Best estimated inverse versus inverse of the best estimator.
The construction of a feed-forward controller frequently requires the estimation of an inverse function. Two possible methods to achieve this are: (i) learning the best estimated inverse (BEI), a method that is sometimes referred to as direct inverse learning and (ii) learning the inverse of the best estimator (IBE), a method that is sometimes referred to as indirect inverse learning. We analyze a general control problem, in the presence of noise, and show analytically that these two methods are asymptotically significantly different, even for simple linear non-redundant systems. We further demonstrate that the IBE method is typically superior for control purposes.
Karniel
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Meir
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Inbar
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D016477:Artifacts; D002490:Central Nervous System / Q000502:physiology*; D005246:Feedback / Q000502:physiology; D007858:Learning / Q000502:physiology*; D016014:Linear Models; D008959:Models, Neurological; D016571:Neural Networks, Computer