2015 16th International Conference on Sciences and Techniques of Automatic Control and Computer Engineering (STA) 2015
DOI: 10.1109/sta.2015.7505117
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Sliding mode multiple observer for perturbed output nonlinear systems

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Cited by 4 publications
(1 citation statement)
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“…Initially, the multiple observers have been used for failure detection [10,11] and switching control [12], where the multiple observers are designed for candidate plant models. In the research area of multiple models' estimation, the aim of the paper [13] was the state estimation for perturbed output nonlinear systems; a Lyapunov based sliding mode multiple observer is presented, the proof of the observer stability being ensured by a suitable choice of estimation gains-solutions of linear matrix inequalities (LMIs). In [14], the authors focus on the state estimation of a nonlinear system described by a Takagi-Sugeno (T-S) multiple model having unknown inputs and outputs; the proposed approach consists of a mathematical transformation which enables 2 Complexity the "conversion" of the unknown outputs into "pseudo" unknown inputs-eliminated through the designed multiple observer.…”
Section: Introductionmentioning
confidence: 99%
“…Initially, the multiple observers have been used for failure detection [10,11] and switching control [12], where the multiple observers are designed for candidate plant models. In the research area of multiple models' estimation, the aim of the paper [13] was the state estimation for perturbed output nonlinear systems; a Lyapunov based sliding mode multiple observer is presented, the proof of the observer stability being ensured by a suitable choice of estimation gains-solutions of linear matrix inequalities (LMIs). In [14], the authors focus on the state estimation of a nonlinear system described by a Takagi-Sugeno (T-S) multiple model having unknown inputs and outputs; the proposed approach consists of a mathematical transformation which enables 2 Complexity the "conversion" of the unknown outputs into "pseudo" unknown inputs-eliminated through the designed multiple observer.…”
Section: Introductionmentioning
confidence: 99%