Data-driven System Interconnections and a Novel Data-enabled Internal Model Control

Fuente: arXiv
Saved in:
Bibliographic Details
Main Authors: Pedari, Yasaman, Lee, Jaeho, Eun, Yongsoon, Ossareh, Hamid
Format: Preprint
Published: 2023
Subjects:
Online Access:
Tags: Add Tag
No Tags, Be the first to tag this record!
_version_ 1866907784372551680
author Pedari, Yasaman
Lee, Jaeho
Eun, Yongsoon
Ossareh, Hamid
author_facet Pedari, Yasaman
Lee, Jaeho
Eun, Yongsoon
Ossareh, Hamid
contents Over the past two decades, there has been a growing interest in control systems research to transition from model-based methods to data-driven approaches. In this study, we aim to bridge a divide between conventional model-based control and emerging data-driven paradigms grounded in Willem's fundamental lemma. Specifically, we study how input/output data from two separate systems can be manipulated to represent the behavior of interconnected systems, either connected in series or through feedback. Using these results, this paper introduces the Internal Behavior Control (IBC), a new control strategy based on the well-known Internal Model Control (IMC) but viewed under the lens of Behavioral System Theory. Similar to IMC, the IBC is easy to tune and results in perfect tracking and disturbance rejection but, unlike IMC, does not require a parametric model of the dynamics. We present two approaches for IBC implementation: a component-by-component one and a unified one. We compare the two approaches in terms of filter design, computations, and memory requirements.
format Preprint
id arxiv_https___arxiv_org_abs_2311_12696
institution arXiv
publishDate 2023
record_format arxiv
spellingShingle Data-driven System Interconnections and a Novel Data-enabled Internal Model Control
Pedari, Yasaman
Lee, Jaeho
Eun, Yongsoon
Ossareh, Hamid
Systems and Control
14J60 (Primary) 14F05, 14J26 (Secondary)
Over the past two decades, there has been a growing interest in control systems research to transition from model-based methods to data-driven approaches. In this study, we aim to bridge a divide between conventional model-based control and emerging data-driven paradigms grounded in Willem's fundamental lemma. Specifically, we study how input/output data from two separate systems can be manipulated to represent the behavior of interconnected systems, either connected in series or through feedback. Using these results, this paper introduces the Internal Behavior Control (IBC), a new control strategy based on the well-known Internal Model Control (IMC) but viewed under the lens of Behavioral System Theory. Similar to IMC, the IBC is easy to tune and results in perfect tracking and disturbance rejection but, unlike IMC, does not require a parametric model of the dynamics. We present two approaches for IBC implementation: a component-by-component one and a unified one. We compare the two approaches in terms of filter design, computations, and memory requirements.
title Data-driven System Interconnections and a Novel Data-enabled Internal Model Control
topic Systems and Control
14J60 (Primary) 14F05, 14J26 (Secondary)
url https://arxiv.org/abs/2311.12696