time pricing mechanism to encourage microgrid participation in demand response, this paper presents the optimization model of microgrid with multi-energy resources in price-based demand response program with the aim of net income maximization. The algorithm of sequential quadratic programming is applied to solve the problem. The effects of real-time pricing, state of charge and unit ratio on demand response are further discussed in detail. The simulation results indicate that the microgrid integrating photovoltaics with gas turbines demonstrates significant elasticity and flexibility in providing ancillary services through demand response.

关键词： demand response microgrid real-time pricing sequential quadratic programming

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Nonlinear Model Predictive Motion Control of Differential Wheeled Robots

Nonlinear Model Predictive Motion Control of Differential Wh...

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IEEE National Aerospace and Electronics Conference (NAECON)

作者： Raziei, Seyed Ata Jiang, Zhenhua Univ Dayton Dept Elect & Comp Engn Dayton OH 45469 USA Univ Dayton Res Inst Power & Energy Div Dayton OH 45469 USA

ISBN: (纸本)9781538665572

Real-time motion control of a nonholonomic mobile robot in a dynamic environment, especially in the case of multiobjective control, is a challenging problem. Model predictive control (MPC) as an optimization based control algorithm has the ability to deal with complex systems, like multiple-input and multiple-output (MIMO) system, in a dynamic environment. However, due to the complexity of optimization algorithms, the implementation of MPC in real-time applications, especially for the systems with fast transient behaviors is very challenging. With the advent of processors with the ability of parallel computing like FPGAs and GPUs, the application of MPC has become reachable. In this study, the algorithm of optimization problem as the core part of the MPC for motion control of a two-wheel differential robot was developed. Considering the final objective of coding the optimization algorithm on FPGA, the sequential quadratic programming (SQP) method was selected as the optimization algorithm. The specific algorithm equations and matrices were derived based on a simplified nonlinear model. The algorithms were then be coded in MATLAB and used to control a two-wheel robot in the simulation. This paper present the MPC design process and simulation results for the cases of path tracking and point tracking.

关键词： nonlinear model predictive control differential wheeled robots sequential quadratic programming constrained optimization motion planning

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Identification of linear systems using output measurements with only two possible values

Identification of linear systems using output measurements w...

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50th IEEE Conference of Decision and Control (CDC)/European Control Conference (ECC)

作者： Depraetere, Bruno Pinte, Gregory Swevers, Jan Katholieke Univ Leuven PMA Fac Mech Engn Celestijnenlaan 300 B1D2 B-3001 Louvain Belgium FMTC B-3001 Louvain Belgium

ISBN: (纸本)9781612848013

Classical identification cannot be applied when no output measurements are available. In many situations however, discrete information on the unmeasured outputs can still be obtained and used to identify the underlying dynamics. An example is a moving object where an optical sensor can detect whether or not is in the sensors line of sight but whose position is not measured. Using these discrete data sources to estimate a model for the underlying dynamics is equivalent to the estimation of the linear parameters of a Wiener system, which has a known but non-invertible static non-linearity with two output levels. Techniques are derived to perform this estimation, using sequential quadratic programming to minimize a least squares goal function. Simulations are used to validate the proposed approach, yielding good convergence of the linear model parameters to their targets and a high prediction accuracy for the unmeasured variable of the Wiener system.

关键词： identification wiener model gauss-newton least squares sequential quadratic programming discrete sensor data linear model estimation

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sequential Tuning of Power System Stabilizers for Improving the Small Signal Stability in Multi-machine Power Systems

Sequential Tuning of Power System Stabilizers for Improving ...

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World Congress on Engineering and Computer Science

作者： Mahabuba, A. Khan, M. Abdullah AL Ghurair Univ Dubai U Arab Emirates BS Abdur Rahman Univ Sci & Technol Madras Tamil Nadu India

ISBN: (纸本)9789881925244

This paper presents a sequential tuning of Power System Stabilizers (PSSs) for improving the damping of low frequency electro- mechanical oscillations in a multi-machine power system using parameter - constrained nonlinear optimization algorithm. This algorithm deals with optimization problem using a sequential quadratic programming. The main objective of this procedure is to shift the undamped poles to the left hand side of the s-plane. In the proposed work, the parameters of each PSS controller are determined by sequentially using non-linear optimization technique. The objective of the coordinated parameter tuning is to globally optimize the overall system damping performance by maximize the damping of all both local and inter area modes of oscillations. The results obtained from sequential coordinating tuning method validate the improvement in damping of the overall power system oscillations in an optimal manner. The time domain simulation results of multi-machine power system validate the effectiveness of the proposed approach. In this paper, 10- machine 39- bus New England system is used as the test system. Investigations revealed that the dynamic performance of the system with sequentially tuned PSS is superior to that obtained from the conventionally optimized PSS.

关键词： Coordinated tuning sequential tuning Power System Stabilizer (PSS) Non-linear Optimization sequential quadratic programming

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