A strategy for the control of the librations of a tethered satellite systemin elliptic orbits using tether length control, which drives the system to controlled periodiclibration trajectories, is suggested. There is a...
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A strategy for the control of the librations of a tethered satellite systemin elliptic orbits using tether length control, which drives the system to controlled periodiclibration trajectories, is suggested. There is a range of eccentricities up to about 0.4453 forwhich no length variations are needed for the system to follow the periodic trajectory. Above thiseccentricity, it is necessary to vary the length of tether to maintain a periodic trajectory. Themethod for finding these trajectories to minimize the control input utilizes a collocation ***-loop stability is provided by a linear feedback control law, whose feedback gains are alsoperiodic. Consequently, Floquet theory demonstrates the stability of the closed-loop system.
This paper discusses a numerical approach to the design of skid landing gears, based on an optimization procedure linked to a multibody explicit c ode. The modeling technique has been validated with the experimental r...
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This paper discusses a numerical approach to the design of skid landing gears, based on an optimization procedure linked to a multibody explicit c ode. The modeling technique has been validated with the experimental results of a drop test considering the overall landing performances as well as the levels of bending strains developed along the cross members. According to the presented numerical-experimental correlations, the numerical analyses obtained appreciable results at a very low computational cost. The technique has been applied to generate a parameterized model of a skid landing-gear, suitable to be adopted in an automatic optimization procedure. To adequately formulate the optimization process, the basic aspects involved in the design of skid landing gears have been reviewed, and two optimization procedures have been developed. These formulations have been directed, respectively, to optimize the landing performances and to obtain an optimal plastic strain distribution along the cross members axes. The optimization search applied to different design tasks shows that the developed numerical tools can identify well-sized landing-gear configurations that satisfy all of the imposed constraints on the landing performances and are characterized by uniform strain distributions along the cross members, thus maximizing the strength and the durability of the landing system.
Calmness of multifunctions is a well-studied concept of generalized continuity in which single-valued selections from the image sets of the multifunction exhibit a restricted type of local Lipschitz continuity where t...
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Calmness of multifunctions is a well-studied concept of generalized continuity in which single-valued selections from the image sets of the multifunction exhibit a restricted type of local Lipschitz continuity where the base point is fixed as one point of comparison. Generalized continuity properties of multifunctions like calmness can be applied to convergence analysis when the multifunction appropriately represents the iterates generated by some algorithm. Since it involves an essentially linear relationship between input and output, calmness gives essentially linear convergence results when it is applied directly to convergence analysis. We introduce a new continuity concept called 'supercalmness' where arbitrarily small calmness constants can be obtained near the base point, which leads to essentially superlinear convergence results. We also explore partial supercalmness and use a well-known generalized derivative to characterize both when a multifunction is supercalm and when it is partially supercalm. To illustrate the value of such characterizations, we explore in detail a new example of a general primal sequential quadratic programming method for nonlinear programming and obtain verifiable conditions to ensure convergence at a superlinear rate.
Optimization is of vital importance when performing intensity modulated radiation therapy to treat cancer tumors. The optimization problem is typically large-scale with a nonlinear objective function and bounds on the...
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Optimization is of vital importance when performing intensity modulated radiation therapy to treat cancer tumors. The optimization problem is typically large-scale with a nonlinear objective function and bounds on the variables, and we solve it using a quasi-Newton sequential quadratic programming method. This study investigates the effect on the optimal solution, and hence treatment outcome, when solving an approximate optimization problem of lower dimension. Through a spectral decompostion, eigenvectors and eigenvalues of an approximation to the Hessian are computed. An approximate optimization problem of reduced dimension is formulated by introducing eigenvector weights as optimization parameters, where only eigenvectors corresponding to large eigenvalues are included. The approach is evaluated on a clinical prostate case. Compared to bixel weight optimization, eigenvector weight optimization with few parameters results in faster initial decline in the objective function, but with inferior final solution. Another approach, which combines eigenvector weights and bixel weights as variables, gives lower final objective values than what bixel weight optimization does. However, this advantage comes at the expense of the pre-computational time for the spectral decomposition.
