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At least 37 records · Page 2
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Global, Multi-Objective Trajectory Optimization With Parametric Spreading

Mission design problems are often characterized by multiple, competing trajectory optimization objectives. Recent multi-objective trajectory optimization formulations enable generation of globally-optimal, Pareto solutions via a multi-objective genetic algorithm. A byproduct of these formulations is that clustering in design space can occur in evolving the population towards the Pareto front. This clustering can be a drawback, however, if parametric evaluations of design variables are desired. This effort addresses clustering by incorporating operators that encourage a uniform spread over specified design variables while maintaining Pareto front representation. The algorithm is demonstrated on a Neptune orbiter mission, and enhanced multidimensional visualization strategies are presented.

trajectory design↗
NASA NTRS2017

Performance Optimizing Multi-Objective Adaptive Control with Time-Varying Model Reference Modification

This paper presents a new adaptive control approach that involves a performance optimization objective. The problem is cast as a multi-objective optimal control. The control synthesis involves the design of a performance optimizing controller from a subset of control inputs. The effect of the performance optimizing controller is to introduce an uncertainty into the system that can degrade tracking of the reference model. An adaptive controller from the remaining control inputs is designed to reduce the effect of the uncertainty while maintaining a notion of performance optimization in the adaptive control system.

Adaptive Control↗
NASA NTRS1993

Integrated design of the CSI evolutionary structure: A verification of the design methodology

One of the main objectives of the Controls-Structures Interaction (CSI) program is to develop and evaluate integrated controls-structures design methodology for flexible space structures. Thus far, integrated design methodologies for a class of flexible spacecraft, which require fine attitude pointing and vibration suppression with no payload articulation, have been extensively investigated. Various integrated design optimization approaches, such as single-objective optimization, and multi-objective optimization, have been implemented with an array of different objectives and constraints involving performance and cost measures such as total mass, actuator mass, steady-state pointing performance, transient performance, control power, and many more. These studies have been performed using an integrated design software tool (CSI-DESIGN CODE) which is under development by the CSI-ADM team at the NASA Langley Research Center. To date, all of these studies, irrespective of the type of integrated optimization posed or objectives and constraints used, have indicated that integrated controls-structures design results in an overall spacecraft design which is considerably superior to designs obtained through a conventional sequential approach. Consequently, it is believed that validation of some of these results through fabrication and testing of a structure which is designed through an integrated design approach is warranted. The objective of this paper is to present and discuss the efforts that have been taken thus far for the validation of the integrated design methodology.

Maghami, Peiman G.↗
NASA NTRSDate not supplied

Time-Varying Reference Model Modification of Adaptive Control with Multi-Objective Performance Optimization

This paper presents an adaptive control approach that modifies a reference model in order to satisfy a multi-objective optimization of two performance signals: a linear signal and a quadratic signal. The time varying reference model modification is accomplished by the real-time solutions of the time-varying Riccati and Sylvester equations coupled with the least-squares parameter estimation of the sensitivities of the performance signals to be minimized. The effectiveness of the proposed method is to be demonstrated by a flight control application of maneuver load alleviation and drag minimization.

Adaptive Control↗
NASA NTRS2005

Multidisciplinary Multiobjective Optimal Design for Turbomachinery Using Evolutionary Algorithm

This report summarizes Dr. Lian s efforts toward developing a robust and efficient tool for multidisciplinary and multi-objective optimal design for turbomachinery using evolutionary algorithms. This work consisted of two stages. The first stage (from July 2003 to June 2004) Dr. Lian focused on building essential capabilities required for the project. More specifically, Dr. Lian worked on two subjects: an enhanced genetic algorithm (GA) and an integrated optimization system with a GA and a surrogate model. The second stage (from July 2004 to February 2005) Dr. Lian formulated aerodynamic optimization and structural optimization into a multi-objective optimization problem and performed multidisciplinary and multi-objective optimizations on a transonic compressor blade based on the proposed model. Dr. Lian s numerical results showed that the proposed approach can effectively reduce the blade weight and increase the stage pressure ratio in an efficient manner. In addition, the new design was structurally safer than the original design. Five conference papers and three journal papers were published on this topic by Dr. Lian.

Source record↗
NASA NTRS2004

Evolutionary computing for spacecraft power subsystem design search and optimization

Multi-objective optimization involves finding one or more optimal solutions when there is more than one conflicting objective. This means that a solution that is better in one objective compromises or trades-off, other objectives. Trade Studies are conducted by flight projects to create mission concepts with different trade-off solutions for mass, cost, performance and risk.

