Identification and adaptive control: Towards a complexity-based general theory

✍ Scribed by G. Zames

• Publisher: Elsevier Science
• Year: 1998
• Tongue: English
• Weight: 124 KB
• Volume: 34
• Category: Article
• ISSN: 0167-6911
• DOI: 10.1016/s0167-6911(98)00009-7

✦ Synopsis

Two recent developments will be surveyed here which are pointing the way towards an input-output theory of H ∞ -l 1 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 H ∞ ); and (2) optimally fast identiÿcation in H ∞ on the other. Taken together, these are yielding adaptive algorithms for slowly varying data in H ∞ -l 1 . At a conceptual level, these results motivate a general input-output theory linking identiÿcation, adaptation, and control learning. In such a theory, the deÿnition of adaptation is based on system performance under uncertainty, and is independent of internal structure, presence or absence of variable parameters, or even feedback.