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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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At least 73 records · Page 4

System identification of the Large-Angle Magnetic Suspension Test Fixture (LAMSTF)

The Large-Angle Magnetic Suspension Test Fixture (LAMSTF), a laboratory-scale research project to demonstrate the magnetic suspension of objects over wide ranges of attitudes, has been developed. This system represents a scaled model of a planned Large-Gap Magnetic Suspension System (LGMSS). The LAMSTF consists of a small cylindrical permanent magnet suspended element which is levitated above a planar array of five electromagnets mounted in a circular configuration. The cylinder is a rigid body and can be controlled to move in five independent degrees of freedom. Six position variables are sensed indirectly by using infrared light-emitting diodes and light-receiving phototransistors. The motion of the suspended cylinder is in general nonlinear and hence only the linear, time-invariant perturbed motion about an equilibrium state is considered. One of the main challenges in this project is the control of the suspended element over a wide range of orientations. An accurate dynamic model plays an essential role in controller design. The analytical model is first derived and open-loop characteristics discussed. The system is shown to be highly unstable and requires feedback control for system identification. Projection filters are first proposed to identify the state space model from closed-loop input/output test data in the time domain. This method is then extended to identify linear systems from the frequency test data. A canonical transformation matrix is also derived to transform the identified state space model into the physical coordinate. The LAMSTF system is stabilized by using a linear quadratic regulator (LQR) feedback controller for closed-loop identification. The rate information is obtained by calculating the back difference of the sensed position signals. Only the closed-loop random input/output data are recorded. Preliminary results from numerical simulations demonstrate that the identified system model is fairly accurate from either time domain or frequency-domain data. Experiments will be performed to validate the proposed closed-loop identification algorithms.

Huang, Jen-Kuang↗

Experimental Feedback Control of Flow Induced Cavity Tones

An experimental study of the application of discrete-time, linear quadratic control design methods to the cavity tone problem is described. State space models of the dynamics from a synthetic jet actuator at the leading edge of the cavity to two pressure sensors in the cavity were computed from experimental data. Variations in model order, control order, control bandwidth, and properties of a Kalman state estimator were studied. Feedback control reduced the levels of multiple cavity tones at Mach 0.275, 0.35, and 0.45. Closed loop performance was often limited by excitation of sidebands of cavity tones, and creation of new tones in the spectrum. State space models were useful for explaining some of these limitations, but were not able to account for non-linear dynamics, such as interactions between tones at different frequencies.

Cabell, Randolph H.↗

Frequency domain state-space system identification

An algorithm for identifying state-space models from frequency response data of linear systems is presented. A matrix-fraction description of the transfer function is employed to curve-fit the frequency response data, using the least-squares method. The parameters of the matrix-fraction representation are then used to construct the Markov parameters of the system. Finally, state-space models are obtained through the Eigensystem Realization Algorithm using Markov parameters. The main advantage of this approach is that the curve-fitting and the Markov parameter construction are linear problems which avoid the difficulties of nonlinear optimization of other approaches. Another advantage is that it avoids windowing distortions associated with other frequency domain methods.

Chen, Chung-Wen↗

Dynamic Forms: Application to Aircraft Guidance - Part 2

The paper describes a method for guiding a dynamic system through a given set of points. The paradigm is a fully automatic aircraft subject to air traffic control (ATC). The ATC provides a sequence of waypoints through which the aircraft trajectory must pass. The waypoints typically specify time, position, and velocity. The guidance problem is to synthesize a system state trajectory that satisfies both the ATC and aircraft constraints. Complications arise because the controlled process is multidimensional, multiaxis, nonlinear, highly coupled, and the state space is not flat. In addition, there is a multitude of operating modes, which may number in the hundreds. Each such mode defines a distinct state space model of the process by specifying the state space coordinatization, the partition of the controls into active controls and configuration controls, and the output map. Furthermore, mode transitions are required to be smooth. The proposed guidance algorithm is based on the inversion of the pure feedback approximation, followed by correction for the effects of zero dynamics. The paper describes the structure and major modules of the algorithm, and the performance is illustrated by several example aircraft maneuvers.

Meyer, George↗

Guidance of Nonlinear Systems

The paper describes a method for guiding a dynamic system through a given set of points. The paradigm is a fully automatic aircraft subject to air traffic control (ATC). The ATC provides a sequence of way points through which the aircraft trajectory must pass. The way points typically specify time, position, and velocity. The guidance problem is to synthesize a system state trajectory which satisfies both the ATC and aircraft constraints. Complications arise because the controlled process is multi-dimensional, multi-axis, nonlinear, highly coupled, and the state space is not flat. In addition, there is a multitude of possible operating modes, which may number in the hundreds. Each such mode defines a distinct state space model of the process by specifying the state space coordination, the partition of the controls into active controls and configuration controls, and the output map. Furthermore, mode transitions must be smooth. The guidance algorithm is based on the inversion of the pure feedback approximations, which is followed by iterative corrections for the effects of zero dynamics. The paper describes the structure and modules of the algorithm, and the performance is illustrated by several example aircraft maneuvers.

