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Milman, M. H.

Publications and source records attributed to Milman, M. H..

At least 19 records

Overview of SIM wide angle astrometric system calibration strategies

This paper summarizes two very different strategies envisioned for calibrating the systematic field dependent biases present in the Space Interferometry Mission (SIM) instrument. The Internal Calibration strategy is based on pre-launch measurements combined with a set of on orbit measurements generated by a source internal to the instrument. The External Calibration strategy uses stars as an external source for generating the calibration function. Both approaches demand a significant amount of innovation given that SIM's calibration strategy requires a post-calibration error of 100picometers over a 15 degree field of regard while the uncalibrated instrument introduces 10's-100's of nanometers of error. The calibration strategies are discussed in the context of the Wide Angle Astrometric mode of the instrument, although variations on the Internal Calibration Strategy may be used for doing Narrow Angle Astrometry.

calibration SIM optical modeling

High-precision early mission narrow angle sciene with the Space Interferometry Mission

We have developed a technique that allows SIM to measure relative stellar positions with an accuracy of 1 micro-arcsecond at any time during its 5-yr mission. Unlike SIM's standard narrow-angle approach, Gridless Narrow Angle Astrometry (GNAA) does not rely on the global reference frame of grid stars that reaches full accuracy after 5 years. GNAA is simply the application of traditional single-telescope narrow angle techniques to SIM's narrow angle optical path delay measurements. In GNAA, a set of reference stars and a target star are observed at several baseline orientations. A linearized model uses delay measurements to solve for star positions and baseline orientations. A conformal transformation maps observations at different epochs to a common reference frame. The technique works on short period signals (P=days to months), allowing it to be applied to many of the known extra-solar planets, intriguing radio/X- ray binaries, and other periodic sources. The technique's accuracy is limited in the long-term by false acceleration due to a combination of reference star and target star proper motion. The science capability 1 micro-arcsecond astrometric precision - is unique to SIM.

Space Interferometry Mission

SIM white light on-board processing algorithms

Interferometry in optical astronomy is an important and growing field of astronomical observation. A number of stellar interferometers have come online over the past several years, and several more are due to be operational in the near future. In addition, space based interferometers are also planned missions of NASA's Origins program, including the Space Interferometry Mission (SIM), the focus of the present paper. The fundamental measurement made by each of these interferometers is the white light fringe measurement to determine the optical pathlength delay between the two arms of the interferometer. SIM makes white light measurements with three independent interferometers observing three different objects. Two of these are the "guide" interferometers that observe bright objects (approximately 7th magnitude) to track the rigid body motion of the instrument. The third interferometer, the "science" interferometer, observes the science targets of interest.

interferometry

SIM vs. SOS: A Space Interferometry Trade Study

This study was undertaken at the Jet Propulsion Laboratory to identify salient features of two competing instrument designs and to select the design that best meets the goals of the Space Interferometry Mission.

trade-study

Optimizaton Methods for Passive Damper Placement and Tunin

The effectiveness of viscous elements in introducing damping in a structure is a function of several variables, including their number, their location in the structure, and their physical properties. This paper addresses the questions of the placement of these elements and the selection of their physical parameters via optimization techniques.

viscous elements

Computational issues in optimal tuning and placement of passive dampers

The effectiveness of viscous elements in introducing damping in a structure is a function of several variables including their number, their location in the structure, and their physical properties. In this paper, the optimal damper placement and tuning problem is posed to optimize these variables. Both discrete and continuous optimization problems are formulated and solved corresponding, respectively, to the problems of placement of passive elements and to the tuning of their parameters. The paper particularly emphasizes the critical computational issues resulting from the optimization formulations. Numerical results involving a lightly damped testbed structure are presented.

Chu, C. C.

A new algorithm for L2 optimal model reduction

In this paper the quadratically optimal model reduction problem for single-input, single-output systems is considered. The reduced order model is determined by minimizing the integral of the magnitude-squared of the transfer function error. It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer. Convergence of the proposed algorithm to stationary values of the quadratic cost function is proved. The formulation is extended to handle the frequency-weighted optimal model reduction problem. Three examples demonstrate the optimization algorithm.

