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Jamal Daafouz

Researcher at University of Lorraine

Publications -  205
Citations -  7317

Jamal Daafouz is an academic researcher from University of Lorraine. The author has contributed to research in topics: Linear system & Lyapunov function. The author has an hindex of 36, co-authored 197 publications receiving 6501 citations. Previous affiliations of Jamal Daafouz include Centre national de la recherche scientifique & Intelligence and National Security Alliance.

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Stabilization of nonlinear systems using event-triggered output feedback controllers

TL;DR: The objective is to design output feedback event-triggered controllers to stabilize a class of nonlinear systems and proves to be applicable to linear time-invariant (LTI) systems as a particular case.
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Event-triggered tracking control of unicycle mobile robots

TL;DR: The proposed event-triggering strategy is able to significantly reduce the need for communication compared to a classical time-triggered setup while ensuring similar, if not better, tracking performances.
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Adaptive synchronization of uncertain chaotic colpitts oscillators based on parameter identification

TL;DR: In this article, a non-linear observer for synchronization of a chaotic colpitts oscillator both in the non-adaptive and adaptive cases is proposed, where all parameters of a totally uncertain model of the oscillator can be estimated through adaptive synchronization.
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Analysis and control of LTI and switched systems in digital loops via an event-based modelling

TL;DR: A new event based discrete-time model (an exponential uncertain system with delay) is presented and it is shown that the stabilizability of this system can be achieved by finding a control for a switched polytopic system with an additive norm bounded uncertainty.
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Comparison of overapproximation methods for stability analysis of networked control systems

TL;DR: A particular class of techniques using discrete-time models that are based on polytopic overapproximations of the uncertain NCS model and lead to stability conditions in terms of linear matrix inequalities (LMIs) are surveyed.