Meyer, George↗

Guidance of Nonlinear Systems

The paper describes a method for guiding a dynamic system through a given set of points. The paradigm is a fully automatic aircraft subject to air traffic control (ATC). The ATC provides a sequence of way points through which the aircraft trajectory must pass. The way points typically specify time, position, and velocity. The guidance problem is to synthesize a system state trajectory which satisfies both the ATC and aircraft constraints. Complications arise because the controlled process is multi-dimensional, multi-axis, nonlinear, highly coupled, and the state space is not flat. In addition, there is a multitude of possible operating modes, which may number in the hundreds. Each such mode defines a distinct state space model of the process by specifying the state space coordinatization, the partition of the controls into active controls and configuration controls, and the output map. Furthermore, mode transitions must be smooth. The guidance algorithm is based on the inversion of the pure feedback approximations, which is followed by iterative corrections for the effects of zero dynamics. The paper describes the structure and modules of the algorithm, and the performance is illustrated by several example aircraft maneuvers.

Meyer, George↗

Evaluation of Aeroservoelastic Effects on Flutter

The HSCT Flight Controls Group is developing a longitudinal control law, known as Gamma-dot / V, for the NASA HSR program. Currently, this control law is based on a quasi-steady aeroelastic (QSAE) model of the vehicle. This control law was implemented into the p-k flutter analysis process for closed loop aeroservoelastic analysis. The available flexible models, developed for the TCA aeroelastic analysis, were used to assess the effect of control laws on flutter at several different Mach numbers and mass conditions. Significant structures and flight control system interaction was observed during the initial assessment. Figures 1 and 2 present a summary of the effect of total closed loop gain and phase on flutter mechanisms, based on ideal sensors and real sensors, for Mach 0.95 and mass M02 condition. Control laws based on ideal sensors gave rise to increased coupling between the rigid body short period mode and the first symmetric elastic mode. This reduced the stability margins for the first elastic mode and does not meet the required 6 dB gain margin requirement. The effect of "real" sensors significantly increased the structures and control system interactions. This caused the elastic,modes to be highly unstable throughout most of the flight envelope. State-space models were developed for several conditions and then MATLAB program was used for the aeroservoelastic stability analysis. These results provided an independent verification of the p-k flutter analysis findings. Good overall agreement was observed between the p-k flutter analysis and state-space model results for both damping and frequency comparisons. These results are also included in this document.

Nagaraja, K. S.↗

Neural Ordinary Differential Equations for Nonlinear System Identification

Neural ordinary differential equations (NODE) have been recently proposed as a promising approach for nonlinear system identification tasks. In this work, we systematically compare their predictive performance with current state-of-the-art nonlinear and classical linear methods. In particular, we present a quantitative study comparing NODE's performance against neural state-space models and classical linear system identification methods and evaluate their inference speed and prediction performance on open-loop errors across eight different dynamical systems. The experiments show that NODEs can consistently improve the prediction accuracy by order of magnitude compared to benchmark methods. Besides improved accuracy, we also observed that NODEs are less sensitive to hyperparameters compared to neural state-space models by paying the cost of increased computation at the inference time.

machine leaning, system identification, physics in↗

Time simulation of flutter with large stiffness changes

Time simulation of flutter, involving large local structural changes, is formulated with a state-space model that is based on a relatively small number of generalized coordinates. Free-free vibration modes are first calculated for a nominal finite-element model with relatively large fictitious masses located at the area of structural changes. A low-frequency subset of these modes is then transformed into a set of structural modal coordinates with which the entire simulation is performed. These generalized coordinates and the associated oscillatory aerodynamic force coefficient matrices are used to construct an efficient time-domain, state-space model for a basic aeroelastic case. The time simulation can then be performed by simply changing the mass, stiffness, and damping coupling terms when structural changes occur. It is shown that the size of the aeroelastic model required for time simulation with large structural changes at a few apriori known locations is similar to that required for direct analysis of a single structural case. The method is applied to the simulation of an aeroelastic wind-tunnel model. The diverging oscillations are followed by the activation of a tip-ballast decoupling mechanism that stabilizes the system but may cause significant transient overshoots.

