Results for “Robust optimization” — Page 35

NASA NTRS1985

Design and evaluation of control systems for large communications satellites

Control techniques for future large flexible spacecraft are developed. Control design and analysis are supported by a comprehensive CAD system. The proposed operational mobile communications satellite (OMSAT) featuring a 44 m offset fed antenna is used as target application. Requirements for satellite attitude control and communications beam pointing are defined. The following control methods are applied to the system: standard linear optimal regulator (LOR) with Luenberger observer, LOR/observer with selective spill-over suppression, frequency shaped LOR, LOR with closed-loop order reduction by cost decoupling, and robust servomechanism.

Steiber, M. E.↗

NASA NTRSDate not supplied

Temporal Changes in Astronauts’ Muscle and Cardiorespiratory Physiology Before, During, and After Spaceflight

NASA’s planned space exploration missions will require astronauts to safely perform extravehicular activity (EVA) and to safely egress vehicles in a variety of landing scenarios. Prolonged exposure to spaceflight decreases cardiovascular and sensorimotor function, causes loss of bone mineral density, reduces muscle mass and strength, and ultimately diminishes tolerance for physical activity. Although exercise can help mitigate these spaceflight-induced physiological decrements, little is known regarding the time-course of changes in muscle and aerobic performance during spaceflight. Furthermore, these exercise countermeasures are not fully protective. For example, maximal aerobic capacity (VO2pk), lower body muscle cross-sectional area, and strength all decrease by about 10% to 15% after long-duration missions on the International Space Station (ISS). Future long-duration space missions beyond Low Earth Orbit will employ exploration vehicles with less robust exercise hardware and more constrained exercise capabilities (e.g., less operational volume, less active exercise time) than provided on the ISS. Thus, countermeasures will need to be optimized to protect crew health and performance on exploration-class missions lasting up to 3 years. This requires a more detailed understanding of the dynamic effects of spaceflight on human health and performance, the ability of exercise to protect against this deconditioning, and the interaction of exercise with interrelated factors like nutrition, sleep, and environmental conditions.

N.C. Strock↗

NASA NTRSDate not supplied

Capturing, Analyzing, Maintaining, and Disseminating Shape Memory Material Data Between Information Management Systems

With an increased demand on reducing the time, cost, and effort to develop new materials, Integrated Computational Materials Engineering (ICME) has received widespread attention in various engineering disciplines as a catalyst for significantly reducing experimental testing during the material design process. An ICME approach to design can enable ‘fit-for-purpose’ materials to be realized in engineering applications by incorporating well-understood process-property-performance relationships between the various length and time scales in a material’s structure, enabling material optimization. However, such an approach requires validated multiscale models at the various length scales for a material, which in turn requires a large amount of data, a robust means of storing the data, and the ability to link data to developed material models. The NASA Vision 2040 [1] has identified nine key elements to enabling ICME approaches in system level design, with one being “Data, Information, and Visualization”, thus outlining the importance of a robust information management system for ICME. As the relationship between microstructure, properties, and material performance become better understood and incorporated into multiscale models that can be leveraged in application design, the emergence of new materials with application-driven properties can be realized. One such new material class that has seen growing attention are shape memory materials (SMM), in which a material can transition between a deformed and undeformed state via a reversible phase transformation when subject to a thermal, mechanical, or magnetic load [2]. SMMs have been used widely in aerospace and biomedical industries, including applications such as actuators, low-shock mechanisms, medical staples, braces, and stents [3, 4]. These materials exhibit unique behavior due to their ability to transition between phases, and thus the mechanisms that enable this transition must be captured in a data information management system and incorporated into SMM material models. At NASA Glenn Research Center, the Shape Memory Materials Database (SMMD) Tool has been developed to capture the necessary information that governs SMM material behavior and provide users the ability to select and visualize various SMMs for a specific application [5]. The database contains point-wise data for published SMM materials, along with the pedigree metadata for traceability necessary for a robust information management system. The database is also capable of storing in-house test data performed at NASA GRC by interacting with the developed Shape Memory Alloy (SMA) Analytics tool to extract the necessary point-wise values and populate the database. Although the SMMD Tool offers its users a single, authoritative source for SMM material data that is critical for model development and material design, the full material pedigree of the in-house test data for SMMs is not currently captured and is out of the scope for the SMMD tool. In this work, the schema for capturing SMM test data within the larger NASA GRC ICME Schema [6, 7, 8, 9] will be developed and implemented for thermomechanical tests conducted at NASA GRC. The developed schema will not only store the relevant data needed for the SMMD tool, but also the material pedigree (i.e., production of the bulk material, bulk material analysis, sample cut-out diagrams, sample fabrication procedure, etc.), test pedigree (i.e., test equipment used, measurement systems used, raw test data), and analysis pedigree (i.e., how the data in the SMMD tool is calculated). Furthermore, a Python-based framework will be developed to seamlessly interact between the SMA Analytics and SMMD tools, which will write the full dataset and associated metadata to the GRC Information Management System before passing the required point-wise data to the SMMD tool. Data informatics is a key element of the NASA Vision 2040, which requires not only that data is stored and maintained throughout the material lifecycle, but that the data is also accessible and reusable such that material development efforts can be minimized. Therefore, for an ICME design approach to be realized, a centralized information management system that drives the ICME process must be able to communicate with other databases. The work that will be presented in this presentation will therefore not only demonstrate the ability of NASA GRC’s information management system to capture SMM data, but also its ability to interact with pre-existing tools specialized for such materials.

