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At least 919 records · Page 51

Design of localizer capture and track hold for a transport airplane - An H(infinity)/LTR approach

The authors describe the design of a lateral track-hold control law in a localizer capture and track autopilot using a procedure based on H(infinity)-optimization and loop transfer recovery. The recovery of the achievable performance using output feedback from a satisfactory track-hold design obtained in an H(infinity)-optimization is demonstrated. Simulation for a lateral track command is presented along with robustness properties of the output feedback design. Results indicate that the recovery of achievable performance must be carefully traded-off against control bandwidth limitation.

Chen, B. M.↗

Model validation - A connection between robust control and identification

The gap between the models used in control synthesis and those obtained from identification experiments is considered by investigating the connection between uncertain models and data. The model validation problem addressed is: given experimental data and a model with both additive noise and norm-bounded perturbations, is it possible that the model could produce the observed input-output data? This problem is studied for the standard H-infinity/mu framework models. A necessary condition for such a model to describe an experimental datum is obtained. For a large class of models in the robust control framework, this condition is computable as the solution of a quadratic optimization problem.

Smith, Roy S.↗

Active flutter and gust response control

After a short recall concerning the aeroelastic equations, active control law based on optimal stochastic control theory is synthesized for a wing flutter and gust response. Robustness of the control system due to structured and unstructured uncertainties is considered. Robustness recovery technique is applied to improve the stability margin.

Oli, Muluneh↗

Status Of The UPS Space-Marching Flow Solver

The status of the three-dimensional parabolized Navier-Stokes solver UPS is described. The UPS code, initiated at NASA Ames Research Center in 1986, continues to develop and evolve through application to supersonic and hypersonic flow fields. Hypersonic applications have motivated enhancement of the physical modeling capabilities of the code, specifically real gas modeling, boundary conditions, and turbulence and transition modeling. The UPS code has also been modified to enhance robustness and efficiency in order to be practically used in concert with an optimization code for supersonic transport design. These developments are briefly described along with some relevant results for generic test problems obtained during verification of the enhancements. Included developments and results have previously been published and widely disseminated domestically.

Lawerence, Scott L.↗

Human motion planning based on recursive dynamics and optimal control techniques

This paper presents an efficient optimal control and recursive dynamics-based computer animation system for simulating and controlling the motion of articulated figures. A quasi-Newton nonlinear programming technique (super-linear convergence) is implemented to solve minimum torque-based human motion-planning problems. The explicit analytical gradients needed in the dynamics are derived using a matrix exponential formulation and Lie algebra. Cubic spline functions are used to make the search space for an optimal solution finite. Based on our formulations, our method is well conditioned and robust, in addition to being computationally efficient. To better illustrate the efficiency of our method, we present results of natural looking and physically correct human motions for a variety of human motion tasks involving open and closed loop kinematic chains.

Non-NASA Center↗

Frequency Weighted H2 Control Design for the Glovebox Integrated Microgravity Isolation Technology (g-LIMIT)

The acceleration environment on the International Space Station (ISS) exceeds the requirements of many microgravity experiments. The Glovebox Integrated Microgravity Isolation Technology (g-LIMIT) has been built by the NASA Marshall Space Flight Center to attenuate the nominal acceleration environment and provide some isolation for microgravity science experiments. The g-LIMIT uses Lorentz (voice-coil) magnetic actuators to isolate a platform, for mounting science payloads, from the nominal acceleration environment. The system utilizes payload-acceleration, relative-position, and relative-orientation measurements in a feedback controller to accomplish the vibration isolation task. The controller provides current commands to six magnetic actuators, producing the required experiment isolation from the ISS acceleration environment. The present work documents the development of a candidate control law to meet the acceleration attenuation requirements for the g-LIMIT experiment platform. The controller design is developed using linear optimal control techniques for frequency-weighted H2 norms. Comparison of performance and robustness to plant uncertainty for this control design approach is included in the discussion. System performance is demonstrated in the presence of plant modeling error.