Hua, Hook↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed and in some cases the final destination. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very diserable. This work presents such as an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Optimization↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Low-Thrust Mission Design

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. In addition, a time-history of control variables must be chosen that defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on a hypothetical mission to the main asteroid belt.

Optimization↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design using Chemical Propulsion

Preliminary design of high‐thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys and the bodies at which those flybys are performed. For some missions, such as surveys of small bodies, the mission designer also contributes to target selection. In addition, real‐valued decision variables, such as launch epoch, flight times, maneuver and flyby epochs, and flyby altitudes must be chosen. There are often many thousands of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the impulsive mission design problem as a multi‐objective hybrid optimal control problem. The method is demonstrated on several real‐world problems. Two assumptions are frequently made to simplify the modeling of an interplanetary high‐thrust trajectory during the preliminary design phase. The first assumption is that because the available thrust is high, any maneuvers performed by the spacecraft can be modeled as discrete changes in velocity. This assumption removes the need to integrate the equations of motion governing the motion of a spacecraft under thrust and allows the change in velocity to be modeled as an impulse and the expenditure of propellant to be modeled using the time‐independent solution to Tsiolkovsky's rocket equation [1]. The second assumption is that the spacecraft moves primarily under the influence of the central body, i.e. the sun, and all other perturbing forces may be neglected in preliminary design. The path of the spacecraft may then be modeled as a series of conic sections. When a spacecraft performs a close approach to a planet, the central body switches from the sun to that planet and the trajectory is modeled as a hyperbola with respect to the planet. This is known as the method of patched conics. The impulsive and patched‐conic assumptions significantly simplify the preliminary design problem.

Optimization↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often many thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The methods is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

Trajectory Design↗
NASA NTRS2014

Multi-Objective Hybrid Optimal Control for Interplanetary Mission Planning

Preliminary design of low-thrust interplanetary missions is a highly complex process. The mission designer must choose discrete parameters such as the number of flybys, the bodies at which those flybys are performed, and in some cases the final destination. Because low-thrust trajectory design is tightly coupled with systems design, power and propulsion characteristics must be chosen as well. In addition, a time-history of control variables must be chosen which defines the trajectory. There are often may thousands, if not millions, of possible trajectories to be evaluated. The customer who commissions a trajectory design is not usually interested in a point solution, but rather the exploration of the trade space of trajectories between several different objective functions. This can be a very expensive process in terms of the number of human analyst hours required. An automated approach is therefore very desirable. This work presents such an approach by posing the mission design problem as a multi-objective hybrid optimal control problem. The method is demonstrated on hypothetical mission to the main asteroid belt and to Deimos.

Low Thrust↗
NASA NTRS2004

Genetic Algorithms Applied to Multi-Objective Aerodynamic Shape Optimization

A genetic algorithm approach suitable for solving multi-objective optimization problems is described and evaluated using a series of aerodynamic shape optimization problems. Several new features including two variations of a binning selection algorithm and a gene-space transformation procedure are included. The genetic algorithm is suitable for finding pareto optimal solutions in search spaces that are defined by any number of genes and that contain any number of local extrema. A new masking array capability is included allowing any gene or gene subset to be eliminated as decision variables from the design space. This allows determination of the effect of a single gene or gene subset on the pareto optimal solution. Results indicate that the genetic algorithm optimization approach is flexible in application and reliable. The binning selection algorithms generally provide pareto front quality enhancements and moderate convergence efficiency improvements for most of the problems solved.

Holst, Terry L.↗
NASA NTRS2015

Multi-Objective Hybrid Optimal Control for Multiple-Flyby Interplanetary Mission Design Using Chemical Propulsion

The customer (scientist or project manager) most often does not want just one point solution to the mission design problem Instead, an exploration of a multi-objective trade space is required. For a typical main-belt asteroid mission the customer might wish to see the trade-space of: Launch date vs. Flight time vs. Deliverable mass, while varying the destination asteroid, planetary flybys, launch year, etcetera. To address this question we use a multi-objective discrete outer-loop which defines many single objective real-valued inner-loop problems.

