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Bergmann, Martin

Publications and source records attributed to Bergmann, Martin.

Optimization of actuator and sensor placement for on-orbit identification in large flexible spacecraft

There has been considerable research on choosing actuator and sensor locations in large flexible spacecraft in order to optimize the controllability and observability of the system, or to maximize some objective function of control system performance. Future large flexible spacecraft may require on-orbit identification of the structure to tune the control system, because such tests cannot be performed in a one-g environment before launch. This indicates that the choice of actuator and sensor locations must serve a dual purpose, for control and for identification. This paper develops concepts for a degree of identifiability and studies placement of actuators and sensors on a free-free beam to optimize such objective functions. The results in this simple situation suggest that in free-free spacecraft structures in orbit, placement for control and placement for identification may often be consistent objectives rather than conflicting objectives.

Bergmann, Martin↗

Variance and bias computation for enhanced system identification

A study is made of the use of a series of variance and bias confidence criteria recently developed for the eigensystem realization algorithm (ERA) identification technique. The criteria are shown to be very effective, not only for indicating the accuracy of the identification results (especially in terms of confidence intervals), but also for helping the ERA user to obtain better results. They help determine the best sample interval, the true system order, how much data to use and whether to introduce gaps in the data used, what dimension Hankel matrix to use, and how to limit the bias or correct for bias in the estimates.

Bergmann, Martin↗

Variance and bias confidence criteria for ERA modal parameter identification

For the ERA system identification algorithm, perturbation methods are used to develop expressions for variance and bias of the identified modal parameters. Based on the statistics of the measurement noise, the variance results serve as confidence criteria by indicating how likely the true parameters are to lie within any chosen interval about their identified values. This replaces the use of expensive and time-consuming Monte Carlo computer runs to obtain similar information. The bias estimates help guide the ERA user in his choice of which data points to use and how much data to use in order to obtain the best results, performing the trade-off between the bias and scatter. Also, when the uncertainty in the bias is sufficiently small, the bias information can be used to correct the ERA results. In addition, expressions for the variance and bias of the singular values serve as tools to help the ERA user decide the proper modal order.

Longman, Richard W.↗