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See detailAn adaptive high-gain observer for nonlinear systems
Boizot, Nicolas UL; Busvelle, Eric; Gauthier, Jean-Paul

in Automatica (2010), 46(9), 1483-1488

In this paper the authors provide a solution to the noise sensitivity of high-gain observers. The resulting nonlinear observer possesses simultaneously 1) extended Kalman filter's good noise filtering ... [more ▼]

In this paper the authors provide a solution to the noise sensitivity of high-gain observers. The resulting nonlinear observer possesses simultaneously 1) extended Kalman filter's good noise filtering properties, and 2) the reactivity of the high-gain extended Kalman filter with respect to large perturbations. The authors introduce innovation as the quantity that drives the gain adaptation. They prove a general convergence result, propose guidelines to practical implementation and show simulation results for an example. [less ▲]

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See detailAdaptive-gain Extended Kalman Filter: Extension to the Continuous-discrete Case
Boizot, Nicolas UL; Busvelle, Eric; Gauthier, Jean-Paul

Scientific Conference (2009)

In the present article we propose a nonlinear observer that merges the behaviors 1) of an extended Kalman filter, mainly designed to smooth off noise , and 2) of high-gain observers devoted to handle ... [more ▼]

In the present article we propose a nonlinear observer that merges the behaviors 1) of an extended Kalman filter, mainly designed to smooth off noise , and 2) of high-gain observers devoted to handle large perturbations in the state estimation. We specifically aim at continuous-discrete systems. The strategy consists in letting the high-gain self adapt according to the innovation. We define innovation computed over a time window and justify its usage via an important lemma. We prove the general convergence of the resulting observer. [less ▲]

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