Output Regulation of Invertible Nonlinear Systems via Robust Dynamic Feedback-Linearization

In this paper, we address a problem of output regulation for a broad class of invertible MIMO nonlinear systems. The system we consider are assumed to possess a globally-defined normal form, in which appropriate invertibility conditions are fulfilled, and to be strongly minimum phase. Asymptotic output regulation is achieved thanks to the design of a preprocessing internal model yielding an augmented system, still expressed in normal form, that remains strongly minimum phase. Classical methods for input-output linearization via dynamic extension and state feedback would, in principle, be able to stabilize the augmented system and hence to steer the regulated output to zero. However, such methods are not applicable because they repose on the knowledge of an accurate model of the plant and on the availability of internal variables that are not accessible for measurement. Instead, we use a recently developed method based on feedback-linearization. The method does not presume the knowledge of an accurate model of the plant and only needs access to the regulated variables.