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At least 55 records · Page 3

On the application of a frequency domain controller design methodology to non-minimum phase and unstable systems

A frequency-domain design methodology was developed for controller synthesis maximizing the allowable size of an unknown-but-bounded disturbance while satisfying prespecified control and output constraints. The design technique, which accounts for bandwidth limitations, is based on mapping time-domain constraints into the frequency domain. Application of this technique to non-minimum-phase and/or unstable systems is presented. A non-minimum-phase, unstable SIMO (single-input/multiple-output) system is examined, and the results are compared to those obtained by the set-theoretic (ST) approach. The comparison shows that this methodology can yield controllers that reject step disturbances larger than those obtained by the ST method.

Sobhani, Massoud↗

A comparison of frequency domain design and l1-optimal control

A frequency-domain design methodology is applied to a DC motor-speed control system and the results are compared to those obtained using l1-optimal control theory (Pearson and Bamieh, 1990). Both methods synthesize controllers that maximize the allowable size of an unknown-but-bounded disturbance while satisfying prespecified constraints on the control, the control rate, and the outputs. The frequency-domain design technique in general results in much lower-order compensators than those required by the l1-optimal method for a given size of disturbance. Also, the design trade-offs regarding the bandwidth of the system, the size of the disturbance input, and the structural complexity of the controller transfer function become quite transparent.

Jayasuriya, Suhada↗

Frequency domain FIR and IIR adaptive filters

A discussion of the LMS adaptive filter relating to its convergence characteristics and the problems associated with disparate eigenvalues is presented. This is used to introduce the concept of proportional convergence. An approach is used to analyze the convergence characteristics of block frequency-domain adaptive filters. This leads to a development showing how the frequency-domain FIR adaptive filter is easily modified to provide proportional convergence. These ideas are extended to a block frequency-domain IIR adaptive filter and the idea of proportional convergence is applied. Experimental results illustrating proportional convergence in both FIR and IIR frequency-domain block adaptive filters is presented.

Lynn, D. W.↗

Time and Frequency-Domain Cross-Verification of SLS 6DOF Trajectory Simulations

The Space Launch System (SLS) Guidance, Navigation, and Control (GNC) team and its partners have developed several time- and frequency-based simulations for development and analysis of the proposed SLS launch vehicle. The simulations differ in fidelity and some have unique functionality that allows them to perform specific analyses. Some examples of the purposes of the various models are: trajectory simulation, multi-body separation, Monte Carlo, hardware in the loop, loads, and frequency domain stability analyses. While no two simulations are identical, many of the models are essentially six degree-of-freedom (6DOF) representations of the SLS plant dynamics, hardware implementation, and flight software. Thus at a high level all of those models should be in agreement. Comparison of outputs from several SLS trajectory and stability analysis tools are ongoing as part of the program's current verification effort. The purpose of these comparisons is to highlight modeling and analysis differences, verify simulation data sources, identify inconsistencies and minor errors, and ultimately to verify output data as being a good representation of the vehicle and subsystem dynamics. This paper will show selected verification work in both the time and frequency domain from the current design analysis cycle of the SLS for several of the design and analysis simulations. In the time domain, the tools that will be compared are MAVERIC, CLVTOPS, SAVANT, STARS, ARTEMIS, and POST 2. For the frequency domain analysis, the tools to be compared are FRACTAL, SAVANT, and STARS. The paper will include discussion of these tools including their capabilities, configurations, and the uses to which they are put in the SLS program. Determination of the criteria by which the simulations are compared (matching criteria) requires thoughtful consideration, and there are several pitfalls that may occur that can severely punish a simulation if not considered carefully. The paper will discuss these considerations and will present a framework for responding to these issues when they arise. For example, small event timing differences can lead to large differences in mass properties if the criteria are to measure those properties at the same time, or large differences in altitude if the criteria are to measure those properties when the simulation experiences a staging event. Similarly, a tiny difference in phase can lead to large gain margin differences for frequency-domain comparisons of gain margins.

