The recent advent of miniature single gimbal control moment gyroscopes has spawned interest in variable-speed versions for combined energy storage and attitude control systems on small satellites. Although much has be...
详细信息
The recent advent of miniature single gimbal control moment gyroscopes has spawned interest in variable-speed versions for combined energy storage and attitude control systems on small satellites. Although much has been studied on the theory behind such a system, little has been done in optimally sizing these actuators for small satellite applications. This paper investigates optimally sizing these actuators for a practical space mission. Given a set of small satellite agility and energy storage requirements, the design is cast as a constrained nonlinear programming problem using a performance index constructed from subsystem design margins and solved using a reduced-order, gradient-based solver software code. By iterating this process for different input conditions and technologies, several design points were created, then scored using a weighted scoring function, and evaluated. The resulting method permits an efficient, structured approach to designing an optimally sized combined energy storage and attitude control system while enabling alternative technology comparisons.
A method, called the (I.) ABS-MPVT algorithm, for solving a system comprising linear equations and linear inequalities is presented. This method is characterized by solving the system of linear equations first via the...
详细信息
A method, called the (I.) ABS-MPVT algorithm, for solving a system comprising linear equations and linear inequalities is presented. This method is characterized by solving the system of linear equations first via the ABS algorithms and then solving an unconstrained minimization obtained by substituting the ABS general form of solutions into the system of linear inequalities. For the unconstrained minimization problem it can be solved by a (modified) parallel algorithm. The convergence of this method is also given. (C) 2007 Elsevier Ltd. All rights reserved.
This article proposes a new approach to solve the optimal reactive dispatch problem, based on Newton approach and the primal-dual logarithmic barrier method. A Lagrangian function is associated with the modified probl...
详细信息
This article proposes a new approach to solve the optimal reactive dispatch problem, based on Newton approach and the primal-dual logarithmic barrier method. A Lagrangian function is associated with the modified problem. The first-order necessary conditions for optimality are fulfilled by Newton's method and by updating the penalty, and barrier terms. The proposed approach does not require the set of binding constraints to be identified and can be utilized from an infeasible starting point. The effectiveness of the proposed approach has been examined by solving the Brazilian 53-bus and 662-bus systems.
Convergence and solution time are important considerations in process system optimization. Another nontrivial task is the definition of termination criteria. However, setting the convergence tolerance is difficult and...
详细信息
Convergence and solution time are important considerations in process system optimization. Another nontrivial task is the definition of termination criteria. However, setting the convergence tolerance is difficult and bewildering for users. Observed behaviors of algorithms when solving many optimization problems include tardiness in deciding convergence or failure of the optimization, and incapability of giving approximate solutions as they fail to converge. Here, we propose convergence depth control (CDC) for process system optimization. It is designed to take advantage of the achievement estimation of the optimization process to discover the proper time to terminate the optimization algorithm. Criteria based on CDC prefer to provide an approximate solution with acceptable optimality. Achievability and rationality of the criteria have been analyzed. To demonstrate the effectiveness of this method, we apply the Reduced-Hessian Successive Quadratic programming (RSQP) algorithm with convergence depth control and with traditional convergence criteria, respectively, to problems from the CUTE test set, the distillation sequence in ethylene production, and catalyst mixing problem in COPS collection. Numerical results of the comparison show significant advantages of convergence depth control.
This paper proposes several globally convergent geometric optimization algorithms on Riemannian manifolds, which extend some existing geometric optimization techniques. Since any set of smooth constraints in the Eucli...
详细信息
This paper proposes several globally convergent geometric optimization algorithms on Riemannian manifolds, which extend some existing geometric optimization techniques. Since any set of smooth constraints in the Euclidean space R-n (corresponding to constrained optimization) and the R-n space itself (corresponding to unconstrained optimization) are both special Riemannian manifolds, and since these algorithms are developed on general Riemannian manifolds, the techniques discussed in this paper provide a uniform framework for constrained and unconstrained optimization problems. Unlike some earlier works, the new algorithms have less restrictions in both convergence results and in practice. For example, global minimization in the one-dimensional search is not required. All the algorithms addressed in this paper are globally convergent. For some special Riemannian manifold other than R-n, the new algorithms are very efficient. Convergence rates are obtained. Applications are discussed.
