Recursive Parameter Estimation of Dynamical Systems under Closed Loop Control

J. Boaventura Cunha (Portugal)

Keywords

Adaptive Control, Dynamic Models, Recursive Least Squares, System Identification

Abstract

Real time parameter estimation of dynamic models operating in closed loop control is a crucial issue to implement industrial adaptive controllers. Parameter estimation must be seen as one of the key elements to solve a system identification problem, which involves also an experiment design, the selection of a model structure, and the model validation. This paper describes some approaches to compute the transfer function parameters of time-varying systems under closed loop control. To point the limitations and advantages of each method, with focus on robustness and quality of the model estimates, the techniques are applied to compute the parameters of a time varying discrete system, with known structure, under PI Proportional-Integral control.

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