| Abstract: | Two recent developments will be surveyed here which are pointing the way towards an input–output theory of
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adaptive feedback: The solution of problems involving; (1) feedback performance (exact) optimization under large plant uncertainty on the one hand (the two-disc problem of
); and (2) optimally fast identification in
on the other. Taken together, these are yielding adaptive algorithms for slowly varying data in
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. At a conceptual level, these results motivate a general input-output theory linking identification, adaptation, and control learning. In such a theory, the definition of adaptation is based on system performance under uncertainty, and is independent of internal structure, presence or absence of variable parameters, or even feedback. |
