Dynamic event-triggered gain-scheduling control of discrete-time quasi-LPV systems

This paper concerns the dynamic event-triggered gain-scheduling control of discrete-time nonlinear systems represented by quasi-linear parameter-varying (quasi-LPV) models. A novel dynamic triggering mechanism is proposed to cancel out the influence of asynchronous parameters induced by the event-ba...

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Bibliographic Details
Published in:Automatica (Oxford) 2022-07, Vol.141, p.110292, Article 110292
Main Authors: Coutinho, Pedro H.S., Peixoto, Márcia L.C., Bessa, Iury, Palhares, Reinaldo Martinez
Format: Article
Language:English
Subjects:
Convex optimization
Event-based control
Gain-scheduling
Lyapunov methods
Parameter-varying systems
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Summary:This paper concerns the dynamic event-triggered gain-scheduling control of discrete-time nonlinear systems represented by quasi-linear parameter-varying (quasi-LPV) models. A novel dynamic triggering mechanism is proposed to cancel out the influence of asynchronous parameters induced by the event-based sampling. This new mechanism allows to derive constructive conditions to simultaneously design the gain-scheduled control law and the dynamic triggering mechanism to ensure the origin of the closed-loop system is asymptotically stable. As a sub-product, a co-design condition is readily derived to design static triggering mechanisms. Moreover, a convex optimization problem is proposed to enlarge the inter-event sampling and an estimate of the region of attraction of the closed-loop system is obtained. Numerical examples are provided to illustrate the effectiveness of the dynamic triggering strategy over its static counterpart.
ISSN:0005-1098
1873-2836
DOI:10.1016/j.automatica.2022.110292