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Multi-Objective Optimization of Perturbed Impulsive Rendezvous Trajectories Using Physical programming

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2008年第6期31卷 1829-1832页

作者： Luo, Ya-zhong Tang, Guo-jin Parks, Geoff Natl Univ Def Technol Coll Aerosp & Mat Engn Changsha 410073 Hunan Peoples R China Univ Cambridge Dept Engn Engn Design Ctr Cambridge CB2 1PZ England

Recently, it has been shown that taking the total velocity characteristic, the time of flight, and the trajectory safety into consideration and constructing a multi-objective optimization problem is an attractive and realistic proposition for rendezvous trajectory design. Luo et al. [1] formulated the multi-objective linearized rendezvous optimization problem and solved it through the multi-objective genetic algorithm NSGA-II. It was shown that the tradeoffs between time of flight, propellant cost, and trajectory safety are quickly established using NSGA-II. In recognition of the drawbacks associated with linearized rendezvous equations, this study was expanded to a nonlinear two-body rendezvous by using NSGA-II and a Lambert algorithm. The nonlinear two-body multi-objective model is more accurate and suitable for more problems in comparison with linearized rendezvous models, which are limited to circular and near-rendezvous. However, the two-body model still does not take into account trajectory perturbations, such as nonspherical perturbations and atmospheric drag, which exist in real operational missions. Thus, it is desirable to be able to obtain Pareto-optimal solutions for perturbed rendezvous trajectories.

关键词： sequential quadratic programming Propellant Spacecraft Trajectory Optimization Multi Objective Genetic Algorithm Annealing Lambert Algorithm Multi Objective Evolutionary Algorithms Pareto Optimality Perigee Stochastic Optimization

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A feasible trust-region sequential quadratic programming algorithm

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SIAM JOURNAL ON OPTIMIZATION 2004年第4期14卷 1074-1105页

作者： Wright, SJ Tenny, MJ Univ Wisconsin Dept Comp Sci Madison WI 53706 USA Univ Wisconsin Dept Chem Engn Madison WI 53706 USA

An algorithm for smooth nonlinear constrained optimization problems is described, in which a sequence of feasible iterates is generated by solving a trust-region sequential quadratic programming (SQP) subproblem at each iteration and by perturbing the resulting step to retain feasibility of each iterate. By retaining feasibility, the algorithm avoids several complications of other trust-region SQP approaches: the objective function can be used as a merit function, and the SQP subproblems are feasible for all choices of the trust-region radius. Global convergence properties are analyzed under various assumptions on the approximate Hessian. Under additional assumptions, superlinear convergence to points satisfying second-order sufficient conditions is proved.

关键词： nonlinear constrained optimization feasible algorithm sequential quadratic programming trust-region algorithms

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Nonlinear model predictive control via feasibility-perturbed sequential quadratic programming

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2004年第1期28卷 87-121页

作者： Tenny, MJ Wright, SJ Rawlings, JB Univ Wisconsin Dept Chem Engn Madison WI 53706 USA Univ Wisconsin Dept Comp Sci Madison WI 53706 USA

Model predictive control requires the solution of a sequence of continuous optimization problems that are nonlinear if a nonlinear model is used for the plant. We describe briefly a trust-region feasibility-perturbed sequential quadratic programming algorithm ( developed in a companion report), then discuss its adaptation to the problems arising in nonlinear model predictive control. Computational experience with several representative sample problems is described, demonstrating the effectiveness of the proposed approach.

关键词： model predictive control nonlinear programming sequential quadratic programming

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A Method for Evaluation of Coning Error Based on Adaptive Cone

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1st International Conference Intelligent Robotics and Applications

作者： Liu, Baoqing Dong, Huimin Dalian Univ Technol Sch Mech Engn Dalian 116024 Peoples R China

ISBN: (纸本)9783540885160

An approach to the coning error evaluation is presented in this paper. Firstly the initial point is calculated based on semi-cone angle and fitting cone axis obtained from fitting circle. Then, this paper puts forward a concise and visual model based on adaptive cone and proposes a solution of coning error base on sequential quadratic programming. Finally, the result of calculation based on many examples indicates that the initial point improves the evaluation of coning error.