Karpel, Mordechay↗

Time simulation of flutter with large stiffness changes

Time simulation of flutter, involving large local structural changes, is formulated with a state-space model that is based on a relatively small number of generalized coordinates. Free-free vibration modes are first calculated for a nominal finite-element model with relatively large fictitious masses located at the area of structural changes. A low-frequency subset of these modes is then transformed into a set of structural modal coordinates with which the entire simulation is performed. These generalized coordinates and the associated oscillatory aerodynamic force coefficient matrices are used to construct an efficient time-domain, state-space model for basic aeroelastic case. The time simulation can then be performed by simply changing the mass, stiffness and damping coupling terms when structural changes occur. It is shown that the size of the aeroelastic model required for time simulation with large structural changes at a few a priori known locations is similar to that required for direct analysis of a single structural case. The method is applied to the simulation of an aeroelastic wind-tunnel model. The diverging oscillations are followed by the activation of a tip-ballast decoupling mechanism that stabilizes the system but may cause significant transient overshoots.

Karpel, M.↗

Time dependent supervisory control update with FARM using rolling window

This report describes improvements to the Feasible Actuator Range Modifier (FARM) component of the RAVEN-based HYBRID framework for analysis of Integrated Energy Systems (IES). FARM supports the HERON plug-in that solves the power dispatch problem. The solution to the dispatch problem involves economically optimal dispatches that satisfy limits on production variables and their rates of variation (explicit constraints) as well as process variables tied to the service life of equipment (implicit constraints). FARM serves to validate or confirm that a HERON solution for explicit constraints also satisfies the implicit constraints. FARM-alpha was released by Argonne National Laboratory in January 2021 followed by FARM-Beta in January 2022 with the latter providing increased flexibility for the user. In this report, FARM-Gamma, the latest version of the code, is described. The major improvement is the implementation of a system identification algorithm based on the Dynamic Mode Decomposition with Control (DMDc) coupled with a “Rolling Window” scheme that allows obtaining linear time-varying state-space models. This feature equips FARM with the most accurate approximation of system dynamics, and it relieves the user from the burden of performing an exhaustive off-line characterization of the dynamics. FARM-Gamma capabilities are assessed by solving the power dispatch problem for a representative IES unit. The simulation times corresponding to the different releases are estimated and compared. These values capture the increasing computational burden of the successively higher fidelity state-space models adopted by FARM-Alpha, FARM-Beta and FARM-Gamma. The code implementation provides significant flexibility, i.e., the user can always select the most suitable version of FARM according to the problem to be solved and the available computational resources. It is anticipated that FARM will play a role in addressing several future IES applications. We outline how it can support the coordinated management and safe operation of a nuclear plant coupled to industrial processes to produce hydrogen and synfuels.

21 SPECIFIC NUCLEAR REACTORS AND ASSOCIATED PLANTS↗

Control Law Design in a Computational Aeroelasticity Environment

A methodology for designing active control laws in a computational aeroelasticity environment is given. The methodology involves employing a systems identification technique to develop an explicit state-space model for control law design from the output of a computational aeroelasticity code. The particular computational aeroelasticity code employed in this paper solves the transonic small disturbance aerodynamic equation using a time-accurate, finite-difference scheme. Linear structural dynamics equations are integrated simultaneously with the computational fluid dynamics equations to determine the time responses of the structure. These structural responses are employed as the input to a modern systems identification technique that determines the Markov parameters of an "equivalent linear system". The Eigensystem Realization Algorithm is then employed to develop an explicit state-space model of the equivalent linear system. The Linear Quadratic Guassian control law design technique is employed to design a control law. The computational aeroelasticity code is modified to accept control laws and perform closed-loop simulations. Flutter control of a rectangular wing model is chosen to demonstrate the methodology. Various cases are used to illustrate the usefulness of the methodology as the nonlinearity of the aeroelastic system is increased through increased angle-of-attack changes.

Newsom, Jerry R.↗

Estimating short-period dynamics using an extended Kalman filter

An extended Kalman filter is used to estimate the parameters of a low-order model from aircraft transient response data. The low-order model is a state-space model derived from the short-period approximation of the longitudinal aircraft dynamics. The model corresponds to the pitch rate to stick force transfer function currently used in flying qualities analysis. The parameters are estimated from flight data as well as from a 6-DOF nonlinear simulation of the aircraft. These two estimates are then compared, and the discrepancies noted. The low-order model is able to satisfactorily match both flight data and simulation data from a high-order computer simulation.

