Title :
Observer design for unknown input nonlinear descriptor systems via convex optimization
Author_Institution :
Lab. d´´Automatique de Grenoble, Saint Martin d´´Heres, France
fDate :
6/1/2006 12:00:00 AM
Abstract :
This paper treats the design problem of full-order observers for nonlinear descriptor systems with unknown input (UI). Depending on the available knowledge on the UI dynamics, two cases are considered. First, a UI proportional observer (UIPO) is proposed when the spectral domain of the UI is unknown. Second, a PIO is proposed when the spectral domain of the UI is in the low frequency range. Sufficient conditions for the existence and stability of such observers are given and proved. Based on the linear matrix inequality (LMI) approach, an algorithm is presented to compute the observer gain matrix that achieves the asymptotic stability objective. An example is included to illustrate the method.
Keywords :
PI control; asymptotic stability; linear matrix inequalities; nonlinear control systems; observers; optimisation; asymptotic stability; convex optimization; linear matrix inequality; observer design; observer gain matrix; proportional integral observers; unknown input nonlinear descriptor system; Asymptotic stability; Design optimization; Frequency; Linear matrix inequalities; Linear systems; Noise robustness; Nonlinear systems; State estimation; Sufficient conditions; Symmetric matrices; Linear matrix inequalities (LMIs); Lipschitz nonlinear descriptor systems; proportional integral observers; unknown input observers;
Journal_Title :
Automatic Control, IEEE Transactions on
DOI :
10.1109/TAC.2006.876807