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Optimization of Impulsive Trajectories from Circular Orbit to an Excess Velocity Vector

JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第1期35卷 234-244页

作者： Jones, D. R. Ocampo, C. Univ Texas Austin Dept Aerosp Engn & Engn Mech WR Woolrich Labs Austin TX 78712 USA

Feasible transfer trajectories are constructed to serve as initial guesses for determining constrained optimal impulsive escape trajectories, from a circular orbit to a target hyperbolic excess velocity vector. The proximity of these feasible solutions to their corresponding optima are quantified. The objective of this work is to improve the feasible solutions, thereby enabling general anytime escape trajectories to be targeted that result in substantially reduced fuel expenditure. The procedure is currently restricted to one- and three-impulse escape trajectories from a circular parking orbit. Two separate three-impulse methods are presented, each specific to whether the time of flight is free or fixed. Numerical results, obtained using nonlinear programming algorithms, are presented to validate the robustness of the method. Analysis and results are nondimensional, and therefore are applicable to departures from a circular orbit about any celestial body.

关键词： Trans Earth Injection Parking Orbit Nonlinear programming Periapsis sequential quadratic programming Kepler's Equation Earth Trajectory Optimization Numerical Integration Space Exploration

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A hybrid FCASO-SQP method for solving the economic dispatch problems with valve-point effects

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ENERGY 2012年第1期38卷 346-353页

作者： Cai, Jiejin Li, Qiong Li, Lixiang Peng, Haipeng Yang, Yixian Sun Yat Sen Univ Sch Phys & Engn Guangzhou 510275 Guangdong Peoples R China Sun Yat Sen Univ Sino French Inst Nucl Engn & Technol Guangzhou 510275 Guangdong Peoples R China S China Univ Technol State Key Lab Subtrop Bldg Sci Guangzhou 510640 Guangdong Peoples R China Beijing Univ Posts & Telecommun Informat Secur Ctr Beijing 100876 Peoples R China

In this paper, a hybrid method integrating the fuzzy adaptive chaotic ant swarm optimization (FCASO) algorithm and the sequential quadratic programming (SQP) techniques, named FCASO-SQP method, is presented for solving the economic dispatch (ED) problems in power systems. The FCASO algorithm is the main optimizer in the hybrid method and the SQP technique is used to fine tune its results to improve the solution. The FCASO algorithm introduces a fuzzy system to dynamically tune the characteristic parameters psi(d) and r(i) of chaotic ant swarm optimization (CASO). The proposed method was applied to three different cases of power systems with three units, thirteen units and forty units, and the simulation results demonstrate its applicability and effectiveness to solve the ED problems with valve-point effect. (C) 2011 Elsevier Ltd. All rights reserved.

关键词： Economic dispatch Fuzzy adaptive chaotic ant swarm optimization sequential quadratic programming Evolutionary algorithm Power system

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Recourse-based stochastic nonlinear programming: properties and Benders-SQP algorithms

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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2012年第1期51卷 77-123页

作者： Kulkarni, Ankur A. Shanbhag, Uday V. Univ Illinois Dept Ind & Enterprise Syst Engn Urbana IL 61801 USA

In this paper, we study recourse-based stochastic nonlinear programs and make two sets of contributions. The first set assumes general probability spaces and provides a deeper understanding of feasibility and recourse in stochastic nonlinear programs. A sufficient condition, for equality between the sets of feasible first-stage decisions arising from two different interpretations of almost sure feasibility, is provided. This condition is an extension to nonlinear settings of the "W-condition," first suggested by Walkup and Wets (SIAM J. Appl. Math. 15:1299-1314, 1967). Notions of complete and relatively-complete recourse for nonlinear stochastic programs are defined and simple sufficient conditions for these to hold are given. Implications of these results on the L-shaped method are discussed. Our second set of contributions lies in the construction of a scalable, superlinearly convergent method for solving this class of problems, under the setting of a finite sample-space. We present a novel hybrid algorithm that combines sequential quadratic programming (SQP) and Benders decomposition. In this framework, the resulting quadratic programming approximations while arbitrarily large, are observed to be two-period stochastic quadratic programs (QPs) and are solved through two variants of Benders decomposition. The first is based on an inexact-cut L-shaped method for stochastic quadratic programming while the second is a quadratic extension to a trust-region method suggested by Linderoth and Wright (Comput. Optim. Appl. 24:207-250, 2003). Obtaining Lagrange multiplier estimates in this framework poses a unique challenge and are shown to be cheaply obtainable through the solution of a single low-dimensional QP. Globalization of the method is achieved through a parallelizable linesearch procedure. Finally, the efficiency and scalability of the algorithm are demonstrated on a set of stochastic nonlinear programming test problems.