This work deals with the optimal synthesis of groundwater remediation networks for the valorization of anionic pollutants by means of emulsion pertraction technology using hollow fiber modules (HFMs). Superstructures ...
详细信息
This work deals with the optimal synthesis of groundwater remediation networks for the valorization of anionic pollutants by means of emulsion pertraction technology using hollow fiber modules (HFMs). Superstructures that incorporate all possible design alternatives are proposed. The aim of this work is to obtain a minimum cost groundwater remediation network that allows treatment of groundwater to required levels and, also, a contaminant rich solution that can be used for further processing. The optimization of the superstructure is initially formulated as a nonconvex nonlinear programming (NLP) problem. This rigorous NLP model is simplified using some assumptions to get a simplified model which is globally optimized using a Lagrangean decomposition algorithm. This globally optimal solution is used as an initialization point for optimizing the rigorous NLP problem. Three cases involving different numbers of HFMs are studied to determine a cost optimized network with an optimal number of modules.
CANDU fuel management can be optimized for efficient reactor operation and reduced fueling costs. The quasi-linear programming approach developed in the OPTEX code for CANDU fuel management optimization has been imple...
详细信息
CANDU fuel management can be optimized for efficient reactor operation and reduced fueling costs. The quasi-linear programming approach developed in the OPTEX code for CANDU fuel management optimization has been implemented in the multipurpose multigroup diffusion code DONJON. With new reactor designs and requirements for advanced reactors, alternative gradient methods are presented and tested to address more complex CANDU fuel management problems. (c) 2006 Elsevier Ltd. All rights reserved.
An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algori...
详细信息
An optimisation technique to solve transmission network expansion planning problem, using the AC model, is presented. This is a very complex mixed integer nonlinear programming problem. A constructive heuristic algorithm aimed at obtaining an excellent quality solution for this problem is presented. An interior point method is employed to solve nonlinear programming problems during the solution steps of the algorithm. Results of the tests, carried out with three electrical energy systems, show the capabilities of the method and also the viability of using the AC model to solve the problem.
In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account th...
详细信息
In liberalized electricity markets, generation companies bid their hourly generation in order to maximize their profit. The optimization of the generation bids over a short-term weekly period must take into account the action of the competing generation companies and the market-price formation rules and must be coordinated with long-term planning results. This paper presents a three stage optimization process with a data analysis and parameter calculation, a linearized unit commitment, and a nonlinear generation scheduling refinement. Although the procedure has been developed from the experience with the Spanish power market, with minor adaptations it is also applicable to any generation company participating in a competitive market system. (C) 2006 Elsevier Ltd. All rights reserved.
The main goal of this study is to investigate a minimal energy rest-to-rest maneuvering control problem with open final time of a rigid spacecraft actuated by three orthogonal momentum wheels. Different from conventio...
详细信息
The main goal of this study is to investigate a minimal energy rest-to-rest maneuvering control problem with open final time of a rigid spacecraft actuated by three orthogonal momentum wheels. Different from conventional shooting methods, this control problem is formulated and solved as a constrained nonlinear programming (NLP) one by utilizing an iterative procedure. In this novel method, the count of control steps is fixed initially and the sampling period is treated as a variable in the optimization process. An approach to find the initial feasible solutions of the NLP problem is also proposed. Since initial feasible solutions can be found easily, the optimization process of the NLP problem can be started from different points to find the minimal energy rest-to-rest maneuver of the rigid spacecraft between two attitudes. To show the feasibility of the proposed method, simulation results are included for illustration. (C) 2007 The Franklin Institute. Published by Elsevier Ltd. All rights reserved.
暂无评论