Data management↗

NASA NTRSDate not supplied

Temporal Changes in Astronauts’ Muscle and Cardiorespiratory Physiology Before, During, and After Spaceflight

NASA’s planned space exploration missions will require astronauts to safely perform extravehicular activity (EVA) and to safely egress vehicles in a variety of landing scenarios. Prolonged exposure to spaceflight decreases cardiovascular and sensorimotor function, causes loss of bone mineral density, reduces muscle mass and strength, and ultimately diminishes tolerance for physical activity. Although exercise can help mitigate these spaceflight-induced physiological decrements, little is known regarding the time-course of changes in muscle and aerobic performance during spaceflight. Furthermore, these exercise countermeasures are not fully protective. For example, maximal aerobic capacity (VO2pk), lower body muscle cross-sectional area, and strength all decrease by about 10% to 15% after long-duration missions on the International Space Station (ISS). Future long-duration space missions beyond Low Earth Orbit will employ exploration vehicles with less robust exercise hardware and more constrained exercise capabilities (e.g., less operational volume, less active exercise time) than provided on the ISS. Thus, countermeasures will need to be optimized to protect crew health and performance on exploration-class missions lasting up to 3 years. This requires a more detailed understanding of the dynamic effects of spaceflight on human health and performance, the ability of exercise to protect against this deconditioning, and the interaction of exercise with interrelated factors like nutrition, sleep, and environmental conditions.

N. Strock↗

NASA NTRSDate not supplied

Design Under Uncertainty with Design-Dependent Uncertain Variables

Uncertainty quantification (UQ) can provide a more robust understanding of a system, leading to better informed decisions earlier in the design process. The additional information that UQ provides can be leveraged during a design optimization process known as design under uncertainty that, when incorporated with multidisciplinary design and optimization, can become computationally infeasible due to the large number of responses required for meaningful results. Previous work addressed reducing the computational expense in design under uncertainty by incorporating analytic derivatives throughout polynomial chaos expansion. Although this allows design under uncertainty to be feasible for more systems, some multidisciplinary systems have design-dependent uncertain variables. This paper details an implementation of design dependent uncertain variables in a manner than preserves derivatives required for efficient gradient-based optimization throughout the process. Two analytic examples of design-dependent uncertain variables are given: the first transforms a uniform uncertain variable with one design variable and the second transforms a normal uncertain variable with two design variables. The polynomial chaos expansion (PCE) results are comparable to both the Monte Carlo (MC) results and the analytic results for the two examples. A case study that maximizes the lift-to-drag ratio with a design-dependence between the wing leading edge sweep angle and uncertain parameter percentage of laminar flow is compared to a MC and alternative optimization formulations. This paper demonstrates that design-dependent uncertain variables are valid and hold throughout PCE.

Joanna N Schmidt↗

NASA NTRS1990

Model reduction for flexible structures

Several conditions for a near-optimal reduction of general dynamic systems are presented focusing on the reduction in balanced and modal coordinates. It is shown that model and balanced reductions give very different results for the flexible structure with closely-spaced natural frequencies. In general, balanced reduction is found to give better results. A robust model reduction technique was developed to study the sensitivity of modeling error to variations in the damping of a structure. New concepts of grammians defined over a finite time and/or a frequency interval are proposed including computational procedures for evaluating them. Application of the model reduction technique to these grammians is considered to lead to a near-optimal reduced model which closely reproduces the full system output in the time and/or frequency interval.