关键词： Stochastic programming Nonlinear programming Almost-sure feasibility Recourse W-condition sequential quadratic programming Benders' decomposition

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Placement and operation strategy of FACTS devices using optimal continuous power flow

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SCIENTIA IRANICA 2012年第6期19卷 1683-1690页

作者： Aghaei, J. Gitizadeh, M. Kaji, M. Shiraz Univ Technol Dept Elect & Elect Engn Shiraz Iran

In this paper, an effective method is presented to determine the security margin against voltage collapse, and improve it by means of FACTS devices in the optimal continuous power flow framework. The primary methods for determining the system's critical states of voltage collapse points are based on the convergence of the Newton-Raphson method in various iterations. Unlike these methods, in this investigation, a method based on sequential quadratic programming is proposed to overcome the divergence of the problem near the critical states, and also to incorporate operation and control constraints through optimal continuous power flow. Furthermore, two FACTS devices, the Thyristor-Controlled Series Capacitor (TCSC) and the Static VAR Compensator (SVC), are mathematically represented and employed in the optimization process to improve the security margin. The proposed method is implemented on a practical power network to investigate the efficacy of the method. (C) 2012 Sharif University of Technology. Production and hosting by Elsevier B.V. All rights reserved.

关键词： Voltage collapse sequential quadratic programming FACTS devices Voltage security margin Optimal continuous power flow

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Microgrid management with a quick response optimization algorithm for active power dispatch

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INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS 2012年第1期43卷 465-473页

作者： Alvarez, Eduardo Campos, Antonio M. Arboleya, Pablo Gutierrez, Antonio J. Fdn CTIC Gijon 33203 Asturias Spain Univ Oviedo Dept Elect Gijon 33203 Asturias Spain Univ Oviedo Dept Energy Oviedo 33004 Asturias Spain

A fast response algorithm has been developed for active-power dispatch to microsources in a distributed generation microgrid. It is capable of adjusting microgrid generation to demand on-line in grid-connected-mode. The algorithm performs an optimization of fuel consumption and emissions costs functions, of microsources using a heuristic approach. It and has been tested to solve different power dispatch cost optimization problems. The tests realized show a maximum execution time of about 1 ms, which is several orders of magnitude faster than the results obtained with other state-of-the-art optimization methods currently employed in these applications. It has also shown better performance in terms of global cost and microsources stability. The fast response implies a substantial reduction of the computational resources needed, allowing the use of a low-cost programmable logic controller or microcontroller for microsources active power dispatching. Thus, the infrastructure requirements and new investments are reduced and the penetration of microgrids based on renewable energies is improved. (C) 2012 Elsevier Ltd. All rights reserved.

关键词： Microgrids Microsource Distributed generation Power dispatch Cost function sequential quadratic programming

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Trajectory Design Combining Invariant Manifolds with Discrete Mechanics and Optimal Control

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第5期35卷 1507-1525页

作者： Moore, Ashley Ober-Bloebaum, Sina Marsden, Jerrold E. CALTECH Pasadena CA 91125 USA Univ Paderborn D-33098 Paderborn Germany

A mission design technique that combines invariant manifold techniques, discrete mechanics, and optimal control produces locally optimal low-energy trajectories. Previously, invariant manifolds of the planar circular restricted three-body problem have been used to design trajectories with relatively small midcourse change in velocity Delta V . A different method of using invariant manifolds is explored to design trajectories directly in the four-body problem. Then, using the local optimal control method DMOC (Discrete Mechanics and Optimal Control), it is possible to reduce the midcourse Delta V to zero. The influence of different boundary conditions on the optimal trajectory is also demonstrated. These methods are tested on a trajectory that begins in Earth orbit and ends in ballistic capture at the moon. Impulsive DMOC trajectories require up to 19% less Delta V than trajectories using a Hohmann transfer. When applied to low-thrust trajectories, DMOC produces an improvement of up to 59% in the mass fraction and 22% in travel time when compared with results from shooting methods.

关键词： Bang Bang Control Earth Moon Elliptical Orbit Low Energy Trajectory Earth Centered Inertial Lagrange Points Periapsis sequential quadratic programming Lagrange D'Alembert Principle

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Automated Mission Planning via Evolutionary Algorithms

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第6期35卷 1878-1887页

作者： Englander, Jacob A. Conway, Bruce A. Williams, Trevor Univ Illinois Dept Aerosp Engn Urbana IL 61801 USA NASA Goddard Space Flight Ctr Nav & Mission Design Branch Greenbelt MD 20770 USA

Many space mission planning problems may be formulated as hybrid optimal control problems, that is, problems that include both real-valued variables and categorical variables. In orbital mechanics problems, the categorical variables will typically specify the sequence of events that qualitatively describe the trajectory or mission, and the real-valued variables will represent the launch date, flight times between planets, magnitudes and directions of rocket burns, flyby altitudes, etc. A current practice is to preprune the categorical state space to limit the number of possible missions to a number whose cost may reasonably be evaluated. Of course, this risks pruning away the optimal solution. The method to be developed here avoids the need for prepruning by incorporating a new solution approach. The new approach uses nested loops: an outer-loop problem solver that handles the finite dynamics and finds a solution sequence in terms of the categorical variables, and an inner-loop problem solver that finds the optimal trajectory for a given sequence A binary genetic algorithm is used to solve the outer-loop problem, and a cooperative algorithm based on particle swarm optimization and differential evolution is used to solve the inner-loop problem. The hybrid optimal control solver is successfully demonstrated here by reproducing the Galileo and Cassini missions.

