[1991] Proceedings of the 30th IEEE Conference on Decision and Control
DOI: 10.1109/cdc.1991.261650
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A high gain observer for a class of uniformly observable systems

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Cited by 155 publications
(77 citation statements)
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“…where F (u, z) is the dynamics of systems (3,7) and K is a constant vector which does not depend on the input. In Section 3, we will extend the above observer design (9) to a class of MIMO nonlinear systems which generalizes systems (7).…”
Section: • Some Well-known Observability Notionsmentioning
confidence: 99%
See 1 more Smart Citation
“…where F (u, z) is the dynamics of systems (3,7) and K is a constant vector which does not depend on the input. In Section 3, we will extend the above observer design (9) to a class of MIMO nonlinear systems which generalizes systems (7).…”
Section: • Some Well-known Observability Notionsmentioning
confidence: 99%
“…Moreover, using this canonical form, the authors designed a high gain observer. Using similar canonical forms, many authors have studied separately high gain observer synthesis (see for instance [3,6]). …”
mentioning
confidence: 99%
“…Most of the published works deal with a class of linear systems with additive nonlinearity characterized by a non linear term in the state and output equation, that are assumed to fulfill a Lipschitz condition. The use of linear matrix inequalities has made possible to address the design of observers for that class of systems surpassing the drawbacks of previous approaches, where a high gain was needed to compensate for the non linear term, as initially proposed in [3]. Another alternative is the use of proportional/integral observers [1], that is, observers where the corrective action is proportional to the observation error and its integral, leading to a more complex observer dynamics.…”
Section: Introductionmentioning
confidence: 99%
“…This strategy was first validated in simulation for a three link biped without feet, using nonlinear high gain observers and a nonlinear observer based on sliding modes with a finite time convergence (Lebastard et al 2006a) and (Lebastard et al 2006b), for walking gaits composed of single support phases and impacts. The main drawback with this family of observers is that, when only some of the degrees of freedom are measured, a state coordinates transformation is necessary to design their canonical form (Gauthier & Bornard 1981;Krener & Respondek 1985;Bornard & Hammouri 1991;Plestan & Glumineau 1997). In this chapter, the observer is an extended Kalman filter and it is applied to SemiQuad, a prototype walking robot built at our institute.…”
Section: Introductionmentioning
confidence: 99%