Johnson, Matthew↗

Frequency-Domain Modeling Of Dynamics Of Helicopters

Method for identification, in frequency domain, of parameters of mathematical models of dynamical behaviors of helicopters combines and extends several existing methods. Focuses on linear-state-space models. Comprehensive frequency-domain method for identification of parameters of mathematical model helicopter involves synthesis of several prior methods.

Tischler, Mark B.↗

Asymptotic Waveform Evaluation (AWE) Technique for Frequency Domain Electromagnetic Analysis

The Asymptotic Waveform Evaluation (AWE) technique is applied to a generalized frequency domain electromagnetic problem. Most of the frequency domain techniques in computational electromagnetics result in a matrix equation, which is solved at a single frequency. In the AWE technique, the Taylor series expansion around that frequency is applied to the matrix equation. The coefficients of the Taylor's series are obtained in terms of the frequency derivatives of the matrices evaluated at the expansion frequency. The coefficients hence obtained will be used to predict the frequency response of the system over a frequency range. The detailed derivation of the coefficients (called 'moments') is given along with an illustration for electric field integral equation (or Method of Moments) technique. The radar cross section (RCS) frequency response of a square plate is presented using the AWE technique and is compared with the exact solution at various frequencies.

Cockrell, C. R.↗

Frequency-domain identification of XV-15 tilt-rotor aircraft dynamics

Frequency-domain methods are used to identify the open-loop dynamics of the XV-15 tilt-rotor aircraft from flight tests. Piloting and data analysis techniques are presented to determine frequency response plots and equivalent transfer function models. The open-loop pitch and roll dynamics for the hover flight condition exhibit unstable low-frequency oscillations, whereas the dynamics in the remaining degrees of freedom are lightly damped and generally decoupled. Comparisons of SV-13 flight-test and simulator data are more favorable for high-frequency inputs (omega greater than 1.0 rad/sec) than low-frequency inputs. The identification of symmetric and asymmetric beam-bending modes compares favorably with previous flight-test data. The results presented in this paper demonstrate the utility of the frequency-domain techniques for dynamics identification and simulator fidelity studies.

Tischler, M. B.↗

New frequency domain methods for system identification

This paper presents two new techniques for frequency domain identification of linear system parameters. The first technique uses the instrumental variables approach. The frequency domain formulation is shown to give a considerable insight into the selection of efficient and convergent instrumental variables. The new maximum likelihood formulation affords simplier numerical solution and provides a way to select parameter starting values in the gradient based optimization method.

Gupta, N. K.↗

Autonomous Frequency-Domain System-Identification Program

Autonomous Frequency Domain Identification (AU-FREDI) computer program implements system of methods, algorithms, and software developed for identification of parameters of mathematical models of dynamics of flexible structures and characterization, by use of system transfer functions, of such models, dynamics, and structures regarded as systems. Software considered collection of routines modified and reassembled to suit system-identification and control experiments on large flexible structures.

Yam, Yeung↗

A frequency-domain estimator for use in adaptive control systems

The paper presents a frequency-domain estimator which can identify both a nominal model of a plant as well as a frequency-domain bounding function on the modeling error associated with this nominal model. This estimator, which is called a robust estimator, can be used in conjunction with a robust control-law redesign algorithm to form a robust adaptive controller.

Lamaire, Richard O.↗

A frequency-domain estimator for use in adaptive control systems

This paper presents a frequency-domain estimator that can identify both a parametrized nominal model of a plant as well as a frequency-domain bounding function on the modeling error associated with this nominal model. This estimator, which we call a robust estimator, can be used in conjunction with a robust control-law redesign algorithm to form a robust adaptive controller.