Gawronski, Wodek↗

NASA NTRS1996

Vibration Attenuation of the NASA Langley Evolutionary Structure Experiment Using H(infinity) and Structured Singular Value (mu) Robust Multivariable Control Techniques

This final report summarizes the research results under NASA Contract NAG-1-1254 from May, 1991 - April, 1995. The main contribution of this research are in the areas of control of flexible structures, model validation, optimal control analysis and synthesis techniques, and use of shape memory alloys for structural damping.

Balas, Gary J.↗

NASA NTRS2007

A Robustly Stabilizing Model Predictive Control Algorithm

A model predictive control (MPC) algorithm that differs from prior MPC algorithms has been developed for controlling an uncertain nonlinear system. This algorithm guarantees the resolvability of an associated finite-horizon optimal-control problem in a receding-horizon implementation.

Ackmece, A. Behcet↗

NASA NTRS1985

A methodology for designing robust multivariable nonlinear feedback control systems

This paper presents an outline of a methodology for the design of nonlinear dynamic compensators for nonlinear multivariable systems with guarantees of closed-loop stability, robustness, and performance. The method is an extension of the Linear-Quadratic-Gaussian with Loop-Transfer-Recovery (LQG/LTR) methodology for linear systems, thus hinging upon the idea of constructing an approximate nonlinear inverse operator for the plant. A major feature of the method is a unification of both the state-space and Input-Output formulations. The major results of the paper are: (1) Properties of the solution of certain optimal control problems; (2) New results on nonlinear estimation, including a new nonlinear observer with certain guaranteed properties; (3) The Loop Operator Recovery (LOR) procedure, and (4) Inclusion of command-following and disturbance rejection with a goal of a closed-loop stable, robust system.

Grunberg, D. B.↗

NASA NTRS1996

An Open Computing Infrastructure that Facilitates Integrated Product and Process Development from a Decision-Based Perspective

Computer applications for design have evolved rapidly over the past several decades, and significant payoffs are being achieved by organizations through reductions in design cycle times. These applications are overwhelmed by the requirements imposed during complex, open engineering systems design. Organizations are faced with a number of different methodologies, numerous legacy disciplinary tools, and a very large amount of data. Yet they are also faced with few interdisciplinary tools for design collaboration or methods for achieving the revolutionary product designs required to maintain a competitive advantage in the future. These organizations are looking for a software infrastructure that integrates current corporate design practices with newer simulation and solution techniques. Such an infrastructure must be robust to changes in both corporate needs and enabling technologies. In addition, this infrastructure must be user-friendly, modular and scalable. This need is the motivation for the research described in this dissertation. The research is focused on the development of an open computing infrastructure that facilitates product and process design. In addition, this research explicitly deals with human interactions during design through a model that focuses on the role of a designer as that of decision-maker. The research perspective here is taken from that of design as a discipline with a focus on Decision-Based Design, Theory of Languages, Information Science, and Integration Technology. Given this background, a Model of IPPD is developed and implemented along the lines of a traditional experimental procedure: with the steps of establishing context, formalizing a theory, building an apparatus, conducting an experiment, reviewing results, and providing recommendations. Based on this Model, Design Processes and Specification can be explored in a structured and implementable architecture. An architecture for exploring design called DREAMS (Developing Robust Engineering Analysis Models and Specifications) has been developed which supports the activities of both meta-design and actual design execution. This is accomplished through a systematic process which is comprised of the stages of Formulation, Translation, and Evaluation. During this process, elements from a Design Specification are integrated into Design Processes. In addition, a software infrastructure was developed and is called IMAGE (Intelligent Multidisciplinary Aircraft Generation Environment). This represents a virtual apparatus in the Design Experiment conducted in this research. IMAGE is an innovative architecture because it explicitly supports design-related activities. This is accomplished through a GUI driven and Agent-based implementation of DREAMS. A HSCT design has been adopted from the Framework for Interdisciplinary Design Optimization (FIDO) and is implemented in IMAGE. This problem shows how Design Processes and Specification interact in a design system. In addition, the problem utilizes two different solution models concurrently: optimal and satisfying. The satisfying model allows for more design flexibility and allows a designer to maintain design freedom. As a result of following this experimental procedure, this infrastructure is an open system that it is robust to changes in both corporate needs and computer technologies. The development of this infrastructure leads to a number of significant intellectual contributions: 1) A new approach to implementing IPPD with the aid of a computer; 2) A formal Design Experiment; 3) A combined Process and Specification architecture that is language-based; 4) An infrastructure for exploring design; 5) An integration strategy for implementing computer resources; and 6) A seamless modeling language. The need for these contributions is emphasized by the demand by industry and government agencies for the development of these technologies.

