Adaptive Control for a Microgravity Vibration Isolation System
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Abstract
Most active vibration isolation systems that try to a provide quiescent acceleration environment for
space-science experiments have utilized linear design methods. In this paper, we address adaptive control
augmentation of an existing classical controller that combines a high-gain acceleration inner-loop feedback
together with a low-gain position outer-loop feedback to regulate the platform about its center position.
The control design considers both parametric and dynamic uncertainties because the isolation system must
accommodate a variety of payloads having different inertial and dynamic characteristics. An important aspect
of the design is the accelerometer bias. Two neural networks are incorporated to adaptively compensate for
the uncertainties within the acceleration and the position loop. A novel feature in the design is that high-band
pass and low pass filters are applied to the error signal used to adapt the weights in the neural network
and the adaptive signals, so that the adaptive processes operate over targeted ranges of frequency. This
prevents the inner and outer loop adaptive processes from interfering with each other. Simulations show
that adaptive augmentation improves the performance of the existing acceleration controller and at the same
time reduces the maximal position deviation and thus also improves the position controller.
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2005-08
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