Design↗
NASA NTRS2005

Surrogate-based Analysis and Optimization

A major challenge to the successful full-scale development of modem aerospace systems is to address competing objectives such as improved performance, reduced costs, and enhanced safety. Accurate, high-fidelity models are typically time consuming and computationally expensive. Furthermore, informed decisions should be made with an understanding of the impact (global sensitivity) of the design variables on the different objectives. In this context, the so-called surrogate-based approach for analysis and optimization can play a very valuable role. The surrogates are constructed using data drawn from high-fidelity models, and provide fast approximations of the objectives and constraints at new design points, thereby making sensitivity and optimization studies feasible. This paper provides a comprehensive discussion of the fundamental issues that arise in surrogate-based analysis and optimization (SBAO), highlighting concepts, methods, techniques, as well as practical implications. The issues addressed include the selection of the loss function and regularization criteria for constructing the surrogates, design of experiments, surrogate selection and construction, sensitivity analysis, convergence, and optimization. The multi-objective optimal design of a liquid rocket injector is presented to highlight the state of the art and to help guide future efforts.

Queipo, Nestor V.↗
NASA NTRSDate not supplied

Reducing Landing Site Contamination Using 3-D Trajectory Optimization for Surface Hoppers

Rocket-powered vehicles utilizing Vertical Take-off Vertical Landing (VTVL) are a compelling alternative to surface rovers for exploring planetary and lunar bodies. These so called “hoppers” provide enhanced mobility for accessing locations difficult to reach, and over a wider region of the surface. However, contamination and plume interactions from rocket exhaust deposited at landing sites is anticipated since landing approaches are typically along a vertical direction during the final descent. Consequently, exhaust products may alter the surface chemistry, potentially confounding compositional analysis for samples collected in the vicinity of the landing site or jeopardize mining efforts. There has been no rigorous study on flight maneuvers that can mitigate plume-to-surface interactions. A multi-objective optimization tool has been developed to simulate propulsive hops on a planetary body and minimize both fuel consumption and site alterations. Trajectories are derived by multi-objective optimization and include solutions with significant reduction in contamination for a modest increase in fuel consumption. For these solutions, surface-to-surface propulsive transfer is demonstrated, but the method can also be modified for orbit-to-surface transfers (e.g., landers).

guidance↗
NASA NTRSDate not supplied

Reducing Landing Site Contamination Using 3-D Trajectory Optimization for Surface Hoppers

Rocket-powered vehicles utilizing Vertical Take-off Vertical Landing (VTVL) are a compelling alternative to surface rovers for exploring planetary and lunar bodies. These so called “hoppers” provide enhanced mobility for accessing locations difficult to reach, and over a wider region of the surface. However, contamination and plume interactions from rocket exhaust deposited at landing sites is anticipated since landing approaches are typically along a vertical direction during the final descent. Consequently, exhaust products may alter the surface chemistry, potentially confounding compositional analysis for samples collected in the vicinity of the landing site or jeopardize mining efforts. There has been no rigorous study on flight maneuvers that can mitigate plume-to-surface interactions. A multi-objective optimization tool has been developed to simulate propulsive hops on a planetary body and minimize both fuel consumption and site alterations. Trajectories are derived by multi-objective optimization and include solutions with significant reduction in contamination for a modest in-crease in fuel consumption. For these solutions, surface-to-surface propulsive transfer is demonstrated, but the method can also be modified for orbit-to-surface transfers (e.g., landers).

guidance↗
NASA NTRS1990

Multi-objective shape and material optimization of composite structures including damping

A multi-objective optimal design methodology is developed for light-weight, low cost composite structures of improved dynamic performance. The design objectives include minimization of resonance amplitudes (or maximization of modal damping), weight, and material cost. The design vector includes micromechanics, laminate, and structural shape parameters. Performance constraints are imposed on static displacements, dynamic amplitudes, and natural frequencies. The effects of damping on the dynamics of composite structures are incorporated. Preliminary applications on a cantilever composite beam illustrated that only the proposed multi-objective optimization, as opposed to single objective functions, simultaneously improved all objectives. The significance of composite damping in the design of advanced composite structures was also demonstrated, indicating the design methods based on undamped dynamics may fail to improve the dynamic performance near resonances.

Saravanos, D. A.↗
NASA NTRS1990

Multi-objective shape and material optimization of composite structures including damping

A multi-objective optimal design methodology is developed for light-weight, low-cost composite structures of improved dynamic performance. The design objectives include minimization of resonance amplitudes (or maximization of modal damping), weight, and material cost. The design vector includes micromechanics, laminate, and structural shape parameters. Performance constraints are imposed on static displacements, dynamic amplitudes, and natural frequencies. The effects of damping on the dynamics of composite structures are incorporated. Preliminary applications on a cantilever composite beam illustrated that only the proposed multi-objective optimization, as opposed to single objective functions, simultaneously improved all objectives. The significance of composite damping in the design of advanced composite structures was also demonstrated, indicating that design methods based on undamped dynamics may fail to improve the dynamic performance near resonances.

Saravanos, D. A.↗