Spanos, J. T.

Optimization methods for passive damper placement and tuning

The effectiveness of viscous elements in introducing damping in a structure is a function of several variables, including their number, their location in the structure, and their physical properties. In this paper several optimization problems are posed to optimize these variables. The paper investigates various metrics to define the optimization problem, and compares the damping profiles that are obtained. Both discrete and continuous optimization problems are formulated and solved, corresponding, respectively, to the problems of placement of damping elements and to the tuning of their parameters. The paper particularly emphasizes techniques to make feasible the large scale problems resulting from the optimization formulations. Numerical results involving a lightly damped tested structure are presented.

Milman, M. H.

Automated on-orbit frequency domain identification for large space structures

Recent experiences in the field of flexible structure control in space have indicated a need for on-orbit system identification to support robust control redesign to avoid in-flight instabilities and maintain high spacecraft performance. This paper highlights an automated frequency domain system identification methodology recently developed to fulfill this need. The methodology is focused to support (1) the estimation of system quantities useful for robust control analysis and design; (2) experiment design tailored to performing system identification in a typically constrained on-orbit environment; and (3) the automation of operations to reduce 'human in the loop' requirements.

Bayard, D. S.

A homotopy approach for combined control-structure optimization - Constructive analysis and numerical examples

This paper outlines the development of methods for the combined control-structure optimization of physical systems encountered in the technology of large space structures. The objectives of the approach taken in this paper is not to produce the 'best' optimized design, but rather to efficiently produce a family of design options so as to assist in early trade studies, typically before hard design constraints are imposed. The philosophy is that these are candidate designs to be passed on for further considerations, and their function is more to guide the development of the system design rather than to represent the ultimate product. A homotopy approach involving multi-objective functions is developed for this purpose. Analytical and numerical examples are also presented.

Scheid, R. E.

Optimal model reduction and frequency-weighted extension

In this paper the quadratically optimal model reduction problem for single-input, single-output systems is considered. The reduced order model is determined by minimizing the integral of the magnitude-squared of the transfer function error. It is shown that the numerator coefficients of the optimal approximant satisfy a weighted least squares problem and, on this basis, a two-step iterative algorithm is developed combining a least squares solver with a gradient minimizer. The existence of globally optimal stable solutions to the optimization problem is established, and convergence of the algorithm to stationary values of the cost function is proved. The formulation is extended to handle the frequency-weighted optimal model reduction problem. Three examples demonstrate the optimization algorithm.

Spanos, J. T.

Autonomous frequency domain identification: Theory and experiment

The analysis, design, and on-orbit tuning of robust controllers require more information about the plant than simply a nominal estimate of the plant transfer function. Information is also required concerning the uncertainty in the nominal estimate, or more generally, the identification of a model set within which the true plant is known to lie. The identification methodology that was developed and experimentally demonstrated makes use of a simple but useful characterization of the model uncertainty based on the output error. This is a characterization of the additive uncertainty in the plant model, which has found considerable use in many robust control analysis and synthesis techniques. The identification process is initiated by a stochastic input u which is applied to the plant p giving rise to the output. Spectral estimation (h = P sub uy/P sub uu) is used as an estimate of p and the model order is estimated using the produce moment matrix (PMM) method. A parametric model unit direction vector p is then determined by curve fitting the spectral estimate to a rational transfer function. The additive uncertainty delta sub m = p - unit direction vector p is then estimated by the cross spectral estimate delta = P sub ue/P sub uu where e = y - unit direction vectory y is the output error, and unit direction vector y = unit direction vector pu is the computed output of the parametric model subjected to the actual input u. The experimental results demonstrate the curve fitting algorithm produces the reduced-order plant model which minimizes the additive uncertainty. The nominal transfer function estimate unit direction vector p and the estimate delta of the additive uncertainty delta sub m are subsequently available to be used for optimization of robust controller performance and stability.

Yam, Yeung