Hale, Mark A.↗

NASA NTRS1993

Hybrid state-space self-tuning control of uncertain linear systems

The paper presents a hybrid state-space self-tuner using a new dual-rate sampling scheme for digital adaptive control of continuous-time uncertain linear systems. A state-space-based recursive least-squares algorithm, together with a variable forgetting factor, is used for direct estimations of both the equivalent discrete-time uncertain linear system parameters and the associated discrete-time state of a continuous-time uncertain linear system from the sampled input and output data. An analogue optimal regional pole-placement design method is used for designing an optimal observer-based analogue controller. A suboptimal observer-based digital controller is then designed from the designed analogue controller using digital redesign technique. To enhance the robustness of parameter identification and state estimation algorithms, a dynamic bound for a class of uncertain bilinear parameters and a fast-rate digital controller are developed at each fast-sampling period. Also, to accommodate computation loads and computation delay for developing the advanced hybrid self-tuner, the designed analogue controller and observer gains are both updated at each slow-sampling period. This control technique has been successfully applied to benchmark control problems.

Shieh, L. S.↗

NASA NTRS1997

Design, Modeling and Performance Optimization of a Novel Rotary Piezoelectric Motor

This work has demonstrated a proof of concept for a torsional inchworm type motor. The prototype motor has shown that piezoelectric stack actuators can be used for rotary inchworm motor. The discrete linear motion of piezoelectric stacks can be converted into rotary stepping motion. The stacks with its high force and displacement output are suitable actuators for use in piezoelectric motor. The designed motor is capable of delivering high torque and speed. Critical issues involving the design and operation of piezoelectric motors were studied. The tolerance between the contact shoes and the rotor has proved to be very critical to the performance of the motor. Based on the prototype motor, a waveform optimization scheme was proposed and implemented to improve the performance of the motor. The motor was successfully modeled in MATLAB. The model closely represents the behavior of the prototype motor. Using the motor model, the input waveforms were successfully optimized to improve the performance of the motor in term of speed, torque, power and precision. These optimized waveforms drastically improve the speed of the motor at different frequencies and loading conditions experimentally. The optimized waveforms also increase the level of precision of the motor. The use of the optimized waveform is a break-away from the traditional use of sinusoidal and square waves as the driving signals. This waveform optimization scheme can be applied to any inchworm motors to improve their performance. The prototype motor in this dissertation as a proof of concept was designed to be robust and large. Future motor can be designed much smaller and more efficient with lessons learned from the prototype motor.

Duong, Khanh A.↗

NASA NTRS2013

Spiraling Away from Vesta: Design of the Transfer from the Low to High Altitude Dawn Mapping Orbits

Dawn has successfully completed its orbital mission at Vesta and is currently en route to an orbital rendezvous with Ceres in 2015. The longest duration and most complex portion of the Vesta departure trajectory was the transfer from the low to high altitude science orbit. This paper describes the design of this low-thrust trajectory optimized assuming a minimum-propellant mass objective. The transfer utilized solar-electric ion propulsion applied over 139 spacecraft revolutions about Vesta. Science drivers, operational constraints, and robustness to statistical uncertainties are addressed. The 45-day transfer trajectory was successfully implemented in early 2012.

low thrust↗

NASA NTRSDate not supplied

Space Algae-2: Preflight Testing for A Long-Duration, Multi-Omics Analysis of Arthrospira Platensis

The cyanobacteria Arthrospira platensis NIES-39, commonly known as spirulina, could provide a fresh supply of nutrients for crew on long-duration spaceflight missions. Spirulina is a readily digestible food that is high in protein with all essential amino acids as well as significant levels of B vitamins, antioxidants, and anti-inflammatory metabolites. Spaceflight has multiple abiotic stressors such as increased ionizing radiation and microgravity, which causes a lack of convective mixing. These environmental conditions may impact productivity, nutritional composition, and in long-duration propagation, spaceflight stress may impact the genetic stability of spirulina cultures. We are developing an International Space Station experiment to continuously culture A. platensis for six months. Multi-omics profiling will be used to monitor for changes in the genome, transcriptome, proteome, and metabolome to determine if A. platensis is a suitable nutritional supplement on long-duration missions. During preflight testing we developed a protocol for inoculated liquid cultures to survive a 10-week storage period prior to photo-incubation. The bioreactor bag, temperature, and lighting conditions that support a 14-day growth cycle between passages were also determined. Media testing identified minimal salts supporting robust growth that can be stored in liquid or dry form. A simple filtration method was developed to dewater cultures and harvest biomass for frozen sample return. We optimized a cryopreservation method to enable return of live cells for isolation of individual A. platensis clones. The concept of operations for Space Algae-2 developed from these test results as well as progress on multi-omics analysis methods will be presented.

