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At least 217 records · Page 12

Certainty Equivalence M-MRAC for Systems with Unmatched Uncertainties

The paper presents a certainty equivalence state feedback indirect adaptive control design method for the systems of any relative degree with unmatched uncertainties. The approach is based on the parameter identification (estimation) model, which is completely separated from the control design and is capable of producing parameter estimates as fast as the computing power allows without generating high frequency oscillations. It is shown that the system's input and output tracking errors can be systematically decreased by the proper choice of the design parameters.

Unmatched uncertainties↗

Dynamic Structural Fault Detection and Identification

Aircraft structures are designed to guarantee safety of flight in some required operational envelope. When the aircraft becomes structurally impaired, safety of flight may not be guaranteed within that previously safe operational envelope. In this case the safe operational envelope must be redefined in-flight and a means to prevent excursion from this new envelope must be implemented. A specific structural failure mode that may result in a reduced safe operating envelope, the exceedance of which could lead to catastrophic structural failure of the aircraft, will be addressed. The goal of the DFEAP program is the detection of this failure mode coupled with flight controls adaptation to limit critical loads in the damaged aircraft structure. The DFEAP program is working with an F/A-18 aircraft model. The composite wing skins are bonded to metallic spars in the wing substructure. Over time, it is possible that this bonding can deteriorate due to fatigue. In this case, the ability of the wing spar to transfer loading between the wing skins is reduced. This failure mode can translate to a reduced allowable compressive strain on the wing skin and could lead to catastrophic wing buckling if load limiting of the wing structure is not applied. The DFEAP program will make use of a simplified wing strain model for the healthy aircraft. The outputs of this model will be compared in real-time to onboard strain measurements at several locations on the aircraft wing. A damage condition is declared at a given location when the strain measurements differ sufficiently from the strain model. Parameter identification of the damaged structure wing strain parameters will be employed to provide load limiting control adaptation for the aircraft. This paper will discuss the simplified strain models used in the implementation and their interaction with the strain sensor measurements. Also discussed will be the damage detection and identification schemes employed and the means by which the damaged aircraft parameters will be used to provide load limiting that keeps the aircraft within the safe operational envelope.

Smith, Timothy↗

Modal identification using single-mode projection filters and comparison with ERA and MLE results

The Single-Mode Projection Filter (SPF) is a newly developed algorithm for eigensystem parameter identification from both analytical results and test data. The SPF is formulated with a single mode only and practical for parallel processing implementation. Explicit formulations of SPF are derived for the multi-input multi-output (MIMO) system by using the orthogonal matrices of the controllability and observability matrices in the general sense. The modal parameters of SPF are initially obtained from an analytical model in modal space. The experimental data are then processed through SPF to update its modal parameters and to minimize a cost function defined by the norm of an error matrix. The updated modal parameters represent the characteristics of the test data. A two-dimensional global minimum optimization algorithm is developed and applied for the filter update by using the interval analysis method. The SPF is developed based on a single-mode subsystem and identifies only one modal frequency and one modal damping within a specified region. For an n-modes structure, n SPF can be implemented for parallel processing to reduce the computational burden. The SPF is applied to analyze the simulated data for the MAST beam structure. The estimated modal parameters are comparable to those from the Eigensystem Realization Algorithm (ERA) and repeated modal frequencies are identified. The modal analysis of the Spacecraft Control Laboratory Experiment (SCOLE) data is also performed by using the ERA and the Maximum Likelihood Estimate (MLE). The result shows that the first five modal frequencies are very close from ERA and MLE. However, there are slight disparities in the damping rates and the computational burdens are quite different among these two algorithms.

Huang, Jen-Kuang↗

Experiments using least square lattice filters for the identification of structural dynamics

An approach for identifying the dynamics of large space structures is applied to a free-free beam. In this approach the system's order is determined on-line, along with mode shapes, using recursive lattice filters which provide a least square estimate of the measurement data. The mode shapes determined are orthonormal in the space of the measurements and, hence, are not the natural modes of the structure. To determine the natural modes of the structure, a method based on the fast Fourier transform is used on the outputs of the lattice filter. These natural modes are used to obtain the modal amplitude time series which provides the input data for an output error parameter identification scheme that identifies the ARMA parameters of the difference equation model of the modes. the approach is applied to both simulated and experimental data.

Sundararajan, N.↗

On-line parameter estimation using a high sensitivity estimator

An on-line parameter identification method is presented. The method is based on a recursive formulation of the maximum likelihood method, with a significant modification on the gains of the state estimator. In the conventional maximum likelihood method, the Kalman gains are used in the state estimator. This produces unbiased, minimum variance parameter estimates in the presence of process noise and measurement noise, but it also slows the convergence rate when the identification is done on-line. Here we suggest choosing the gains to maximize a measure of the sensitivities of the state estimates to parameter variations. One such criterion is to minimize the trace of the inverse information matrix. This increases the convergence rate significantly. After one or two time constants, the gains are switched to the Kalman values to assure unbiased, minimum-variance estimates. The state estimate will initially be nonoptimal, and may not be adequate for control purposes. In this case, a parallel Kalman filter which uses the identifier's parameter estimates can be used. This method is applied here for the identification of a simple first-order system, and for the identification of short-period stability derivatives of an F-8 aircraft from simulated data.

