Adaptive extremal control

Abstract
In this paper extremal control of a simple nonlinear stochastic system is analyzed. The process is modeled as a generalized Hammerstein model. Different problem formulations are discussed and the performances of the resulting nonlinear adaptive controllers are investigated. The adaptive controllers are based on online estimation of the parameters of the process and the certainty equivalence principle.

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