A Showcase of LMI-Based Methods for Analysis, Control and Estimation of PDEs

The last 5 years have seen the emergence of several research groups focused on the use of optimization and Linear Matrix Inequality (LMI) methods for the analysis, control, and estimation of systems governed by Partial Differential Equations (PDEs). The development of efficient numerical methods for the analysis and control of PDE systems has applications in fields such as drag reduction; controlled nuclear fusion; wind generation; high-tech industries; and process control, to name a few. Unlike older, 'lumping'-based work, these newly emerging research groups have focused on using optimization-based tools to design controllers without the use of discretization. As a result, the tools being developed have provable stability and optimality properties.

The goal of this workshop, then, is to bring together representatives from each of the newly emerging research groups in order to compare results and propose a vision for the future of this rapidly evolving field.