关键词： Particle Swarm Optimization Gas Giant Interplanetary Mission Genetic Algorithm Gravity Assist Maneuver Rockets Trajectory Optimization Deep Space Maneuver Interplanetary Trajectories sequential quadratic programming

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Optimization of Monopod Offshore Tower under Uncertainties with Gradient-Based and Gradient-Free Optimization Algorithms

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ADVANCES IN STRUCTURAL ENGINEERING 2012年第12期15卷 2021-2032页

作者： Togan, Vedat Karadeniz Tech Univ Dept Civil Engn Trabzon Turkey

In the RBDO applications which include a reliability analysis and an optimization algorithm, sequential quadratic programming (SQP) is frequently used for the optimization. In this work, in addition to SQP, some heuristic algorithms such as Simulating Annealing (SA), Genetic Algorithms (GA) and Harmony Search (HS) are employed as optimization methods to demonstrate the performance, accuracy and efficiency of the corresponding methods in the RBDO process. The probabilistic constraints are evaluated by using Reliability Index Approach (RIA). The optimum design of a monopod offshore tower is presented as a numerical example to show the applicability of the proposed algorithm. Graphical and tabular forms are proposed to compare the efficiency of the optimization methods used in the Reliability Based Design Optimization (RBDO) process. As a result, heuristic algorithms exhibit good performance although they call many function evaluations including constraints and objective functions.

关键词： reliability-based optimization sequential quadratic programming heuristic algorithms offshore towers

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Optimization of an Occulter-Based Extrasolar-Planet-Imaging Mission

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JOURNAL OF GUIDANCE CONTROL AND DYNAMICS 2012年第1期35卷 172-185页

作者： Kolemen, Egemen Kasdin, N. Jeremy Princeton Plasma Phys Lab Princeton NJ 08543 USA Princeton Univ Mech & Aerosp Dept Princeton NJ 08544 USA

A novel approach to extrasolar-planet imaging uses a pair of satellites: a telescope and an occulter, where the latter is placed in the line of sight between the telescope and the star system to be imaged in order to enhance the telescope's imaging capability. The optimal configuration of this satellite formation around sun-Earth L2 halo orbits is studied. Trajectory optimization of the occulter motion between imaging sessions of different stars is performed using a range of different criteria and methods. Thus, the global optimization problem is transformed into a time-dependent traveling salesman problem. The time-dependent traveling salesman problem is augmented with various constraints that arrive from the mission, and this problem is solved by employing simulated annealing and branching algorithms. For a concrete understanding of the feasibility of the mission, the performance of an example spacecraft, the Small Missions for Advanced Research in Technology (SMART-1), is analyzed.

关键词： Earth Telescopes Small Missions for Advanced Research in Technology Trajectory Optimization Annealing Halo Orbit sequential quadratic programming Planetary Systems Fuel Consumption Terrestrial Planet Finder

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De Saint-Venant equations-based model assessment in model predictive control of open channel flow

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ADVANCES IN WATER RESOURCES 2012年第Dec.期49卷 37-45页

作者： Xu, M. Negenborn, R. R. van Overloop, P. J. van de Giesen, N. C. Delft Univ Technol Fac Civil Engn & Geosci Sect Water Resources Management NL-2628 CN Delft Netherlands Delft Univ Technol Fac Mech Maritime & Mat Engn Sect Marine & Transport Technol NL-2628 CD Delft Netherlands

Model predictive control (MPC) is a model-based control technique that uses an optimization algorithm to generate optimal control actions. Based on the model used in optimization, MPC approaches can be categorized as linear or nonlinear. Both classes have advantages and disadvantages in terms of control accuracy and computational time. A typical linear model in open channel water management is the Integrator Delay (ID) model, while a nonlinear model usually refers to the Saint-Venant equations. In earlier work, we proposed the use of linearized Saint-Venant equations for MPC, where the model is formulated in a linear time-varying format and time-varying parameters are estimated outside of the optimization. quadratic programming (QP) is used to solve the optimization problem. However, the control accuracy of such an MPC scheme is not clear. In this paper, we compare this approach with an MPC scheme that uses sequential quadratic programming (SQP) to solve the optimization problem. Because the estimation of the time-varying parameters is integrated in the optimization in SQP, the solutions from SQP-based MPC are expected to be superior to the solutions of QP-based approach. However, SQP can be computationally expensive. A simulation experiment illustrates that the QP-based MPC approach using a linearized Saint-Venant model has an accurate approximation of the control performance of SQP. Crown Copyright (C) 2012 Published by Elsevier Ltd. All rights reserved.

关键词： Model predictive control quadratic programming Open channel flow sequential quadratic programming Saint-Venant equations

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