Lamaire, Richard O.↗

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Due to the high computational cost associated with unsteady aeroelastic analysis, state-of-the-art aeroelastic optimizations based on computational fluid dynamics typically ignore critical constraints like flutter and aeroelastic gust response. The linearized frequency-domain method offers an approach for adding high-fidelity flutter constraints to multidisciplinary optimizations at relatively low cost compared to other unsteady computational fluid dynamics methods. In recent work, sensitivities have been implemented for the linearized frequency-domain method in FUN3D. In this work, the linearized frequency-domain method and associated sensitivities are applied to gradient-based aeroelastic optimization with flutter constraints based on computational fluid dynamics. An overview of the flutter constraint formulation and implementation is provided, and then two optimization problems are presented. The first optimization increases the flutter speed of a pitch and plunge airfoil at transonic conditions using the minimal amount of geometric changes. The second optimization minimizes the mass of the AGARD 445.6 wing subject to a flutter constraint.

Aeroelasticity↗

Flutter-Constrained Optimization with the Linearized Frequency-Domain Approach

Due to the high computational cost associated with unsteady aeroelastic analysis, state-of-the-art aeroelastic optimizations based on computational fluid dynamics typically ignore critical constraints like flutter and aeroelastic gust response. The linearized frequency-domain method offers an approach for adding high-fidelity flutter constraints to multidisciplinary optimizations at relatively low cost compared to other unsteady computational fluid dynamics methods. In recent work, sensitivities have been implemented for the linearized frequency-domain method in FUN3D. In this work, the linearized frequency-domain method and associated sensitivities are applied to gradient-based aeroelastic optimization with flutter constraints based on computational fluid dynamics. An overview of the flutter constraint formulation and implementation is provided, and then two optimization problems are presented. The first optimization increases the flutter speed of a pitch and plunge airfoil at transonic conditions using the minimal amount of geometric changes. The second optimization minimizes the mass of the AGARD 445.6 wing subject to a flutter constraint.

Aeroelasticity↗

Frequency Domain Beamforming for a Deep Space Network Downlink Array

This paper describes a frequency domain beamformer to array up to 8 antennas of NASA's Deep Space Network currently in development. The objective of this array is to replace and enhance the capability of the DSN 70m antennas with multiple 34m antennas for telemetry, navigation and radio science use. The array will coherently combine the entire 500 MHz of usable bandwidth available to DSN receivers. A frequency domain beamforming architecture was chosen over a time domain based architecture to handle the large signal bandwidth and efficiently perform delay and phase calibration. The antennas of the DSN are spaced far enough apart that random atmospheric and phase variations between antennas need to be calibrated out on an ongoing basis in real-time. The calibration is done using measurements obtained from a correlator. This DSN Downlink Array expands upon a proof of concept breadboard array built previously to develop the technology and will become an operational asset of the Deep Space Network. Design parameters for frequency channelization, array calibration and delay corrections will be presented as well a method to efficiently calibrate the array for both wide and narrow bandwidth telemetry.

Filterbank↗

High-order wide-band frequency domain identification using composite curve fitting

A method is presented for curve fitting nonparametric frequency domain data so as to identify a parametric model composed of two models in parallel, where each model has dynamics in a specified portion of the frequency band. This decomposition overcomes the problem of numerical sensitivity since lower order polynomials can be used compared to existing methods which estimate the model as a single entity. Consequently, composite curve fitting is useful for frequency domain identification of high-order systems and/or systems whose dynamics are spread over a large bandwidth. The approach can be extended to identify an arbitrary number of parallel subsystems in specified frequency regimes.

Bayard, D. S.↗

Multivariable frequency domain identification via 2-norm minimization

The author develops a computational approach to multivariable frequency domain identification, based on 2-norm minimization. In particular, a Gauss-Newton (GN) iteration is developed to minimize the 2-norm of the error between frequency domain data and a matrix fraction transfer function estimate. To improve the global performance of the optimization algorithm, the GN iteration is initialized using the solution to a particular sequentially reweighted least squares problem, denoted as the SK iteration. The least squares problems which arise from both the SK and GN iterations are shown to involve sparse matrices with identical block structure. A sparse matrix QR factorization method is developed to exploit the special block structure, and to efficiently compute the least squares solution. A numerical example involving the identification of a multiple-input multiple-output (MIMO) plant having 286 unknown parameters is given to illustrate the effectiveness of the algorithm.

Bayard, David S.↗