Abstract

The paper focuses on the synthesis of adaptive robust controllers that achieve not only excellent output tracking performance but also accurate parameter estimations for secondary purposes such as machine health monitoring and prognostics. Such an objective is accomplished through an intelligent integration of the output tracking performance oriented direct adaptive robust control (DARC) design with the recently proposed accurate parameter estimation based indirect adaptive robust control (IARC) design. SISO nonlinear systems transformable to semi-strict feedback forms are considered. Theoretically, regardless of the specific estimation algorithm to be used, certain guaranteed transient performance and final tracking accuracy are achieved even in the presence of uncertain nonlinearities-a desirable feature in applications. In addition, the theoretical performance of adaptive designs - asymptotic output tracking in the presence of parametric uncertainties only - is preserved. The construction of physical parameter estimation law is based on the actual system dynamics and totally independent from the design of underline robust control law, which allows various estimation algorithms having better parameter convergence properties and practical modifications such as the on-line explicit monitoring of signal excitation levels to be used to significantly improve the accuracy of the resulting parameter estimates in implementation.

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