Abstract
A software package which integrates model reduction and controller design is applied to design controllers for the Jet Propulsion Laboratory Large Spacecraft Control Laboratory experiment facility. Modal cost analysis is used for the model reduction, and various output covariance constraints are guaranteed by the controller design. The main motivation is to find the controller with the best performance with respect to output covariances. It is shown that by iterating on the reduced-order design model, the controller designed does have better performance than that obtained with the first model reduction, demonstrating an effective strategy for integrating modeling and control design.
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