The most important classes of Newton-type methods for solving constrained optimization problems are discussed. These are the sequential quadratic programming methods, active set methods, and semismooth Newton methods ...
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In order to improve the convergence and calculate optimal results reliably and accurately, a trust-region algorithm based on global sequential quadratic programming (SQP) Is presented for reactive power optimization. ...
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ISBN:
(纸本)9781424404926
In order to improve the convergence and calculate optimal results reliably and accurately, a trust-region algorithm based on global sequential quadratic programming (SQP) Is presented for reactive power optimization. This method combines global SQP with trust-region method. The method of decomposed inaccurate direction component is adopted to compute trust-region sub problem to guarantee feasible region of this sub problem is not null. The penalty parameter is effectively regulated in Merit Function to avoid the Marotos Effect. This example of the computation shows that this algorithm has global convergence and is fast, accurate and reliable.
Stoichiometric Network Theory is a constraints-based, optimization approach for quantitative analysis of the phenotypes of large-scale biochemical networks that avoids the use of detailed kinetics. This approach uses ...
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A novel low-thrust orbit transfer design method is presented which is based on the knowledge of optimal thrust direction and optimal location for changing each of the orbit elements and the concept of Lyapunov feed ba...
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ISBN:
(纸本)9787302139225
A novel low-thrust orbit transfer design method is presented which is based on the knowledge of optimal thrust direction and optimal location for changing each of the orbit elements and the concept of Lyapunov feed back control. In this method, a set of equinoctial elements is utilized to avoid the singularities in dynamical equation of classical orbit elements. A thruster switch law is derived by analyzing the effectivity of the changing of each orbit elements. The thrust will be cut-off if the effectivity is below a specified level. When on, the thrust is a constant. The two-body dynamics model is used in this method. The method needs few input parameters. By sequential quadratic programming (SQP), these parameters could be adjusted and performance index could be maximized. This method is a simple way to estimate key parameters of a low-thrust orbit transfer and could also give an accurate initial guesses for the future optimization.
Results for 2-D airfoil shape optimization in transonic regime are presented. Airfoil shapes are represented by nonuniform rational B-splines with appropriate regularity properties. A Navier-Stokes How solver is used ...
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Results for 2-D airfoil shape optimization in transonic regime are presented. Airfoil shapes are represented by nonuniform rational B-splines with appropriate regularity properties. A Navier-Stokes How solver is used to compute the flow field and to obtain aerodynamic coefficients. A design of experiment is conducted to select the most sensitive design variables among the nonuniform rational B-splines parameters to reduce their number in the final optimization process. Single-point and multipoint formulations of the optimization problem are proposed and compared. The nonuniform rational B-splines parameterization guarantees smooth optimized airfoils. The multipoint optimization formulation combined with the nonuniform rational B-splines parameterization leads to airfoils with good performance over a specified Mach range.
In the upper bound approach to limit analysis of slope stability based on the rigid finite element method, the search for the minimum factor of safety can be formulated as a non-linear programming problem with equalit...
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In the upper bound approach to limit analysis of slope stability based on the rigid finite element method, the search for the minimum factor of safety can be formulated as a non-linear programming problem with equality constraints only based on a yield criterion, a flow rule, boundary conditions, and an energy-work balance equation. Because of the non-linear property of the resulting optimization problems, a non-linear mathematical programming algorithm has to be employed. In this paper, the relations between the numbers of nodes, elements, interfaces, and subsequent unknowns and constraints in the approach have been derived. It can be shown that in the large-scale problems, the unknowns are subject to a highly sparse set of equality constraints. Because of the existence of non-linear equalities in the approach, this paper applies first time a special sequential quadratic programming (SQP) algorithm, feasible SQP (FSQP), to obtain solutions for such non-linear optimization problems. In FSQP algorithm, the non-linear equality constraints are turned into inequality constraints and the objective function is replaced by an exact penalty function which penalizes non-linear equality constraint violations only. Three numerical examples are presented to illustrate the potentialities and efficiencies of the FSQP algorithm in the slope stability analysis. Copyright (C) 2004 John Wiley Sons, Ltd.
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