Algae↗

NASA NTRS2021

Monte Carlo Tree Search Methods for the Earth-Observing Satellite Scheduling Problem

This work explores on-board planning for the single spacecraft, multiple ground station Earth-observing satellite scheduling problem through artificial neural network function approximation of state–action value estimates generated by Monte Carlo tree search (MCTS). An extensive hyperparameter search is conducted for MCTS on the basis of performance, safety, and downlink opportunity utilization to determine the best hyperparameter combination for data generation. A hyperparameter search is also conducted on neural network architectures. The learned behavior of each network is explored, and each network architecture’s robustness to orbits and epochs outside of the training distributions is investigated. Furthermore, each algorithm is compared with a genetic algorithm, which serves to provide a baseline for optimality. MCTS is shown to compute near-optimal solutions in comparison to the genetic algorithm. The state–action value networks are shown to match or exceed the performance of MCTS in six orders of magnitude less execution time, showing promise for execution on board spacecraft.

Adam P. Herrmann↗

NASA NTRSDate not supplied

Space Algae-2: Preflight Testing for A Long-Duration, Multi-Omics Analysis of Arthrospira Platensis

The cyanobacteria Arthrospira platensis NIES-39, commonly known as spirulina, could provide a fresh supply of nutrients for crew on long-duration spaceflight missions. Spirulina is a readily digestible food that is high in protein with all essential amino acids as well as significant levels of B vitamins, antioxidants, and anti-inflammatory metabolites. Spaceflight has multiple abiotic stressors such as increased ionizing radiation and microgravity, which causes a lack of convective mixing. These environmental conditions may impact productivity, nutritional composition, and in long-duration propagation, spaceflight stress may impact the genetic stability of spirulina cultures. We are developing an International Space Station experiment to continuously culture A. platensis for six months. Multi-omics profiling will be used to monitor for changes in the genome, transcriptome, proteome, and metabolome to determine if A. platensis is a suitable nutritional supplement on long-duration missions. During preflight testing we developed a protocol for inoculated liquid cultures to survive a 10-week storage period prior to photo-incubation. The bioreactor bag, temperature, and lighting conditions that support a 14-day growth cycle between passages were also determined. Media testing identified minimal salts supporting robust growth that can be stored in liquid or dry form. A simple filtration method was developed to dewater cultures and harvest biomass for frozen sample return. We optimized a cryopreservation method to enable return of live cells for isolation of individual A. platensis clones. The concept of operations for Space Algae-2 developed from these test results as well as progress on multi-omics analysis methods will be presented.

Algae↗

NASA NTRSDate not supplied

TechEdSat-11: Prototyping Autonomous Communications in Orbit

Cognitive Engine 1 (CE-1) is a state-of-the-art automated system designed to manage routine operations and respond to adverse events without requiring human operator input. CE-1 will optimize scheduling capabilities, detect and react to link failures, and ensure data delivery deadlines are met efficiently. Seamless roaming between government and commercial providers will allow for a robust and cost-effective network. TechEdSat-11 will demonstrate two key components of CE-1: User Initiated Services (UIS) and Delay Tolerant Networking (DTN). The first phase of the experiment will use UIS to automate on-demand scheduling of a commercial S-band ground station. Later phases of the experiment will demonstrate DTN store-and-forward and space internetworking capabilities through the TechEdSat-11 S-band radio. This paper will discuss the CE-1 main components relevant to the experiment, the flight and ground software architecture, experiment concept of operations and preliminary results.

Rachel Dudukovich↗

NASA NTRS1989

An implicit and stiffly stable finite element CFD algorithm for unsteady aerodynamics

A stable and accurate finite element CFD algorithm for hyperbolic/incompletely parabolic conservation law systems is described and verified. It combines a Taylor weak statement FEM, an optimal implicit Runge-Kutta time integration algorithm, and a matrix tensor product approximate factorization linear algebra procedure. The results of computational experiments show that the developed algorithm is robust.

Baker, A. J.↗