State and Fault Estimation of a Class of Nonlinear Systems with Slow Internal Dynamics: Asymptotic Decoupling Approach

Dalil Ichalal (1) , Saïd Mammar (1)

1 IBISC - Informatique, BioInformatique, Systèmes Complexes

This paper presents an Unknown Input Observer (UIO) for a class of Lipschitz nonlinear systems affected by disturbances/faults and having slow internal dynamics after the decoupling of the Unknown Input (UI). Thanks to the Asymptotic Decoupling notion, the constraint related to the internal dynamics is bypassed. The nonlinear UIO presents time varying dynamics that allows to obtain the Asymptotic Decoupling notion. It will be shown that the proposed approach allows to enhance the convergence rate of the UIO. The convergence enhancement of the state estimation error is demonstrated via a Lyapunov analysis and the established conditions are expressed in terms of Linear Matrix Inequalities. Finally, simulations will be given in order to illustrate the proposed approach with some comparisons to existing techniques.

Keywords: State estimation; Unknown Input Observers (UIO); Asymptotic Decoupling concept; Internal Dynamics; Nonlinear Lipschitz Systems; LMIs

Domains: Automatic

Dalil Ichalal, Saïd Mammar. State and Fault Estimation of a Class of Nonlinear Systems with Slow Internal Dynamics: Asymptotic Decoupling Approach. 4th IFAC Conference on Embedded Systems, Computational Intelligence and Telematics in Control (CESCIT 2021), Jul 2021, Valencienne, France. pp.130--134, ⟨10.1016/j.ifacol.2021.10.022⟩. ⟨hal-03281056⟩