Abstract
An iterative numerical algorithm for designing robust controllers using experimental data models is presented. This numerical approach has several advantages over standard analytical approaches. First, design constraints of many types can be specified. Also, the controller order is pre-specified by the designer. Finally, no analytical model of the system to be controlled is required; instead, experimental frequency response data can be used. The algorithm has been successfully applied to the design of a controller for disturbance rejection and vibration suppression in a flexible structure test facility. This application involved satisfying a variety of design goals, resulted in a low order controller, and experimental data were used as the sole plant model.
Published Version
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