Estimation Design using Youla Parametrization with Automotive Applications

Francis Assadian, Alex Beckerman, and Jose Velazquez

Youla parametrization is a well-established technique in deriving SISO (Single-Input Single-Output) and, to a lesser extent, MIMO (Multiple-Input Multiple-Ouput) controllers. However, the utility of this methodology in estimation design, specifically in the framework of Controller Output Observer (COO), is not established.

The fundamental question to be answered is as follows: is it possible to design a deterministic estimation technique using Youla parametrization with the same robust performance, or better, than well-established stochastic estimation techniques such as Kalman filtering? To prove this point, at this stage, a comparative analysis between Youla parametrization in estimation and Kalman filtering is performed through simulations only.

In this article, we provide an overview of Youla parametrization for both control and estimation design. We develop a deterministic SISO and MIMO Youla estimation technique in the framework of COO and we investigate the utility of this method for two applications in the automotive domain.

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