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At least 559 records · Page 31
All sourcesNASA NTRSDOE OSTI
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https://cneos.jpl.nasa.gov/ pd/cs/pdc17/. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or lowthrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft/asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth/spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection

Barbee, Brent W.↗
NASA NTRS2017

Spacecraft Mission Design for the Mitigation of the 2017 PDC Hypothetical Asteroid Threat

This paper presents a detailed mission design analysis results for the 2017 Planetary Defense Conference (PDC) Hypothetical Asteroid Impact Scenario, documented at https:cneos.jpl.nasa.govpdcspdc17. The mission design includes campaigns for both reconnaissance (flyby or rendezvous) of the asteroid (to characterize it and the nature of the threat it poses to Earth) and mitigation of the asteroid, via kinetic impactor deflection, nuclear explosive device (NED) deflection, or NED disruption. Relevant scenario parameters are varied to assess the sensitivity of the design outcome, such as asteroid bulk density, asteroid diameter, momentum enhancement factor, spacecraft launch vehicle, and mitigation system type. Different trajectory types are evaluated in the mission design process from purely ballistic to those involving optimal midcourse maneuvers, planetary gravity assists, and/or low-thrust solar electric propulsion. The trajectory optimization is targeted around peak deflection points that were found through a novel linear numerical technique method. The optimization process includes constrain parameters, such as Earth departure date, launch declination, spacecraft, asteroid relative velocity and solar phase angle, spacecraft dry mass, minimum/maximum spacecraft distances from Sun and Earth, and Earth-spacecraft communications line of sight. Results show that one of the best options for the 2017 PDC deflection is solar electric propelled rendezvous mission with a single spacecraft using NED for the deflection.

Barbee, Brent W.↗
NASA NTRS1974

The discrete complementary variational principle and optimal control systems

A discrete complementary variational principle is developed and applied to linear and nonlinear discrete-time optimal control systems. Using the variational approach, a primal-dual relationship is established. This relationship provides a precise measure of system suboptimality independent of any a priori knowledge of the optimal solution.

Chan, W. L.↗
NASA NTRS1985

A method to stabilize linear systems using eigenvalue gradient information

Formal optimization methods and eigenvalue gradient information are used to develop a stabilizing control law for a closed loop linear system that is initially unstable. The method was originally formulated by using direct, constrained optimization methods with the constraints being the real parts of the eigenvalues. However, because of problems in trying to achieve stabilizing control laws, the problem was reformulated to be solved differently. The method described uses the Davidon-Fletcher-Powell minimization technique to solve an indirect, constrained minimization problem in which the performance index is the Kreisselmeier-Steinhauser function of the real parts of all the eigenvalues. The method is applied successfully to solve two different problems: the determination of a fourth-order control law stabilizes a single-input single-output active flutter suppression system and the determination of a second-order control law for a multi-input multi-output lateral-directional flight control system. Various sets of design variables and initial starting points were chosen to show the robustness of the method.

Wieseman, C. D.↗
NASA NTRS1992

Control-structure interaction

The feasibility of using conventional proportional-integral-derivative (PID) control and an alternative optimal control to perform the pointing and tracking functions of the Space Station solar dynamic power module is investigated. A very large state model of 6 rigid body modes and 272 flexible modes is used in conjunction with classical linear-quadratic-Gaussian (LQG) optimal control to produce a full-order controller that satisfies the requirements. The results are compared with a classically designed PID controller that was implemented for a much smaller (6 rigid body, 40 flexible modes) model. The conventional control design approach is shown to be very much influenced by the order reduction of the plant model, i.e., the number of retained elastic modes from the full-order model, suggesting that for a complex, large space structure, such as the Space Station Freedom solar dynamic module, application of conventional control system design methods may not be adequate. The use of LQG control is recommended, and method for solving the large matrix. Riccati equation that arises from the optimal formulation is provided.

Cheng, Joseph K.↗
NASA NTRS1999

Non-waisted fuselage design for supersonic aircraft

A method for designing a non-waisted fuselage for supersonic wing/fuselage configurations that increases the fuselage volume and improves the supersonic aerodynamic performance compared to a conventional waisted-fuselage configuration. The method entails removing the waisted region of an existing waisted-fuselage configuration by linearly reconstructing cross-sections between the endpoints representing the waisted cross-sectional area portion to create a modified fuselage configuration without waisting. This configuration will have increased fuselage volume and improved supersonic aerodynamic performance. The fuselage camber can then be optimized using non-linear aerodynamic methods to further increase the supersonic aerodynamic performance.

Hager, James O.↗
NASA NTRS1983

Minimum information modelling of structural systems with uncertain parameters

Work is reviewed wherein the design of active structural control is formulated as the mean-square optimal control of a linear mechanical system with stochastic parameters. In practice, a complete probabilistic description of model parameters can never be provided by empirical determinations, and a suitable design approach must accept very limited a priori data on parameter statistics. In consequence, the mean-square optimization problem is formulated using a complete probability assignment which is made to be consistent with available data but maximally unconstrained otherwise through use of a maximum entropy principle. The ramifications of this approach for both robustness and large dimensionality are illustrated by consideration of the full-state feedback regulation problem.

