ON OPTIMIZATION OF NONLINEAR DYNAMIC PROCESSES WITH UNKNOWN PARAMETERS.
COLUMBIA UNIV NEW YORK DEPT OF ELECTRICAL ENGINEERING
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An important theoretical and practical problem which arises in dealing with self-optimizing or adaptive systems is to prove that a particular optimalizing process converges for every state of the plant. In this paper a class of nonlinear, inertial and random plants which satisfy certain optimizability conditions is considered. Two different convergent iteration processes are constructed and compared. The notation of functional analysis is used for reasons of simplicity and conciseness. Author
- Theoretical Mathematics