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Application of sequential quadratic programming method to temperature distribution control in reactor furnace

ISIJ INTERNATIONAL 2005年第3期45卷 347-355页

作者： Ishimaru, K Konishi, M Imai, J Nishi, T Okayama Univ Grad Sch Nat Sci & Technol Okayama 7008530 Japan Okayama Univ Dept Elect & Elect Engn Okayama 7008530 Japan

Recently, various studies have been undertaken to examine the inner furnace phenomena of a blast furnace. These studies are limited, however, to the evaluation of furnace performance while a designed method of furnace control remains unfulfilled. This paper proposes a method of estimating temperature distribution in a reactor furnace using boundary data in order to control inner target furnace temperature distribution. Initially, a simplified furnace simulation program for the calculation of inner furnace gas flow, pressure and temperature distribution is developed. Following that, the simulator is used to estimate and control inner furnace temperature distribution. In the estimation, boundary data such as temperature and pressure, measured near a furnace wall, are used in the furnace simulation. Then, for the control of inner furnace temperature distribution, necessary values for gas blowing at the bottom of the furnace and the burden supply at the top of the furnace are used. Both for the estimation and the control of the inner furnace temperature distribution, a sequential quadratic programming method, a method of the iterative optimization, is applied. In our method, an estimation of inner furnace temperature distribution is done as preparation for the determination of furnace control variables. Through numerical experiments, the validity of our method is demonstrated, showing that the temperature distribution in a furnace can be regulated to the desired one after iterative control operations.

关键词： sequential quadratic programming method optimization reactor furnace temperature distribution

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A study on the optimization method for a multi-body system using the response surface analysis

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JOURNAL OF MECHANICAL SCIENCE AND TECHNOLOGY 2009年第4期23卷 950-953页

作者： Jung, Sung-Pil Park, Tae-Won Jun, Kab-Jin Yoon, Ji-Won Lee, Soo-Ho Chung, Won-Sun Ajou Univ Dept Mech Engn Suwon 443749 South Korea Ajou Univ Grad Sch Mech Engn Suwon 443749 South Korea Korea Automot Technol Inst Body Chassis Reliabil Div Cheonan 330912 South Korea

An optimization method, which minimizes the characteristic value of a system using response surface analysis, is presented. Plackett-Burman design is used as a screening method. Using the response surface analysis, second order recursive model function is estimated as an objective function. To verify the reliability of the model function, an F-test based on the analysis of variances table is used. Lastly, the sequential quadratic-programming method is used to find the value of design parameters. By applying the preceding procedure to a multi-body dynamic model, the optimization process presented in this study is verified.

关键词： Design of experiments Plackett-Burman design Central composite design Analysis of variance sequential quadratic programming method

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DOTcvpSB, a software toolbox for dynamic optimization in systems biology

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BMC BIOINFORMATICS 2009年第1期10卷 199-199页

作者： Hirmajer, Tomas Balsa-Canto, Eva Banga, Julio R. IIM CSIC Inst Invest Marinas Spanish Council Sci Res Vigo 36208 Spain Slovak Acad Sci Inst Neuroimmunol Bratislava 84510 Slovakia

Background: Mathematical optimization aims to make a system or design as effective or functional as possible, computing the quality of the different alternatives using a mathematical model. Most models in systems biology have a dynamic nature, usually described by sets of differential equations. Dynamic optimization addresses this class of systems, seeking the computation of the optimal time-varying conditions (control variables) to minimize or maximize a certain performance index. Dynamic optimization can solve many important problems in systems biology, including optimal control for obtaining a desired biological performance, the analysis of network designs and computer aided design of biological units. Results: Here, we present a software toolbox, DOTcvpSB, which uses a rich ensemble of state-of-the-art numerical methods for solving continuous and mixed-integer dynamic optimization (MIDO) problems. The toolbox has been written in MATLAB and provides an easy and user friendly environment, including a graphical user interface, while ensuring a good numerical performance. Problems are easily stated thanks to the compact input definition. The toolbox also offers the possibility of importing SBML models, thus enabling it as a powerful optimization companion to modelling packages in systems biology. It serves as a means of handling generic black-box models as well. Conclusion: Here we illustrate the capabilities and performance of DOTcvpSB by solving several challenging optimization problems related with bioreactor optimization, optimal drug infusion to a patient and the minimization of intracellular oscillations. The results illustrate how the suite of solvers available allows the efficient solution of a wide class of dynamic optimization problems, including challenging multimodal ones. The toolbox is freely available for academic use.

关键词： Dynamic Optimization Initial Value Problem Global Optimization method Dynamic Optimization Problem sequential quadratic programming method

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An Optimum Design of a Gas Circuit Breaker Using Design of Experiments

An Optimum Design of a Gas Circuit Breaker Using Design of E...