Hyland, D. C.↗
NASA NTRS2010

Verifiable Adaptive Control with Analytical Stability Margins by Optimal Control Modification

This paper presents a verifiable model-reference adaptive control method based on an optimal control formulation for linear uncertain systems. A predictor model is formulated to enable a parameter estimation of the system parametric uncertainty. The adaptation is based on both the tracking error and predictor error. Using a singular perturbation argument, it can be shown that the closed-loop system tends to a linear time invariant model asymptotically under an assumption of fast adaptation. A stability margin analysis is given to estimate a lower bound of the time delay margin using a matrix measure method. Using this analytical method, the free design parameter n of the optimal control modification adaptive law can be determined to meet a specification of stability margin for verification purposes.

Nguyen, Nhan T.↗
NASA NTRS1988

Modeling and control of flexible structures

This monograph presents integrated modeling and controller design methods for flexible structures. The controllers, or compensators, developed are optimal in the linear-quadratic-Gaussian sense. The performance objectives, sensor and actuator locations and external disturbances influence both the construction of the model and the design of the finite dimensional compensator. The modeling and controller design procedures are carried out in parallel to ensure compatibility of these two aspects of the design problem. Model reduction techniques are introduced to keep both the model order and the controller order as small as possible. A linear distributed, or infinite dimensional, model is the theoretical basis for most of the text, but finite dimensional models arising from both lumped-mass and finite element approximations also play an important role. A central purpose of the approach here is to approximate an optimal infinite dimensional controller with an implementable finite dimensional compensator. Both convergence theory and numerical approximation methods are given. Simple examples are used to illustrate the theory.

Gibson, J. S.↗
NASA NTRS1988

Results of an integrated structure-control law design sensitivity analysis

Next generation air and space vehicle designs are driven by increased performance requirements, demanding a high level of design integration between traditionally separate design disciplines. Interdisciplinary analysis capabilities have been developed, for aeroservoelastic aircraft and large flexible spacecraft control for instance, but the requisite integrated design methods are only beginning to be developed. One integrated design method which has received attention is based on hierarchal problem decompositions, optimization, and design sensitivity analyses. This paper highlights a design sensitivity analysis method for Linear Quadratic Cost, Gaussian (LQG) optimal control laws, which predicts change in the optimal control law due to changes in fixed problem parameters using analytical sensitivity equations. Numerical results of a design sensitivity analysis for a realistic aeroservoelastic aircraft example are presented. In this example, the sensitivity of the optimally controlled aircraft's response to various problem formulation and physical aircraft parameters is determined. These results are used to predict the aircraft's new optimally controlled response if the parameter was to have some other nominal value during the control law design process. The sensitivity results are validated by recomputing the optimal control law for discrete variations in parameters, computing the new actual aircraft response, and comparing with the predicted response. These results show an improvement in sensitivity accuracy for integrated design purposes over methods which do not include changess in the optimal control law. Use of the analytical LQG sensitivity expressions is also shown to be more efficient that finite difference methods for the computation of the equivalent sensitivity information.

Gilbert, Michael G.↗
NASA NTRS1975

A linear feedback guidance law for an Aeromaneuvering Orbit-to-Orbit Shuttle

The sensitivity of the trajectory of an Aeromaneuvering Orbit-to-Orbit Shuttle (AMOOS) to unpredictable variations in atmospheric density is shown and a compensating guidance law is developed. The sensitivity was determined using a varying atmosphere model whose statistical properties matched those of actual atmosphere data. This study showed that a compensating guidance law is crucial to the feasibility of AMOOS. Using an optimal regulator approach, a linear feedback law for bank angle was developed and checked out with the atmosphere model. This law uses the altitude profile of the trajectory to control the amount of energy dissipated within the atmosphere.

Rehder, J. J.↗
NASA NTRS1978

Specific-optimal control with a dual minimal-order observer-based compensator

The steady-state optimal control of a linear time-invariant stochastic system by means of a minimal-order dual-observer-based compensator is considered in this paper. The structure of the compensator is fixed while the associated gains are to be chosen so as to minimize a quadratic penalty on the plant state. Necessary and sufficient conditions for optimality are given, and an explicit solution is displayed. Salient features pertaining to the optimal system are: a decoupling property, a projection property, and an innovation property. Finally, it is shown that this design corresponds to a singular LQG problem, which is precisely the dual of another singular LQG problem: namely Newmann's problem. A complete picture is then given showing clearly the correspondence between the two designs.

