Boundary Output Feedback Stabilization for a Novel Magnetizable Piezoelectric Beam Model

TL;DR

This paper develops a boundary output feedback stabilization method for a novel magnetizable piezoelectric beam model, introducing a non-collocated controller and observer design to ensure exponential stability of the coupled PDE system.

Contribution

It presents the first non-collocated boundary output feedback controller and observer for the magnetizable piezoelectric beam, enhancing stability and control performance.

Findings

Both the observer and error dynamics are proven to be exponentially stable.

The Lyapunov function construction guarantees stability of the closed-loop system.

Framework supports model reduction via Finite Differences.

Abstract

A magnetizable piezoelectric beam model, free at both ends, is considered. Piezoelectric materials have a strong interaction of electromagnetic and acoustic waves, whose wave propagation speeds differ substantially. The corresponding strongly-coupled PDE model describes the longitudinal vibrations and the total charge accumulation at the electrodes of the beam. It is known that the PDE model with appropriately chosen collocated state feedback controllers is known to have exponentially stable solutions. However, the collocated controller design is not always feasible since the performance of controllers may not be good enough, and moreover, a small increment of feedback controller gains can easily make the closed-loop system unstable. Therefore, a non-collocated controller and observer design is considered for the first time for this model. In particular, two state feedback controllers are designed at the right end to recover the states so that the boundary output feedback controllers can be designed as a replacement of the states with the estimate from the observers on the left end. By a carefully-constructed Lyapunov function, it is proved that the both the observer and the observer error dynamics have uniformly exponential stable solutions. This framework offers a substantial foundation for the model reductions by Finite Differences.