Title :
Luenberger-type observers for perspective linear systems
Author :
Abdursul, Rixat ; Inaba, Hiroshi ; Ghosh, Bijoy K.
Abstract :
Perspective dynamical systems arise in machine vision, in which only perspective observation is available, and the essential problem is to estimate the state and /or unknown parameters for a moving rigid body based on the observed information. This paper proposes and studies a Luenberger-type observer for perspective linear systems. In particular, assuming a given perspective linear system to be Lyapunov stable and to satisfy some sort of detectability condition, it is shown that the estimation error converges exponentially to zero. Finally, some simple numerical examples are presented to illustrate the result obtained.
Keywords :
Lyapunov methods; linear systems; state estimation; Luenberger-type observers; Lyapunov stability; detectability condition; estimation error; machine vision; moving rigid body; perspective dynamical systems; perspective linear systems; state estimation; Dynamics; Estimation error; Linear systems; Machine vision; Observers; Vectors; detectability; exponential stability; machine vision; nonlinear observer; perspective system;
Conference_Titel :
Control Conference (ECC), 2001 European
Conference_Location :
Porto
Print_ISBN :
978-3-9524173-6-2