Blanvillain, P. J.↗
NASA NTRS2016

Temporal Gain Correction for X-Ray Calorimeter Spectrometers

Calorimetric X-ray detectors are very sensitive to their environment. The boundary conditions can have a profound effect on the gain including heat sink temperature, the local radiation temperature, bias, and the temperature of the readout electronics. Any variation in the boundary conditions can cause temporal variations in the gain of the detector and compromise both the energy scale and the resolving power of the spectrometer. Most production X-ray calorimeter spectrometers, both on the ground and in space, have some means of tracking the gain as a function of time, often using a calibration spectral line. For small gain changes, a linear stretch correction is often sufficient. However, the detectors are intrinsically non-linear and often the event analysis, i.e., shaping, optimal filters etc., add additional non-linearity. Thus for large gain variations or when the best possible precision is required, a linear stretch correction is not sufficient. Here, we discuss a new correction technique based on non-linear interpolation of the energy-scale functions. Using Astro-HSXS calibration data, we demonstrate that the correction can recover the X-ray energy to better than 1 part in 104 over the entire spectral band to above 12 keV even for large-scale gain variations. This method will be used to correct any temporal drift of the on-orbit per-pixel gain using on-board calibration sources for the SXS instrument on the Astro-H observatory.

X-ray detector X-ray spectrometer X-ray calorimete↗
NASA NTRS1990

Optimal fabrication processes for unidirectional metal-matrix composites: A computational simulation

A method is proposed for optimizing the fabrication process of unidirectional metal matrix composites. The temperature and pressure histories are optimized such that the residual microstresses of the composite at the end of the fabrication process are minimized and the material integrity throughout the process is ensured. The response of the composite during the fabrication is simulated based on a nonlinear micromechanics theory. The optimal fabrication problem is formulated and solved with non-linear programming. Application cases regarding the optimization of the fabrication cool-down phases of unidirectional ultra-high modulus graphite/copper and silicon carbide/titanium composites are presented.

Saravanos, D. A.↗
NASA NTRSDate not supplied

Hardware-Efficient Quantum Optimization Layered Algorithms and Experiments

Quantum optimization algorithms, such as QAOA, that implement parametrized stochastic optimization solvers attempt to identify low-energy solutions of Ising systems by exploiting available quantum effects in noisy-intermediate scale machines. Engineering a well-performing parametrized quantum optimization circuit is indeed an exercise in balancing the trade-off between expressivity and implementation complexity. We show that, for MaxCut QAOA circuits defined on native hardware topology (Rigetti’s Aspen Quantum Processors), error-mitigation techniques recover simulated features of the noiseless theory. Moreover, we explore a design space for QAOA-like ansatze that perform well in theory as well as in hardware for fully-connected problems. We also discuss how efficient coherence and entanglement detection methods that could be coupled with quantum optimization experiments require only linear overhead in benchmarking time.

quantum computing↗
NASA NTRS2019

Using Computational Flow Imaging to Optimize Filtered Rayleigh Scattering Measurements of an Isolator Shock Train

Filtered Rayleigh scattering (FRS) is a laser diagnostic where the intensity of elastically scattered light is measured after it passes through a molecular absorption filter. The filter removes background interference that overwhelms the relatively weak scattering from the gas molecules. However, with a filter, the measured light intensity depends on many of the scattering gas properties, including pressure, density, temperature, and velocity. In this work, CFD simulations of an isolator shock train flow field are input into a physics-based model to predict the values of FRS intensity measurements in a proposed experiment. The goal is to evaluate if a simplistic FRS setup (that utilizes one camera, laser, and absorption filter) can be used to accurately quantify number density despite the fact that the scattered light intensity also depends on other gas properties. It is found that the experimental setup can be optimized such that a linear relationship describes the number density with an average prediction error of 2%. The vast majority of the flow exhibits prediction errors of less than 3%, but small regions of the flow reach up to 11% error. A sensitivity analysis shows that the prediction error increases with the central wavelength of the incident laser light and decreases with the angle between the camera and laser propagation directions. The optimal experimental parameters are chosen based on a compromise between the prediction error, spatial resolution, and the amount of unfiltered light. In the future, the proposed FRS setup will be implemented to acquire new and valuable information on an isolator shock train, a flow field that has been traditionally studied using wall static pressure measurements and path-integrated visualization techniques, such as schlieren and shadowgraphy.

Hunt, Robin L.↗
NASA NTRS1974

Transient response of multidegree-of-freedom linear systems to forcing functions with inequality constraints

Optimal control theory is applied to analyze the transient response of discrete linear systems to forcing functions with unknown time dependence but having known bounds. Particular attention is given to forcing functions which include: (1) maximum displacement of any given mass element, (2) maximum relative displacement of any two adjacent masses, and (3) maximum acceleration of a given mass. Linear mechanical systems with an arbitrary number of degrees of freedom and only one forcing function acting are considered. In the general case, the desired forcing function is found to be a function that switches from the upper-to-lower bound and vice-versa at certain moments of time. A general procedure for finding such switching times is set forth.

Michalopoulos, C. D.↗