Finite-Dimensional Boundary Control of the Linear Kuramoto-Sivashinsky Equation Under Point Measurement With Guaranteed L2-Gain

Rami Katz*, Emilia Fridman

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review


Finite-dimensional observer-based controller design for PDEs is a challenging problem. Recently, such controllers were introduced for the one dimensional (1D) heat equation, under the assumption that one of the observation or control operators is bounded. This article suggests a constructive method for such controllers for 1D parabolic partial differential equations (PDEs) with both observation and control operators being unbounded. We consider the Kuramoto-Sivashinsky equation under either boundary or in-domain point measurement and boundary actuation in the presence of disturbances in the PDE and measurement. 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. We suggest a direct Lyapunov approach to the full-order closed-loop system, which results in a linear matrix inequality (LMI), for input-to-state stabilization (ISS) and guaranteed L2-gain, whose elements and dimension depend on N. The value of N and the decay rate are obtained from the LMI. We prove that the LMI is always feasible provided N and the L2 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. Numerical examples demonstrate the efficiency of the method.

Original languageEnglish
Pages (from-to)5570-5577
Number of pages8
JournalIEEE Transactions on Automatic Control
Issue number10
StatePublished - 1 Oct 2022


  • Boundary control
  • LMI
  • modal decomposition
  • observer-based control
  • parabolic PDEs


Dive into the research topics of 'Finite-Dimensional Boundary Control of the Linear Kuramoto-Sivashinsky Equation Under Point Measurement With Guaranteed L2-Gain'. Together they form a unique fingerprint.

Cite this