Time-Domain Model Matching Under General Norms via Sparse Matrix Methods

Publikationen: Beitrag in Buch/Bericht/KonferenzbandBeitrag in Konferenzband

Externe Organisationseinheiten

  • École de technologie supérieure

Abstract

This paper presents a new approach to the task of time-domain model matching for state-space systems. The traditional problem formulation of designing a controller to match a reference model is relaxed to matching only a desired reference response. The presented algorithm then computes the feedback gain that delivers the best fit solution to the reference response under general norms. Additionally, the proposed discretization approach enables the employment of sparse matrix methods which enables a numerically efficient implementation. The new method is successfully verified using a random system. Additionally, an application example involving a simplified gantry crane system is presented, showcasing the practicality of the approach. Overall, the new method provides an intuitive and numerically efficient solution to the problem of time-domain model matching for state-space systems.

Details

OriginalspracheEnglisch
Titel2023 12th Mediterranean Conference on Embedded Computing (MECO)
DOIs
StatusVeröffentlicht - 6 Juni 2023
Veranstaltung12th Mediterranean Conference on Embedded Computing - Budva, Montenegro
Dauer: 6 Juni 202310 Juni 2023
Konferenznummer: 12

Konferenz

Konferenz12th Mediterranean Conference on Embedded Computing
KurztitelMECO
Land/GebietMontenegro
OrtBudva
Zeitraum6/06/2310/06/23