Finite-dimensional boundary control of the linear Kuramoto-Sivashinsky equation under point measurement with guaranteed $L^2$-gain

TL;DR

This paper develops a constructive, finite-dimensional boundary control method for the 1D Kuramoto-Sivashinsky equation with point measurements, ensuring stability and $L^2$-gain guarantees through LMIs.

Contribution

It introduces a new modal decomposition approach for boundary control of PDEs with unbounded operators, extending previous methods to the Kuramoto-Sivashinsky equation.

Findings

LMI feasibility guarantees controller stability for large enough N.

Enlarging N does not worsen decay rate in stabilization.

Numerical examples confirm the method's effectiveness.

Abstract

Finite-dimensional observer-based controller design for PDEs is a challenging problem. Recently, such controllers were introduced for the 1D heat equation, under the assumption that one of the observation or control operators is bounded. This paper suggests a constructive method for such controllers for 1D parabolic PDEs with both (observation and control) operators being unbounded. We consider the Kuramoto-Sivashinsky equation (KSE) under either boundary or in-domain point measurement and boundary actuation. We employ a modal decomposition approach via dynamic extension, using eigenfunctions of a Sturm-Liouville operator. The controller dimension is defined by the number of unstable modes, whereas the observer dimension $N$ may be larger than this number. We suggest a direct Lyapunov approach to the full-order closed-loop system, which results in an LMI whose elements and dimension depend on $N$. The value of $N$ and the decay rate are obtained from the LMI. We extend our approach to internal stabilization with guaranteed $L^2$-gain and input-to-state stabilization. We prove two crucial properties of the derived LMIs. First, We prove that the LMIs are always feasible provided $N$ and the $L^2$ or ISS gains are large enough, thereby obtaining guarantees for our approach. Moreover, for the case of stabilization, we show that feasibility of the LMI for some $N$ implies its feasibility for $N+1$ (i.e., enlarging $N$ in the LMI cannot deteriorate the resulting decay rate of the closed-loop system). Numerical examples demonstrate the efficiency of the method.