关键词： sequential quadratic programming adaptive saddle point programming initial point

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Non-Linear Multiobjective Optimization for Control of Hydropower Plants Network

Non-Linear Multiobjective Optimization for Control of Hydrop...

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IEEE/ASME International Conference on Advanced Intelligent Mechatronics

作者： Moosavian, S. Ali A. Ghafari, A. Salimi, A. Abdi, N. KN Toosi Univ Technol Dept Mech Engn ARAS Lab Tehran Iran

ISBN: (纸本)9781424424948

In this paper, a non-linear multiobjective optimization model is developed to obtain optimal annual scheduling for control of power generation in serial or parallel hydropower plants. Weighted-sum method is used to convert multiobjective optimization to single objective problem. Then, sequential quadratic programming (SQP) is used, based on using Newton's method and Kune-Tucker conditions, to solve optimization problem. Maximization of power generation benefits and minimization of specific water consumption are assumed as objective functions. In this study, stochastic flows from external sources that enter to each reservoir (like rivers and rain) are assumed based on some scenarios for dry, median, and wet years. These various dry, median and wet water inflow scenarios are generated from the gathered fifty-year historical inflow measurements. Besides, turbine power generation is obtained from hill diagrams. The case study refers to hydropower plants network in Karoon River Basin in southern Iran. The corresponding optimization model has 240 variables and 660 constraints and MATLAB software is used to develop the model. Solving such non-linear multiobjective optimization model, annual rule curves that show optimal operation for reservoirs and total yearly energy production are presented for control of the cascaded units.

关键词： Network of hydropower plant Optimal annual scheduling Multiobjective optimization Weighted sum method sequential quadratic programming

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A Suboptimal Control Strategy for the Start-up of the Open Plate Reactor

A Suboptimal Control Strategy for the Start-up of the Open P...

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10th International Conference on Control, Automation, Robotics and Vision

作者： Kaya, Sener A. Attia, S. A. Raisch, J. Dalarna Univ Dept Elect Engn Borlange Sweden Tech Univ Berlin Control Syst Grp Berlin Germany

ISBN: (纸本)9781424422869

In this paper the application of Nonlinear Model Predictive Control (NMPC) to a chemical reactor, namely the Open Plate Reactor(OPR), is considered. A control strategy which allows a safe start-up operation of the reactor and provides an easy handling of system restrictions and nonlinearities, is proposed. An efficient open-loop parameterization of the control signals is used to further reduce the size of the optimization variables. It is shown that the NMPC algorithm developed gives satisfactory operation and the reduced open loop parameterization results in a sufficiently rich closed loop behavior.

关键词： chemical reactor heat exchange plate reactor start-up control nonlinear model predictive control efficient open loop parameterization sequential quadratic programming

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Jets in crossflow mixing analysis using computational fluid dynamics and mathematical optimization

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JOURNAL OF PROPULSION AND POWER 2007年第3期23卷 618-628页

作者： Morris, R. M. Snyman, J. A. Meyer, J. P. Univ Pretoria ZA-0002 Pretoria South Africa Univ Pretoria Dept Mech & Aeronaut Engn ZA-0002 Pretoria South Africa

Computational fluid dynamics and mathematical optimization were used to investigate the mixing effectiveness of jets in crossflow. A numerical model was developed, validated, and calibrated against experimental measurements of a temperature distribution at different cross-sectional planes downstream of an orifice injection plane. Good agreement was obtained when the ratio between momentum and species diffusivities was varied according to the jetto-mainstream momentum flux ratio. Numerical optimization of various double-sided jet configurations followed, using a parametric approach. The results obtained showed that changes in orifice size and spacing at a constant orifice-to-mainstream area ratio and momentum flux ratio have a significant influence on mixing effectiveness. The optimum configuration compared favorably with an empirically defined relationship between orifice spacing and momentum flux ratio. Mathematical optimization was then combined with numerical methods to predict the optimum orifice configuration. The results showed the feasibility of using a gradient-based approximation method to allow, for a given set of parameters, the systematic adjustment of design variables to achieve improvement in performance.