Bauer, Jeffrey E.↗

High-order state space simulation models of helicopter flight mechanics

This paper describes the formulation and validation of a high-order linearized mathematical model of helicopter flight mechanics, which includes rotor flap and lag degrees of freedom as well as inflow dynamics. The model is extracted numerically from an existing nonlinear, blade element, time simulation model. Extensive modifications in the formulation and solution process of the nonlinear model, required for a theoretically rigorous linearization, are described in detail. The validation results show that the linearized model successfully captures the coupled rotor-fuselage dynamics in the frequency band most critical for the design of advanced flight control systems. Additional results quantify the extent to which the order of the model can be reduced without loss of fidelity.

Kim, Frederick D.↗

High-order state space simulation models of helicopter flight mechanics

This paper describes the formulation and validation of a high-order linearized mathematical model of helicopter flight mechanics, which includes rotor flap and lag degrees of freedom as well as inflow dynamics. The model is extracted numerically from an existing nonlinear, blade element, real-time simulation model. Extensive modifications in the formulation and solution process of the nonlinear model, required for a theoetically rigorous linearization, are described in detail. The validation results show that the linearized model successfully captures the coupled rotor-fuselage dynamics in the frequency band most critical for the design of advanced flight control systems. Additional results quantify the extent to which the order of the model can be reduced without loss of fidelity.

Kim, Frederick D.↗

Model Structures and Algorithms for Identification of Aerodynamic Models for Flight Dynamics Applications

This paper describes model structures and parameter estimation algorithms suitable for the identification of unsteady aerodynamic models from input-output data. The model structures presented are state space models and include linear time-invariant (LTI) models and linear parameter-varying (LPV) models. They cover a wide range of local and parameter dependent identification problems arising in unsteady aerodynamics and nonlinear flight dynamics. We present a residue algorithm for estimating model parameters from data. The algorithm can incorporate apriori information and is described in detail. The algorithms are evaluated on the F-16XL wind-tunnel test data from NAS Langley Research Center. Results of numerical evaluation are presented. The paper concludes with a discussion major issues and directions for future work.

Prasanth, Ravi K.↗

Modeling State-Space Aeroelastic Systems Using a Simple Matrix Polynomial Approach for the Unsteady Aerodynamics

A simple matrix polynomial approach is introduced for approximating unsteady aerodynamics in the s-plane and ultimately, after combining matrix polynomial coefficients with matrices defining the structure, a matrix polynomial of the flutter equations of motion (EOM) is formed. A technique of recasting the matrix-polynomial form of the flutter EOM into a first order form is also presented that can be used to determine the eigenvalues near the origin and everywhere on the complex plane. An aeroservoelastic (ASE) EOM have been generalized to include the gust terms on the right-hand side. The reasons for developing the new matrix polynomial approach are also presented, which are the following: first, the "workhorse" methods such as the NASTRAN flutter analysis lack the capability to consistently find roots near the origin, along the real axis or accurately find roots farther away from the imaginary axis of the complex plane; and, second, the existing s-plane methods, such as the Roger s s-plane approximation method as implemented in ISAC, do not always give suitable fits of some tabular data of the unsteady aerodynamics. A method available in MATLAB is introduced that will accurately fit generalized aerodynamic force (GAF) coefficients in a tabular data form into the coefficients of a matrix polynomial form. The root-locus results from the NASTRAN pknl flutter analysis, the ISAC-Roger's s-plane method and the present matrix polynomial method are presented and compared for accuracy and for the number and locations of roots.

Pototzky, Anthony S.↗

Evaluation of the Validity of Bio-Mathematical Models in Predicting Fatigue in an Operational Environment

During long-duration spaceflight missions, crewmembers and ground-support staff experience irregular sleep schedules, erratic natural light patterns, and high workload due to mission demands. Such conditions can cause circadian misalignment and sleep loss, which in turn cause deficits in cognitive performance. While bio-mathematical models have been implemented within workplace settings to predict fatigue profiles, the accuracy of sleep-wake models under conditions of non-traditional shiftwork is little known. Thus, the present study aims to evaluate the validity of four sleep-wake models (e.g., SAFTE-FAST, the Unified Model of Performance, the Adenosine-Circadian Model, and the State-Space Model) designed to predict human performance and fatigue levels against objective measures of performance in a spaceflight analog. To accomplish this aim, we will collect Psychomotor Vigilance Task (PVT) data from four crews (n=16) in the Human Exploration Research Analog (HERA) over 45 days. HERA is a closed, 3-story habitat at Johnson Space Center where inhabitants are exposed to extreme space exploration scenarios under varying sleep-wake conditions. The PVT is a simple reaction time test that involves minimal learning, making it sensitive to the effects of sleep loss and circadian misalignment. Findings from this study will help inform work scheduling and implementation of effective countermeasures (e.g., caffeine, lighting) to improve work efficiency and combat fatigue, as well as offer valuable insight into the applicability of bio-mathematical fatigue models in future space exploration missions.

fatigue↗