Self-triggered output-feedback control of LTI systems subject to disturbances and noise

Self-triggered output-feedback control of LTI systems subject to disturbances and noise

de Albuquerque Gleizer, G. (TU Delft Team Tamas Keviczky)
Mazo, M. (TU Delft Team Tamas Keviczky)

2020

Self-triggered control (STC) and periodic event-triggered control (PETC) are aperiodic sampling techniques aiming at reducing control data communication when compared to periodic sampling. In both techniques, the effects of measurement noise in continuous-time systems with output feedback are unaddressed. In this work we prove that additive noise does not hinder stability of output-feedback PETC of linear time-invariant (LTI) systems. Then we build an STC strategy that estimates PETC's worst-case triggering times. To accomplish this, we use set-based methods, more specifically ellipsoidal sets, which describe uncertainties on state, disturbances and noise. Ellipsoidal reachability is then used to predict worst-case triggering condition violations, ultimately determining the next communication time. The ellipsoidal state estimate is recursively updated using guaranteed state estimation (GSE) methods. The proposed STC is designed to be computationally tractable at the expense of some added conservatism. It is expected to be a practical STC implementation for a broad range of applications.

Bounded disturbances
Bounded noise
Control systems
Digital control
Dynamic output feedback
Linear systems
Networked control
Self-triggered control
State estimation

http://resolver.tudelft.nl/uuid:10c8df98-8a61-4598-90dc-0d4cb97103f3

https://doi.org/10.1016/j.automatica.2020.109129

2021-01-10

0005-1098

Automatica, 120

Green Open Access added to TU Delft Institutional Repository ‘You share, we take care!’ – Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.

Institutional Repository

journal article

© 2020 G. de Albuquerque Gleizer, M. Mazo