Abstract

Special problems related to control system design for large flexible structures include the inherent low damping, wide range of modal frequencies, unmodeled dynamics, and possibility of system failures. Neuro-control, which combines concepts from artificial neural networks and adaptive control is investigated as a solution to some of these problems. Specifically, the roles of neutro-controllers in learning unmodeled dynamics and adaptive control for system failures are investigated. The neuro-controller synthesis procedure and its capabilities in adaptively controlling the structure are demonstrated using a mathematical model of an existing structure, the advanced control evaluation for systems test article located at NASA/Marshall Space Flight Center. Also, the real-time adaptive capability of neuro-controllers is demonstrated via an experiment utilizing a flexible clamped-free beam equipped with an actuator that uses a bang-bang controller.

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