Event-triggered observer design for linear systems

Petri, Elena; Astolfi, Daniele; Nešić, Dragan; Heemels, W.P.M.H.

doi:10.1109/cdc45484.2021.9683754

Cited by 7 publications

(1 citation statement)

References 29 publications

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“…In [18], an asynchronous event-based H∞ control for output feedback systems is described, where the output signal sent from the controller is event-triggered; • ET measurement, where a measurement is sent to the observer/controller only when a condition is met. In [19], the authors describe a solution where the smart sensor's output is sent to the observer only when the triggering condition is met.…”

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Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set

et al. 2023

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This paper discusses the issue of optimizing the communication between the components of a cooperating control system formed by a pair of MPC controllers of a nuclear power plant turbine set using online recursive least squares identification. It is proposed to use event-triggered communication, i.e., sending information only at selected time instants, as opposed to the standard approach where communication is triggered by time (time-triggered approach). The aim of this paper is to propose a change in the method of information exchange in the case of asynchronous communication between control system components and to prove its suitability for the selected application. Resignation from continuous communication in favor of sending information only at selected moments allows the load on the communication network to be reduced by approximately 90% while maintaining the quality of control.

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Event-Triggered Communication in Cooperative, Adaptive Model Predictive Control of a Nuclear Power Plant’s Turbo–Generator Set

et al. 2023

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Observer design for continuous-time dynamical systems

Bernard

Andrieu

Astolfi

2022

Annual Reviews in Control

106

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We review the main design techniques of state observer design for continuous-time dynamical systems, namely algorithms which reconstruct online the full information of a dynamical process on the basis of partially measured data. Starting from necessary conditions for the existence of such asymptotic observers, we classify the available methods depending on the detectability/observability assumptions they require. We show how each class of observer relies on transforming the system dynamics in a particular normal form which allows the design of an observer, and how each observability condition guarantees the invertibility of its associated transformation and the convergence of the observer. Finally, some implementation aspects and open problems are briefly discussed.

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