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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.
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The recently developed nonlinear servomechanism theory is applied to the attitude control of large maneuvering spacecraft subject to sinusoidal disturbances and parametric uncertainties.
This paper proposes a methodology for the analysis and design optimization of models subject to parametric uncertainty, where hard inequality constraints are present. Hard constraints are those that must be satisfied for all parameter realizations prescribed by the uncertainty model. Emphasis is given to uncertainty models prescribed by norm-bounded perturbations from a nominal parameter value, i.e., hyper-spheres, and by sets of independently bounded uncertain variables, i.e., hyper-rectangles. These models make it possible to consider sets of parameters having comparable as well as dissimilar levels of uncertainty. Two alternative formulations for hyper-rectangular sets are proposed, one based on a transformation of variables and another based on an infinity norm approach. The suite of tools developed enable us to determine if the satisfaction of hard constraints is feasible by identifying critical combinations of uncertain parameters. Since this practice is performed without sampling or partitioning the parameter space, the resulting assessments of robustness are analytically verifiable. Strategies that enable the comparison of the robustness of competing design alternatives, the approximation of the robust design space, and the systematic search for designs with improved robustness characteristics are also proposed. Since the problem formulation is generic and the solution methods only require standard optimization algorithms for their implementation, the tools developed are applicable to a broad range of problems in several disciplines.
This paper proposes a framework for the analysis and design optimization of models subject to parametric uncertainty where design requirements in the form of inequality constraints are present. Emphasis is given to uncertainty models prescribed by norm bounded perturbations from a nominal parameter value and by sets of componentwise bounded uncertain variables. These models, which often arise in engineering problems, allow for a sharp mathematical manipulation. Constraints can be implemented in the hard sense, i.e., constraints must be satisfied for all parameter realizations in the uncertainty model, and in the soft sense, i.e., constraints can be violated by some realizations of the uncertain parameter. In regard to hard constraints, this methodology allows (i) to determine if a hard constraint can be satisfied for a given uncertainty model and constraint structure, (ii) to generate conclusive, formally verifiable reliability assessments that allow for unprejudiced comparisons of competing design alternatives and (iii) to identify the critical combination of uncertain parameters leading to constraint violations. In regard to soft constraints, the methodology allows the designer (i) to use probabilistic uncertainty models, (ii) to calculate upper bounds to the probability of constraint violation, and (iii) to efficiently estimate failure probabilities via a hybrid method. This method integrates the upper bounds, for which closed form expressions are derived, along with conditional sampling. In addition, an l(sub infinity) formulation for the efficient manipulation of hyper-rectangular sets is also proposed.
This thesis discusses application of a robust constrained optimization approach to control design to develop an Auto Balancing Controller (ABC) for a centrifuge rotor to be implemented on the International Space Station. The design goal is to minimize a performance objective of the system, while guaranteeing stability and proper performance for a range of uncertain plants. The Performance objective is to minimize the translational response of the centrifuge rotor due to a fixed worst-case rotor imbalance. The robustness constraints are posed with respect to parametric uncertainty in the plant. The proposed approach to control design allows for both of these objectives to be handled within the framework of constrained optimization. The resulting controller achieves acceptable performance and robustness characteristics.
G-Sample is designed for sample collection missions to identify the presence and quantity of sample material gathered by spacecraft equipped with end effectors. The software method uses a maximum-likelihood estimator to identify the collected sample's mass based on onboard force-sensor measurements, thruster firings, and a dynamics model of the spacecraft. This makes sample mass identification a computation rather than a process requiring additional hardware. Simulation examples of G-Sample are provided for spacecraft model configurations with a sample collection device mounted on the end of an extended boom. In the absence of thrust knowledge errors, the results indicate that G-Sample can identify the amount of collected sample mass to within 10 grams (with 95-percent confidence) by using a force sensor with a noise and quantization floor of 50 micrometers. These results hold even in the presence of realistic parametric uncertainty in actual spacecraft inertia, center-of-mass offset, and first flexibility modes. Thrust profile knowledge is shown to be a dominant sensitivity for G-Sample, entering in a nearly one-to-one relationship with the final mass estimation error. This means thrust profiles should be well characterized with onboard accelerometers prior to sample collection. An overall sample-mass estimation error budget has been developed to approximate the effect of model uncertainty, sensor noise, data rate, and thrust profile error on the expected estimate of collected sample mass.
The initial X-43A flight test, June 2, 2001, resulted in a mishap and loss of the vehicle. A mishap investigation board (MIB) report and findings, including the established root cause, were publicly released on July, 23, 2003. The X-43A Flight 1 Hyper-X Launch Vehicle (HXLV) failed because the vehicle control system design was deficient for the trajectory flown due to inaccurate analytical models (Pegasus heritage and HXLV specific), which overestimated the (control) system margin ? X-43A Mishap Investigation Report, Vol. I. ? included as Reference 1. Several specific errors were noted, 1) HXLV aerodynamics ? failure to model changes to wing, fin and rudder airfoil shapes due to addition of thermal protection system (TPS); 2) Fin actuation system (FAS) modeling ? under prediction of the control surface hinge moments and FAS compliance; and 3) Parametric uncertainties ? insufficient variation in the aerodynamic, FAS and control system models. In response to the MIB findings, the X-43A program has been working RTF through an approved Corrective Action Plan (CAP) over the last two years.