关键词： Mathematical Optimization Large Eddy Simulation Temperature Distribution Numerical Modeling Schmidt Numbers Flow Conditions Annular Combustor sequential quadratic programming Reynolds Averaged Navier Stokes Aspect Ratio

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Sensitivity analysis and optimization using energy finite element and boundary element methods

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AIAA JOURNAL 2007年第6期45卷 1187-1198页

作者： Dong, Jun Choi, Kyung K. Vlahopoulos, Nickolas Wang, Aimin Zhang, Weiguo Univ Iowa Dept Mech & Ind Engn Iowa City IA 52242 USA Univ Michigan Dept Naval Architecture & Marine Engn Ann Arbor MI 48109 USA

This paper presents a continuum-based design sensitivity analysis and optimization of high-frequency radiation problems using the energy finite element method and energy boundary element method. The noise radiated from the vibrating structure at a high-frequency range is obtained through a sequential procedure. The structural energy finite element method calculates structural energy distribution, which is then used as the boundary condition for the energy boundary element method to calculate the energy density at a far-field observation point. For design sensitivity analysis, the direct differentiation method calculates the sensitivity of the exterior noise through the sensitivity of the structural energy density obtained from the energy finite element method. The adjoint variable method calculates the adjoint load from an acoustic energy boundary element method reanalysis, and the adjoint response is obtained from a structural energy finite element method reanalysis. The sensitivity information is obtained by carrying out numerical integration only on the structural finite element part. The proposed design sensitivity analysis approach has been applied in the design of automotive and naval structures to search for the best material layout to achieve the lowest noise level at high frequency.

关键词： Sensitivity Analysis Boundary Element Method Finite Element Approximation Energy Distribution Statistical Energy Analysis Mechanical Properties Material Properties Hysteresis Noise, Vibration, and Harshness sequential quadratic programming

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Large margin semi-supervised learning

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JOURNAL OF MACHINE LEARNING RESEARCH 2007年第8期8卷 1867-1891页

作者： Wang, Junhui Shen, Xiaotong Univ Minnesota Sch Stat Minneapolis MN 55455 USA

In classification, semi-supervised learning occurs when a large amount of unlabeled data is available with only a small number of labeled data. In such a situation, how to enhance predictability of classification through unlabeled data is the focus. In this article, we introduce a novel large margin semi-supervised learning methodology, using grouping information from unlabeled data, together with the concept of margins, in a form of regularization controlling the interplay between labeled and unlabeled data. Based on this methodology, we develop two specific machines involving support vector machines and psi-learning, denoted as SSVM and SPSI, through difference convex programming. In addition, we estimate the generalization error using both labeled and unlabeled data, for tuning regularizers. Finally, our theoretical and numerical analyses indicate that the proposed methodology achieves the desired objective of delivering high performance in generalization, particularly against some strong performers.

关键词： generalization grouping sequential quadratic programming support vectors

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A modified SQP-filter method and its global convergence

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APPLIED MATHEMATICS AND COMPUTATION 2007年第1期194卷 92-101页

作者： Su, Ke Che, Jianren Tongji Univ Dept Surveying & Geoinformat Shanghai 200092 Peoples R China Tongji Univ Dept Math Shanghai 200092 Peoples R China

For current sequential programming (SQP) type algorithms, there exist two problems. One is that there are many quadratic programming subproblems are needed to be solved per iteration, the other is that the search direction may be unbounded and caused the sequence to be divergent. In this paper, we presented a modified SQP-filter method based on the modified quadratic subproblem proposed in Zhou [G. L. Zhou, A modified SQP method and its global convergence, J. Global Optim. 11 (1997) 193-205]. This method has no demand on the initial point, and need not using a penalty parameter, which could be problematic to obtain. What is more, the subproblem is feasible at each iterate point. Under some conditions, the global convergence property is obtained. (c) 2007 Elsevier Inc. All rights reserved.

关键词： constrained optimization KKT point sequential quadratic programming global convergence

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