Mishne, D.↗

A method for high order linear system reduction and nonlinear system simplification

Least-squares-type algorithms for reducing the order of linear systems in the frequency domain and simplifying nonlinear systems in time domain are developed and demonstrated. The possible model structures are represented as nodes in a tree, and costs along the branches are assigned using the repeated-Gram-Schmidt orthogonalization procedure of Desrochers and Saridis (1980), permitting identification of the optimal n-term model by searching the tree to depth n, with no need for parameter identification. The efficiency and flexibility of the algorithms is shown in applications to the eighth-order linear system studied by Hsia (1972), a three-state eight-nonlinear-term aircraft-dynamics problem, and the related linear-controller problem (Garrard and Jordan, 1977).

Desrochers, A. A.↗

Active Aeroelastic Wing Aerodynamic Model Development and Validation for a Modified F/A-18A

A new aerodynamic model has been developed and validated for a modified F/A-18A used for the Active Aeroelastic Wing (AAW) research program. The goal of the program was to demonstrate the advantages of using the inherent flexibility of an aircraft to enhance its performance. The research aircraft was an F/A-18A with wings modified to reduce stiffness and a new control system to increase control authority. There have been two flight phases. Data gathered from the first flight phase were used to create the new aerodynamic model. A maximum-likelihood output-error parameter estimation technique was used to obtain stability and control derivatives. The derivatives were incorporated into the National Aeronautics and Space Administration F-18 simulation, validated, and used to develop new AAW control laws. The second phase of flights was used to evaluate the handling qualities of the AAW aircraft and the control law design process, and to further test the accuracy of the new model. The flight test envelope covered Mach numbers between 0.85 and 1.30 and dynamic pressures from 600 to 1250 pound-force per square foot. The results presented in this report demonstrate that a thorough parameter identification analysis can be used to improve upon models that were developed using other means. This report describes the parameter estimation technique used, details the validation techniques, discusses differences between previously existing F/A-18 models, and presents results from the second phase of research flights.

Cumming, Stephen B.↗

Active Aeroelastic Wing Aerodynamic Model Development and Validation for a Modified F/A-18A Airplane

A new aerodynamic model has been developed and validated for a modified F/A-18A airplane used for the Active Aeroelastic Wing (AAW) research program. The goal of the program was to demonstrate the advantages of using the inherent flexibility of an aircraft to enhance its performance. The research airplane was an F/A-18A with wings modified to reduce stiffness and a new control system to increase control authority. There have been two flight phases. Data gathered from the first flight phase were used to create the new aerodynamic model. A maximum-likelihood output-error parameter estimation technique was used to obtain stability and control derivatives. The derivatives were incorporated into the National Aeronautics and Space Administration F-18 simulation, validated, and used to develop new AAW control laws. The second phase of flights was used to evaluate the handling qualities of the AAW airplane and the control law design process, and to further test the accuracy of the new model. The flight test envelope covered Mach numbers between 0.85 and 1.30 and dynamic pressures from 600 to 1250 pound-force per square foot. The results presented in this report demonstrate that a thorough parameter identification analysis can be used to improve upon models that were developed using other means. This report describes the parameter estimation technique used, details the validation techniques, discusses differences between previously existing F/A-18 models, and presents results from the second phase of research flights.

Cumming, Stephen B.↗

Digital system identification and its application to digital flight control

On-line system identification of linear discrete systems for implementation in a digital adaptive flight controller is considered by the conventional extended Kalman filter and a decoupling process in which the linear state estimation problem and the linear parameter identification problem are each treated separately and alternately. Input requirements for parameter identifiability are established using the standard conditions of observability for a time variant system. Experimental results for simulated linearized lateral aircraft motion are included along with the effect of different initialization and updating procedures for the priming trajectory used by the filter.

Kotob, S.↗

System identification of large space structures

The paper deals with the problem of system identifiability for a linear dynamical system. Two theorems are given relating the sufficient condition of system identifiability for certain linear structures to the total number of inputs and outputs. The principle of least squares, that seeks the minimization of a cost function is employed to carry out the system identification process. To illustrate the concept of the paper, a structural model of a beam with point masses is examined. Parameter identification methods are studied and a random search technique is introduced.

Juang, J. N.↗

An adaptive control scheme for a flexible manipulator

The problem of controlling a single link flexible manipulator is considered. A self-tuning adaptive control scheme is proposed which consists of a least squares on-line parameter identification of an equivalent linear model followed by a tuning of the gains of a pole placement controller using the parameter estimates. Since the initial parameter values for this model are assumed unknown, the use of arbitrarily chosen initial parameter estimates in the adaptive controller would result in undesirable transient effects. Hence, the initial stage control is carried out with a PID controller. Once the identified parameters have converged, control is transferred to the adaptive controller. Naturally, the relevant issues in this scheme are tests for parameter convergence and minimization of overshoots during control switch-over. To demonstrate the effectiveness of the proposed scheme, simulation results are presented with an analytical nonlinear dynamic model of a single link flexible manipulator.