Calhoun, Philip C.↗

Austere Human Missions to Mars

The Design Reference Architecture 5 (DRA 5) is the most recent concept developed by NASA to send humans to Mars in the 2030 time frame using Constellation Program elements. DRA 5 is optimized to meet a specific set of requirements that would provide for a robust exploration program to deliver a new six-person crew at each biennial Mars opportunity and provide for power and infrastructure to maintain a highly capable continuing human presence on Mars. This paper examines an alternate architecture that is scaled back from DRA 5 and might offer lower development cost, lower flight cost, and lower development risk. It is recognized that a mission set using this approach would not meet all the current Constellation Mars mission requirements; however, this 'austere' architecture may represent a minimum mission set that would be acceptable from a science and exploration standpoint. The austere approach is driven by a philosophy of minimizing high risk or high cost technology development and maximizing development and production commonality in order to achieve a program that could be sustained in a flat-funded budget environment. Key features that would enable a lower technology implementation are as follows: using a blunt-body entry vehicle having no deployable decelerators, utilizing aerobraking rather than aerocapture for placing the crewed element into low Mars orbit, avoiding the use of liquid hydrogen with its low temperature and large volume issues, using standard bipropellant propulsion for the landers and ascent vehicle, and using radioisotope surface power systems rather than a nuclear reactor or large area deployable solar arrays. Flat funding within the expected NASA budget for a sustained program could be facilitated by alternating cargo and crew launches for the biennial Mars opportunities. This would result in two assembled vehicles leaving Earth orbit for Mars per Mars opportunity. The first opportunity would send two cargo landers to the Mars surface to preposition a habitat, supplies, and exploration equipment. The next opportunity, two years later, would send to Mars orbit 1) a lander with a Mars Ascent Vehicle (MAV) and 2) a crewed Mars Transit Habitat with an Orion CEV for Earth return. The following opportunity, two years after the first crew, would go back to cargo-only launches. This alternation of cargo and crew opportunities results in a sustainable launch rate of six Ares V launches every two years. It is notable that four of the six launches per Mars opportunity are identical, build-to-print, Tran-Mars Injection stages. This type of production rate could lend itself well to a COTStype service provider, and would make it feasible to have a live spare in place in the event of a single launch failure.

landers↗

Advances in Adaptive Control Methods

This poster presentation describes recent advances in adaptive control technology developed by NASA. Optimal Control Modification is a novel adaptive law that can improve performance and robustness of adaptive control systems. A new technique has been developed to provide an analytical method for computing time delay stability margin for adaptive control systems.

Nguyen, Nhan↗

Temporal Changes in Astronauts’ Muscle and Cardiorespiratory Physiology Pre-, In-, and Post-Spaceflight

NASA’s vision for future exploration missions depends on the ability to protect astronauts’ health and safety for performance of Extravehicular Activity (EVA), and to allow astronauts to safely egress from vehicles in a variety of landing scenarios (e.g. water landing upon return to Earth and undefined planetary/lunar landings). Prolonged exposure to spaceflight results in diminished tolerance to prolonged physical activity, decreased cardiac and sensorimotor function, and loss of bone mineral density, muscle mass, and muscle strength. For over 50 years exercise has been the primary countermeasure against these physiologic decrements during spaceflight, and while the resulting protection is adequate for ISS missions (i.e., Soyuz landing, microgravity EVAs), there is little information regarding time-course changes in muscle and aerobic performance. As spaceflight progresses towards longer exploration missions and vehicles with less robust exercise capabilities compared to ISS, countermeasures will need to be combined and optimized to protect crew health and performance across all organ systems over the course of exploration missions up to 3 years in duration. This will require a more detailed understanding of the dynamic effects of spaceflight on human performance. Thus, the focus of this study is quantifying decrements in physical performance over different mission durations, and to provide detailed information on the physiological rational for “why” and “when” observed changes in performance occur. The research proposed will temporally profile changes in astronauts’ cardiorespiratory fitness, muscle mass, strength, and endurance over spaceflight missions of 2 months, 6 months, and up to 1 year in duration. Additionally, an extrapolation model will provide predictions for changes associated with exploration missions 2-3 years in duration. To accomplish these objectives astronauts will be asked to participate in pre, in, post-flight measurement of muscle performance, muscle size, cardiorespiratory fitness and submaximal performance capabilities, as well as non-invasive assessment of cerebral and muscle oxygenation and perfusion (Table 1). Additionally, ambulatory and in-flight exercise, nutrition, and sleep will be monitored using a variety of commercial technologies and in-flight assessment tools. Significance: Our detailed testing protocol will provide valuable information for describing how and when spaceflight-induced muscle and aerobic based adaptations occur over the course of spaceflight missions up to and beyond 1 year. This information will be vital in the assessment as to whether humans can be physically ready for deep space exploration such as Mars missions with current technology, or if additional mitigation strategies are necessary.

Downs, M. E.↗

Investigation of Direct Force Control for Planetary Aerocapture at Neptune

In this work, a direct force control numerical predictor-corrector guidance architecture is developed to enable Neptune aerocapture using flight-heritage blunt body aeroshells. A linear aerodynamics model is formulated for a Mars Science Laboratory-derived aeroshell. The application of calculus of variations shows that the optimal angle of attack and side-slip angle control laws are bang-bang. A closed-loop numerical predictor-corrector direct force control guidance algorithm is developed and numerically simulated using the Program to Optimize Simulated Trajectories II. The Monte Carlo simulated trajectories are demonstrated to be robust to the modeled dispersions in aerodynamics, atmospheric density, and entry state. An aerocapture technology trade study demonstrates that blunt body direct force control aerocapture enables similar performance as slender body bank angle control but halves the peak g-loading.

