Sensor Fault and Unknown Input Estimation Based on Proportional Integral Observer Applied to LPV Descriptor Systems.

2012 ◽  
Vol 45 (20) ◽  
pp. 1059-1064 ◽  
Author(s):  
A. Aguilera-González ◽  
D. Theilliol ◽  
M. Adam-Medina ◽  
C.M. Astorga-Zaragoza ◽  
M. Rodrigues
Keyword(s):  
Descriptor Systems ◽  
Unknown Input ◽  
Sensor Fault ◽  
Input Estimation ◽  
Proportional Integral ◽  
Unknown Input Estimation

H∞ dynamical observers design for linear descriptor systems. Application to state and unknown input estimation

2015 ◽  
Vol 26 ◽  
pp. 35-43 ◽  
Author(s):  
Gloria-Lilia Osorio-Gordillo ◽  
Mohamed Darouach ◽  
Carlos-Manuel Astorga-Zaragoza
Keyword(s):  
Descriptor Systems ◽  
Unknown Input ◽  
Input Estimation ◽  
Unknown Input Estimation

Proportional-Integral-Observer With Adaptive High-Gain Design Using Funnel Adjustment Concept

2017 ◽  
Author(s):  
Fateme Bakhshande ◽  
Dirk Söffker
Keyword(s):  
Feedback Linearization ◽  
Dynamical Behavior ◽  
High Gain ◽  
Present Contribution ◽  
Input Estimation ◽  
Proportional Integral ◽  
Spring System ◽  
Unknown Input Estimation ◽  
Mass Spring ◽  
Funnel Control

This paper focuses on a novel gain design approach of Proportional-Integral-Observer (known as PI-Observer) for unknown input estimation such as disturbances. Whereas estimation of the fast dynamical behavior requires large observer gains, the effect of measurement noise is not negligible. To adjust the PIO gain adaptively, in this contribution the idea of funnel control is taken into consideration. The advantage of the proposed approach compared to previously published PIO gain design is the self adjustment of the observer gains according to the actual estimation situation. To improve the control performance and robustness, in the present contribution the proposed approach is combined with exact feedback linearization (EFL) method. The effectiveness of the proposed approach is verified by simulation results of a MIMO mass-spring system.

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