The Ares I launch vehicle represents a challenging flex-body structural environment for flight control system design. This paper presents a design methodology for employing numerical optimization to develop the Ares I flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics, propellant slosh, and flex. Under the assumption that the Ares I time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time launch control systems in the presence of parametric uncertainty. Flex filters in the flight control system are designed to minimize the flex components in the error signals before they are sent to the attitude controller. To ensure adequate response to guidance command, step response specifications are introduced as constraints in the optimization problem. Imposing these constraints minimizes performance degradation caused by the addition of the flex filters. The first stage bending filter design achieves stability by adding lag to the first structural frequency to phase stabilize the first flex mode while gain stabilizing the higher modes. The upper stage bending filter design gain stabilizes all the flex bending modes. The flight control system designs provided here have been demonstrated to provide stable first and second stage control systems in both Draper Ares Stability Analysis Tool (ASAT) and the MSFC 6DOF nonlinear time domain simulation.
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.
The paper presents performance and robustness analysis of the modified reference model MRAC (model reference adaptive control) or M-MRAC in short, which differs from the conventional MRAC systems by feeding back the tracking error to the reference model. The tracking error feedback gain in concert with the adaptation rate provides an additional capability to regulate not only the transient performance of the tracking error, but also the transient performance of the control signal. This differs from the conventional MRAC systems, in which we have only the adaptation rate as a tool to regulate just the transient performance of the tracking error. It is shown that the selection of the feedback gain and the adaptation rate resolves the tradeoff between the robustness and performance in the sense that the increase in the feedback gain improves the behavior of the adaptive control signal, hence improves the systems robustness to time delays (or unmodeled dynamics), while increasing the adaptation rate improves the tracking performance or systems robustness to parametric uncertainties and external disturbances.
This paper examines the application of state-of-the-art coupled ablation and radiation simulations to highspeed sample return vehicles, such as those returning from Mars or an asteroid. A defining characteristic of these entries is that the surface recession rates and temperatures are driven by nonequilibrium convective and radiative heating through a boundary layer with significant surface blowing and ablation products. Measurements relevant to validating the simulation of these phenomena are reviewed and the Stardust entry is identified as providing the best relevant measurements. A coupled ablation and radiation flowfield analysis is presented that implements a finite-rate surface chemistry model. Comparisons between this finite-rate model and a equilibrium ablation model show that, while good agreement is seen for diffusion-limited oxidation cases, the finite-rate model predicts up to 50% lower char rates than the equilibrium model at sublimation conditions. Both the equilibrium and finite rate models predict significant negative mass flux at the surface due to sublimation of atomic carbon. A sensitivity analysis to flowfield and surface chemistry rates show that, for a sample return capsule at 10, 12, and 14 km/s, the sublimation rates for C and C3 provide the largest changes to the convective flux, radiative flux, and char rate. A parametric uncertainty analysis of the radiative heating due to radiation modeling parameters indicates uncertainties ranging from 27% at 10 km/s to 36% at 14 km/s. Applying the developed coupled analysis to the Stardust entry results in temperatures within 10% of those inferred from observations, and final recession values within 20% of measurements, which improves upon the 60% over-prediction at the stagnation point obtained through an uncoupled analysis. Emission from CN Violet is shown to be over-predicted by nearly and order-of-magnitude, which is consistent with the results of previous independent analyses. Finally, the coupled analysis is applied to a 14 km/s Earth entry representative of a Mars sample return. Although the radiative heating provides a larger fraction of the total heating, the influence of ablation and radiation on the flowfield are shown to be similar to Stardust.
The Morpheus Lander is a vertical takeoff and landing test bed vehicle developed to demonstrate the system performance of the Guidance, Navigation and Control (GN&C) system capability for the integrated autonomous landing and hazard avoidance system hardware and software. The Morpheus flight control system design must be robust to various mission profiles. This paper presents a design methodology for employing numerical optimization to develop the Morpheus flight control system. The design objectives include attitude tracking accuracy and robust stability with respect to rigid body dynamics and propellant slosh. Under the assumption that the Morpheus time-varying dynamics and control system can be frozen over a short period of time, the flight controllers are designed to stabilize all selected frozen-time control systems in the presence of parametric uncertainty. Both control gains in the inner attitude control loop and guidance gains in the outer position control loop are designed to maximize the vehicle performance while ensuring robustness. The flight control system designs provided herein have been demonstrated to provide stable control systems in both Draper Ares Stability Analysis Tool (ASAT) and the NASA/JSC Trick-based Morpheus time domain simulation.
