Conventional feedback control
models of the oculo motor system fail to account for the destabilizing effects
of neural transmission delays. To address this short coming, a linear quadratic
tracking algorithm used to control smoothly pursuing eye movements of various
target trajectories is presented.
Based on the type of input to the system, itis shown that stability, in the presence of large motor feedback delays, can be maintained by modulating weighting factors intrinsic to the model. Conditions,
such as the initial orientation of the eye relative to the location of where a
target first becomes salient and the possible oscillatory nature that the
reference trajectory may present, play important roles in determining the
optimal cost to go motor control strategy at the onset of a tracking movement.
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