Yang, T. C.↗

Improved Estimates of Clear Sky Longwave Flux and Application to the Tropical Greenhouse Effect

The first objective of this investigation is to eliminate the clear-sky offset introduced by the scene-identification procedures developed for the Earth Radiation Budget Experiment (ERBE). Estimates of this systematic bias range from 10 to as high as 30 W/sq m. The initial version of the ScaRaB data is being processed with the original ERBE algorithm. Since the ERBE procedure for scene identification is based upon zonal flux averages, clear scenes with longwave emission well below the zonal mean value are mistakenly classified as cloudy. The erroneous classification is more frequent in regions with deep convection and enhanced mid- and upper-tropospheric humidity. We will develop scene identification parameters with zonal and/or time dependence to reduce or eliminate the bias in the clear- sky data. The modified scene identification procedure could be used for the ScaRaB-specific version of the Earth-radiation products. The second objective is to investigate changes in the clear-sky Outgoing Longwave Radiation (OLR) associated with decadal variations in the tropical and subtropical climate. There is considerable evidence for a shift in the climate state starting in approximately 1977. The shift is accompanied by higher SSTs in the equatorial Pacific, increased tropical convection, and higher values of atmospheric humidity. Other evidence indicates that the humidity in the tropical troposphere has been steadily increasing over the last 30 years. It is not known whether the atmospheric greenhouse effect has increased during this period in response to these changes in SST and precipitable water. We will investigate the decadal-scale fluctuations in the greenhouse effect using Nimbus-7, ERBE, and ScaRaB measurements spaning 1979 to the present. The data from the different satellites will be intercalibrated by comparison with model calculations based upon ship radiosonde observations. The fluxes calculated from the radiation model will also be used for validation of the ScaRaB fluxes.

Collins, W. D.↗

AAA gunnermodel based on observer theory

The Luenberger observer theory is used to develop a predictive model of a gunner's tracking response in antiaircraft artillery systems. This model is composed of an observer, a feedback controller and a remnant element. An important feature of the model is that the structure is simple, hence a computer simulation requires only a short execution time. A parameter identification program based on the least squares curve fitting method and the Gauss Newton gradient algorithm is developed to determine the parameter values of the gunner model. Thus, a systematic procedure exists for identifying model parameters for a given antiaircraft tracking task. Model predictions of tracking errors are compared with human tracking data obtained from manned simulation experiments. Model predictions are in excellent agreement with the empirical data for several flyby and maneuvering target trajectories.

Kou, R. S.↗

Aerodynamic coefficient estimation for dynamic wind tunnel models

Maximum likelihood parameter identification is used to estimate the aerodynamic coefficients of a 'flying' aircraft model which is mounted in a transonic wind tunnel by a system of cables and pulleys. The model's motion is governed by both cable and aerodynamic forces, where the parameters to be identified are functions of the aerodynamic forces but cable forces greatly predominate. The test data were successfully processed assuming a linear equation model in the identification procedure. In one instance, the procedure was able to detect a failing measurement instrument. The final parameter estimates are compared to estimates obtained in independent tests of a similar aircraft model.

Mohr, R. L.↗

Computation of the intervals of uncertainties about the parameters found for identification

A modeling method to calculate the intervals of uncertainty for parameters found by identification is described. The region of confidence and the general approach to the calculation of these intervals are discussed. The general subprograms for determination of dimensions are described. They provide the organizational charts for the subprograms, the tests carried out and the listings of the different subprograms.

Mereau, P.↗

Fundamental Rotorcraft Acoustic Modeling From Experiments (FRAME)

A new methodology is developed for the construction of helicopter source noise models for use in mission planning tools from experimental measurements of helicopter external noise radiation. The models are constructed by employing a parameter identification method to an assumed analytical model of the rotor harmonic noise sources. This new method allows for the identification of individual rotor harmonic noise sources and allows them to be characterized in terms of their individual non-dimensional governing parameters. The method is applied to both wind tunnel measurements and ground noise measurements of two-bladed rotors. The method is shown to match the parametric trends of main rotor harmonic noise, allowing accurate estimates of the dominant rotorcraft noise sources to be made for operating conditions based on a small number of measurements taken at different operating conditions. The ability of this method to estimate changes in noise radiation due to changes in ambient conditions is also demonstrated.

Greenwood, Eric↗

Analysis of pilot control strategy

Methods for nonintrusive identification of pilot control strategy and task execution dynamics are presented along with examples based on flight data. The specific analysis technique is Nonintrusive Parameter Identification Procedure (NIPIP), which is described in a companion user's guide (NASA CR-170398). Quantification of pilot control strategy and task execution dynamics is discussed in general terms followed by a more detailed description of how NIPIP can be applied. The examples are based on flight data obtained from the NASA F-8 digital fly by wire airplane. These examples involve various piloting tasks and control axes as well as a demonstration of how the dynamics of the aircraft itself are identified using NIPIP. Application of NIPIP to the AFTI/F-16 flight test program is discussed. Recommendations are made for flight test applications in general and refinement of NIPIP to include interactive computer graphics.

Heffley, R. K.↗