HAVOK Model Predictive Control for Time-Delay Systems with Applications to District Heating

TL;DR

This paper introduces a HAVOK-based Model Predictive Control method for systems with unknown delays, utilizing input/output data and Koopman operator theory to achieve efficient and accurate control, validated on district heating systems.

Contribution

It presents a novel HAVOK-MPC framework that reduces computational complexity and handles unknown delays using only input/output data and a delay upper bound.

Findings

Demonstrates excellent prediction accuracy in experiments.

Achieves effective tracking performance.

Validates approach on a real district heating system.

Abstract

A computationally efficient Model-Predictive Control (MPC) approach is proposed for systems with unknown delay using only input/output data. We use the Koopman operator framework and the related Hankel Alternative View of Koopman (HAVOK) algorithm to identify a model in a basis of projected time-delay coordinates and demonstrate a novel MPC structure that reduces and bounds the computational complexity. The proposed HAVOK-MPC approach is validated experimentally on a laboratory-scale District Heating System (DHS), demonstrating excellent prediction and tracking performance while only requiring knowledge of a conservative upper bound on the system delay.