Deshmukh, Rohan G.↗

Joining and Integration of Silicon Carbide-Based Ceramic Materials for Aerospace Applications: An Overview

In order to fully utilize silicon carbide-based ceramics and ceramic matrix composites (CMCs) for aerospace and ground based applications, advanced joining and integration technologies are critically needed for achieving large, complex shaped, and integrated components. Careful material selection of joining inter-layers needs to consider chemical and thermal compatibilities with the parent materials that are being joined. Also, optimization needs to be conducted to select the proper processing conditions for achieving robust joints that are well adhered, strong, uniform, crack free, and have minimal residual stresses. NASA GRC developed pressureless and pressure aided approaches for joining ceramics and CMCs include brazing, diffusion bonding, refractory eutectic phase joining, and Single-step Elevated Temperature (SET) Joining. For joining ceramics and CMCs to metals, several brazes have been utilized. Brazing approaches for joining ceramics and metals have also included tailored brazes with multiple interlayers and particle additions. An overview of the joining approaches will be provided. In addition, processing-microstructure-property relationships will be discussed.

Silicon carbide↗

Establishing and Maintaining the Digital Thread of Additively Manufactured Materials and Applications

Additive Manufacturing (AM) and Integrated Computational Materials Engineering (ICME) are complementary enabling technologies for design and manufacturing of “fit-for-purpose” materials. Both technologies will impact rapid material design, reduction in cost- and time-to-market for new applications, and discovery and implementation of new materials. An ICME approach to design, however, requires experimentally validated material models at multiple length and time scales, an integrated framework that can connect analysis tools with one another to ensure the digital thread of an application is maintained, and the manufacturing (e.g., AM) capability to leverage processing-structure-property-performance (PSPP) relationships to achieve spatially varying material properties where desired. AM enables the implementation of the design of an optimized, spatially varying microstructure through careful selection of the processing parameters used during an additively manufactured build. In order to establish these PSPP relations, a large amount of data is necessary, and that data must be properly captured, analyzed and maintained in an information management system that can establish the required traceability between various aspects of the design process to ensure an application’s digital thread is maintained (from design to end of life). Such an information management system must be able to capture feedstock material pedigree, resulting microstructure from various build parameters, subsequent mechanical properties derived from testing, developed material models, and enable spatial variations in material assignment in an engineering application. Furthermore, the information management system should be easily integrated with traditionally engineered materials in a single, centralized platform to enable an ICME optimization tool to explore both types of manufacturing processes. At NASA GRC, a robust, 21st century materials information management system has been previously developed with a focus towards enabling ICME. In this work, GRC’s ICME schema is extended to accommodate additively manufactured materials, enabling storage of both traditionally and additively manufactured materials in the same construct. The methodology for properly capturing additively manufactured materials across the entire material lifecycle is presented, following the previously established database best practices, as a potential framework for establishing PSPP relationships for additively manufactured materials and applying them to engineering applications.

Data management↗

Numerical study of proppant transport and settling processes in fractures

Reservoir stimulation by creating hydraulically conductive fractures is the key step for enabling enhanced geothermal systems (EGS). The effectiveness of stimulation is significantly influenced by the deposition of proppant inside induced fractures. The transportation and settling of proppant in a propagating fracture is controlled by a multitude of operational and physical parameters, including the fracturing fluid rheology, injection rate, proppant concentration, fracture length/aperture evolution, proppant size/density/shape, etc. A numerical tool that robustly and efficiently accounts for all important attributes can facilitate the design and optimization of reservoir stimulation. This study presents the novel computational tool ELK (ELectrical fracKing) developed for the numerical simulation of proppant-fluid mixture circulation in a fractured geothermal reservoir. We enriched the MOOSE-based PorousFlow module with a suite of equations to consider the fluid-proppant mixture with particle-particle/fluid interactions, which include gravitational settling, particle convection, particle hampering, and strong density and viscosity contrasts. The computational tool is validated by comparing the predicted proppant bed evolution against two different laboratory scale experiments of proppant transport in a fixed aperture channel. Further parameter studies were performed, and the modeling results show that the proppant deposition is determined by the mixing characteristics and settling of the particles from the slurry. Concentration-dependent density and viscosity lead to an inhomogeneous distribution of the proppant, particle collision, and enhanced settling at the bottom of the fractures. Preliminary coupling with dynamic fracture propagation shows promising results and will be further developed to simulate hydraulic stimulation at high fidelity.