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International Symposium on Multibody Systems and Mechatronics

作者： Jung, Sung Pil Jun, Kab Jin Park, Tae Won Ahn, Ill Chul Ajou Univ Dept Mech Engn Suwon 443749 Gyeonggi Do South Korea Ajou Univ Grad Sch Mech Engn Suwon 443749 Gyeonggi Do South Korea LS Ind Syst Co LTD Electrotechnol R&D Ctr GIS Res Team Cheongju South Korea

In this study, a gas circuit breaker (GCB) used to interrupt or apply an electric current in a high-voltage system is optimized using design of experiments. A multibody dynamic simulation model of the GCB is created and the performance of the system is optimized according to the optimization procedure presented in this paper. Sensitivity analysis is performed on the basis of a Plackett-Burman design table. Then, through the response surface analysis, the objective function is estimated and the reliability of the function is verified by an analysis of variance table. Using the sequential quadratic programming method, the values of design parameters that minimize the objective function and satisfy the constraint conditions are obtained. The performance of the current and optimized system is compared and by conducting an actual test of the GCB, the reliability of the simulation model and the usefulness of the optimal design method presented are verified.

关键词： Analysis of variance Objective function Plackett-Burman design Response surface analysis sequential quadratic programming method

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An Optimum Design of a Gas Circuit Breaker Using Design of Experiments

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MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES 2008年第4期36卷 346-363页

关键词： Analysis of variance Objective function Plackett-Burman design Response surface analysis sequential quadratic programming method

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Selection of appropriate approximation schemes in multi-disciplinary engineering optimization

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ADVANCES IN ENGINEERING SOFTWARE 2000年第6期31卷 385-389页

作者： Fluery, C Zhang, WH Univ Liege LTAS Aerosp Lab B-4000 Liege Belgium

Convex approximation methods used in structural optimization are discussed in this paper. These methods ranging from CONvex LINearization method (CONLIN), the method of Moving Asymptotes (MMA) to the sequential quadratic programming method (SQP) can be basically classified as monotonic and non-monotonic approximations. It is shown that for the considered problems of different nature, the achievement of a successful and efficient design will essentially depend upon whether approximation schemes can be appropriately selected. To ensure the approximation quality, a Generalized method of the Moving Asymptotes (GMMA) and a Diagonal quadratic Approximation (DQA) based optimizers are developed, respectively, in this work. In addition, it can be seen that the mixed approximation DQA-GMMA can be also established. Numerical examples of truss design will be used to illustrate these methods. (C) 2000 Published by Elsevier Science Ltd. All rights reserved.

关键词： method of moving asymptotes sequential quadratic programming method convex approximation methods

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Numerical approximation of optimal flow control problems by a penalty method: Error estimates and numerical results

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SIAM JOURNAL ON SCIENTIFIC COMPUTING 1999年第5期20卷 1753-1777页

作者： Hou, LS Ravindran, SS Iowa State Univ Dept Math Ames IA 50011 USA York Univ Dept Math & Stat N York ON M3J 1P3 Canada NASA Langley Res Ctr Flow Modeling & Control Branch Hampton VA 23681 USA

The purpose of this paper is to present numerically convenient approaches to solve optimal Dirichlet control problems governed by the steady Navier-Stokes equations. We will examine a penalized Neumann control approach for solving Dirichlet control problems from numerical and computational points of view. The control is affected by the suction or injection of fluid through the boundary or by boundary surface movements in the tangential direction. The control objective is to minimize the vorticity in the flow or to drive the velocity field to a desired one. We develop sequential quadratic programming methods to solve these optimal control problems. The effectiveness of the optimal control techniques in flow controls and the feasibility of the proposed penalized Neumann control approaches for flow control problems are demonstrated by numerical experiments for a viscous, incompressible fluid flow in a two-dimensional channel and in a cavity geometry.

关键词： flow control sequential quadratic programming method Navier-Stokes equations finite elements vorticity optimization

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A combined method for the global optimization using radial basis function and deterministic approach

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IEEE TRANSACTIONS ON MAGNETICS 1999年第3期35卷 1730-1733页

作者： Ishikawa, T Tsukui, Y Matsunami, M Gunma Univ Dept Elect Engn Kiryu Gumma 3768515 Japan

The present paper proposes a combined method for the global optimization of realistic engineering problems using radial basis functions and a deterministic approach. A die mold model for orientation of magnetic powder... 详细信息

关键词： global optimization radial basis function sequential quadratic programming method

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NLPQL: A fortran subroutine solving constrained nonlinear programming problems

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Annals of Operations Research 1986年第1-4期5卷 485-500页

作者： Schittkowski, K. Institut für Informatik Universität Stuttgart Stuttgart 1 D-7000 Azenbergstrasse 12 Germany

NLPQL is a FORTRAN implementation of a sequential quadratic programming method for solving nonlinearly constrained optimization problems with differentiable objective and constraint functions. At each iteration, the search direction is the solution of a quadratic programming subproblem. This paper discusses the organization of NLPQL, including the formulation of the subproblem and the information that must be provided by a user. A summary is given of the performance of different algorithmic options of NLPQL on a collection of test problems (115 hand-selected or application problems, 320 randomly generated problems). The performance of NLPQL is compared with that of some other available codes. © 1986 *** A.G., Scientific Publishing Company.

关键词： Nonlinear programming numerical implementation sequential quadratic programming method test results

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