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Event-triggered intermittent sampling for nonlinear model predictive control
KTH, School of Electrical Engineering (EES), Automatic Control. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.ORCID iD: 0000-0001-7309-8086
2017 (English)In: Automatica, ISSN 0005-1098, E-ISSN 1873-2836, Vol. 81, p. 148-155Article in journal (Refereed) Published
Abstract [en]

In this paper, we propose a new aperiodic formulation of model predictive control for nonlinear continuous-time systems. Unlike earlier approaches, we provide event-triggered conditions without using the optimal cost as a Lyapunov function candidate. Instead, we evaluate the time interval when the optimal state trajectory enters a local set around the origin. The obtained event-triggered strategy is more suitable for practical applications than the earlier approaches in two directions. First, it does not include parameters (e.g., Lipschitz constant parameters of stage and terminal costs) which may be a potential source of conservativeness for the event-triggered conditions. Second, the event-triggered conditions are necessary to be checked only at certain sampling time instants, instead of continuously. This leads to the alleviation of the sensing cost and becomes more suitable for practical implementations under a digital platform. The proposed event-triggered scheme is also validated through numerical simulations.

Place, publisher, year, edition, pages
Elsevier Ltd , 2017. Vol. 81, p. 148-155
Keywords [en]
Event-triggered control, Networked control, Nonlinear model predictive control, Continuous time systems, Costs, Lyapunov functions, Nonlinear systems, Predictive control systems, Event-triggered controls, Intermittent samplings, Lipschitz constant, Networked controls, Nonlinear continuous-time systems, Optimal state trajectories, Potential sources, Model predictive control
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
URN: urn:nbn:se:kth:diva-216312DOI: 10.1016/j.automatica.2017.03.028ISI: 000403513900017Scopus ID: 2-s2.0-85018488469OAI: oai:DiVA.org:kth-216312DiVA, id: diva2:1162471
Note

QC 20171204

Available from: 2017-12-04 Created: 2017-12-04 Last updated: 2017-12-04Bibliographically approved

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Dimarogonas, Dimos V.

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