15 GEOTHERMAL ENERGY↗

Building Automation

In this chapter, we focus on both need-based and vision-based control innovation for building automation for HVAC systems. After providing a brief background that describes different HVAC architectures and products, we describe the control challenges and opportunities from a needs-based point of view, at the equipment level, the systems level, and the building level. At the equipment level, increased use of continuously variable actuation such as variable speed compressors and fans, requires application of robust multivariable control that must consider various types of nonlinear behavior across increasingly larger operating envelopes. The objective at this level is to achieve robust and energy efficient operation. At the system level, coupled and interactive dynamics among subsystems are increasingly important to consider, and functional integration of these subsystems, along with set points and operating schedules are designed to minimize energy consumption and improve occupant comfort. At the building level, issues such as integration among other building systems, such as the building envelope and the electric grid, offer opportunities to develop new types of demand response and grid-interactive behaviors and technologies. At the higher levels, system dynamics and robust stability are less of an issue, similar to process control applications, while optimization and integration are more important, although dynamic stability is increasing an issue at the higher levels too. From a vision-driven innovation point of view, we describe three areas that will require sustained research efforts and will eventually impact building automation: Digital Twins, Model Predictive Control, and Grid Interactive Buildings.

Bortoff, Scott↗

Scaling Subspace-Driven Approaches Using Information Fusion

In this work, we seek to exploit the deep structure of multi-modal data to robustly exploit the group subspace distribution of the information using the Convolutional Neural Networks (CNNs) formalism. Upon unfolding the set of subspaces constituting each data modality, and learning their corresponding encoders, an optimized integration of the generated inherent information is carried out to yield a characterization of various classes. Referred to as deep Multimodal Robust Group Subspace Clustering (DRoGSuRe), this approach is compared against the independently developed state-of-the-art approach named Deep Multimodal Subspace Clustering (DMSC). Experiments on different multimodal datasets show that our approach is competitive and more robust in the presence of noise.

Ghanem, Sally↗

Two-Stage Distributionally Robust Conic Linear Programming over 1-Wasserstein Balls

Here, this paper studies two-stage distributionally robust conic linear programming under constraint uncertainty over type-1 Wasserstein balls. We present optimality conditions for the dual of the worst-case expectation problem, which characterizes worst-case uncertain parameters for its inner maximization problem. This condition offers an alternative proof, a counterexample, and an extension to previous works. Additionally, the condition highlights the potential advantage of a specific distance metric for out-of-sample performance, as exemplified in a numerical study on a facility location problem with demand uncertainty. Furthermore, cutting-plane-based algorithms, equipped with a unified scenario generation framework, are proposed for addressing both unbounded support and second-stage dual feasible regions, with a finite convergence proof under less stringent assumptions.

Wasserstein↗

Fixed-Order Mixed Norm Designs for Building Vibration Control

This study investigates the use of H2, mu-synthesis, and mixed H2/mu methods to construct full order controllers and optimized controllers of fixed dimensions. The benchmark problem definition is first extended to include uncertainty within the controller bandwidth in the form of parametric uncertainty representative of uncertainty in the natural frequencies of the design model. The sensitivity of H2 design to unmodeled dynamics and parametric uncertainty is evaluated for a range of controller levels of authority. Next, mu-synthesis methods are applied to design full order compensators that are robust to both unmodeled dynamics and to parametric uncertainty. Finally, a set of mixed H2/mu compensators are designed which are optimized for a fixed compensator dimension. These mixed norm designs recover the H2 design performance levels while providing the same levels of robust stability as the mu designs. It is shown that designing with the mixed norm approach permits higher levels of controller authority for which the H2 designs are destabilizing. The benchmark problem is that of an active tendon system. The controller designs are all based on the use of acceleration feedback.

Whorton, Mark S.↗

User-Centric Communication With Aerial Network for 6G: A Reinforcement Learning Approach

Meeting the diverse needs of user verticals requires innovative cellular architectures that can offer additional degrees of freedom to provide on-demand services. The terrestrial user-centric radio access network (UC-RAN) stands out as an excellent choice for this purpose. However, a drawback of UC-RAN is its tendency to prioritize high-priority verticals, often resulting in a subpar quality of experience for low-priority verticals. This issue is particularly exacerbated in hotspot areas. Here, to address this problem, we introduce an aerial network integrated with terrestrial UC-RAN to provide coverage to users which are not served by the terrestrial network. Furthermore, we analyze the impact of key configuration and optimization parameters (COPs), such as location, transmit power, altitude, and beamwidth of aerial base stations (ABSs) on system key performance indicators (KPIs), such as coverage, latency satisfaction, average spectral efficiency, and energy efficiency. We formulate a robust multiobjective function to maximize these KPIs without biasing toward any specific KPI(s). Finally, we propose a deep reinforcement learning optimization framework based on the state-of-the-art soft actor-critic algorithm to control ABS COPs and optimize system KPIs. Experimental evaluations demonstrate that the proposed optimization framework can converge to near-optimal solutions derived from the pseudo brute force in a few thousand epochs.

6G↗