Data-driven control of infinite dimensional systems: Application to a continuous crystallizer

TL;DR

This paper compares two data-driven control strategies for infinite dimensional systems, specifically a continuous crystallizer, highlighting their effectiveness and potential for practical implementation.

Contribution

It introduces and compares a structured robust technique and the L-DDC method based on Loewner interpolation for controlling complex infinite dimensional systems.

Findings

Both methods effectively control the continuous crystallizer.

The L-DDC approach simplifies controller design without extensive model reduction.

Structured robust technique offers high robustness in control performance.

Abstract

Controlling infinite dimensional models remains a challenging task for many practitioners since they are not suitable for traditional control design techniques or will result in a high-order controller too complex for implementation. Therefore, the model or the controller need to be reduced to an acceptable dimension, which is time-consuming, requires some expertise and may introduce numerical error. This paper tackles the control of such a system, namely a continuous crystallizer, and compares two different data-driven strategies: the first one is a structured robust technique while the other one, called L-DDC, is based on the Loewner interpolatory framework.