This paper presents an overview of the analysis and measurements of equilibrium radiation obtained in the NASA Ames Research Center's Electric Arc Shock Tube (EAST) facility as a part of recent testing aimed at reaching shock velocities up to 15.5 km/s. The goal of these experiments was to measure the level of radiation encountered during high speed Earth entry conditions, such as would be relevant for an asteroid, inter-planetary or lunar return mission. These experiments provide the first spectrally and spatially resolved data for high speed Earth entry and cover conditions ranging from 9.5 to 15.5 km/s at 13.3 and 26.6 Pa (0.1 and 0.2 Torr). The present analysis endeavors to provide a validation of shock tube radiation measurements and simulations at high speed conditions. A comprehensive comparison between the spectrally resolved absolute equilibrium radiance measured in EAST and the predictive tools, NEQAIR and HARA, is presented. In order to provide a more accurate representation of the agreement between the experimental and simulation results, the integrated value of radiance has been compared across four spectral regions (VUV, UV/Vis, Vis/NIR and IR) as a function of velocity. Results have generally shown excellent agreement between the two codes and EAST data for the Vis through IR spectral regions, however, discrepancies have been identified in the VUV and parts of the UV spectral regions. As a result of the analysis presented in this paper, an updated parametric uncertainty for high speed radiation in air has been evaluated to be [9.0%, -6.3%]. Furthermore, due to the nature of the radiating environment at these high shock speeds, initial calculations aimed at modeling phenomena that become more significant with increasing shock speed have been performed. These phenomena include analyzing the radiating species emitting ahead of the shock and the increased significance of radiative cooling mechanisms.
Responses to challenges associated with verification and validation (V&V) of Space Launch System (SLS) structural dynamics models are presented in this paper. Four methodologies addressing specific requirements for V&V are discussed. (1) Residual Mode Augmentation (RMA), which has gained acceptance by various principals in the NASA community, defines efficient and accurate FEM modal sensitivity models that are useful in test-analysis correlation and reconciliation and parametric uncertainty studies. (2) Modified Guyan Reduction (MGR) and Harmonic Reduction (HR, introduced in 1976), developed to remedy difficulties encountered with the widely used Classical Guyan Reduction (CGR) method, are presented. MGR and HR are particularly relevant for estimation of "body dominant" target modes of shell-type SLS assemblies that have numerous "body", "breathing" and local component constituents. Realities associated with configuration features and "imperfections" cause "body" and "breathing" mode characteristics to mix resulting in a lack of clarity in the understanding and correlation of FEM- and test-derived modal data. (3) Mode Consolidation (MC) is a newly introduced procedure designed to effectively "de-feature" FEM and experimental modes of detailed structural shell assemblies for unambiguous estimation of "body" dominant target modes. Finally, (4) Experimental Mode Verification (EMV) is a procedure that addresses ambiguities associated with experimental modal analysis of complex structural systems. Specifically, EMV directly separates well-defined modal data from spurious and poorly excited modal data employing newly introduced graphical and coherence metrics.
The paper presents a modified model reference adaptive control (M-MRAC) for multi-input multi-output nonlinear dynamical systems with time varying parametric uncertainties and bounded external disturbances. It uses a prediction model to rapidly generate adaptive estimates of the system's uncertainties with adjustable errors that converge to a small neighborhood of the origin. A sufficient condition is derived to specify the region of attraction in the space of initialization errors, design parameters and external commends. The approach is applied to thrust controlled multi-rotor air vehicles operating in an urban environment. It is shown that the designed controller can provide a good tracking of a given trajectory in the unknown urban wind field, assuming that the maximum thrust generated by the rotors is known. The performance of the algorithms are demonstrated in simulations.
Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.
Numerical models of hypersonic flows rely on chemistry data inferred from experiments and quantum calculations. Experiments from NASA's Electric Arc Shock Tube (EAST) measure the spectral emission of strong shocks in pure nitrogen flows. These spectral profiles are only approximately captured by numerical simulations. To address these discrepancies, one wishes to calibrate some of the chemical parameters to better match experiment. Because there are hundreds of parameters in the numerical model, a sensitivity analysis was carried out on the entire chemistry database to determine which parameters are most important to analyze in the future. In order to perform this work it was necessary to generate a consistent chemical database that interfaced with both the CFD and line-by-line radiation solver. Using Monte Carlo methods, the total Sobol index was calculated for important parameters. Twenty parameters were identified as important across the nitrogen system. However, it was noted that in some spectral regions, the parametric uncertainty was unable to bound EAST measurements. Further improvements could be made by increasing the parameter uncertainties or addressing other sources of modeling error.
The quantification of model uncertainty is becoming increasingly important as robust control is an important tool for control system design and analysis. This paper presents an algorithm that effectively characterizes the model uncertainty in terms of parametric and nonparametric uncertainties. The algorithm utilizes the frequency domain model error which is estimated from the spectra of output error and input data. The parametric uncertainty is represented as an interval transfer function while the nonparametric uncertainty is bounded by a designed error bound transfer function. Both discrete and continuous systems are discussed in this paper. The algorithm is applied to the Mini-Mast example, and the detail analysis is given.
A parametric pretest uncertainty analysis has been performed for a chemical rocket engine test at a unique 1000:1 area ratio altitude test facility. Results from the parametric study provide the error limits required in order to maintain a maximum uncertainty of 1 percent on specific impulse. Equations used in the uncertainty analysis are presented.