Unknown inputs observer design for descriptor systems with monotone nonlinearities

2018 ◽  
Vol 28 (17) ◽  
pp. 5481-5494 ◽  
Author(s):  
Mahendra Kumar Gupta ◽  
Nutan Kumar Tomar ◽  
Mohamed Darouach
2020 ◽  
Vol 65 (1) ◽  
pp. 287-294 ◽  
Author(s):  
Jiancheng Zhang ◽  
Xudong Zhao ◽  
Fanglai Zhu ◽  
Hamid Reza Karimi

2017 ◽  
Vol 5 ◽  
pp. 117-134
Author(s):  
Karim Bouassem ◽  
Jalal Soulami ◽  
Abdellatif El Assoudi ◽  
El Hassane El Yaagoubi

Author(s):  
Shenghui Guo ◽  
Fanglai Zhu

Reduced-order observer design methods for both linear and nonlinear discrete-time descriptor systems based on the linear matrix inequality (LMI) approach are investigated. We conclude that the conditions under which a full-order observer exists can also guarantee the existence of a reduced-order observer. By choosing a special reduced-order observer gain matrix, a reduced-order unknown input observer is proposed for linear system with unknown inputs, and then an unknown input reconstruction is provided for some special cases. We also extend above results to the cases of nonlinear systems. Finally, three numerical comparative simulation examples are given to illustrate the effectiveness and merits of proposed methods.


2021 ◽  
Vol 229 ◽  
pp. 01019
Author(s):  
Karim Bouassem ◽  
Abdellatif El Assoudi ◽  
Jalal Soulami ◽  
El Hassane El Yaagoubi

This paper addresses the problem of unknown inputs observer (UIO) design for a class of linear descriptor systems. The unknown inputs affect both state and output of the system. The basic idea of the proposed approach is based on the separation between dynamic and static relations in the descriptor model. Firstly, the method used to separate the differential part from the algebraic part is developed. Secondly, an observer design permitting the simultaneous estimation of the system state and the unknown inputs is proposed. The developed approach for the observer design is based on the synthesis of an augmented model which regroups the differential variables and unknown inputs. The exponential stability of the estimation error is studied using the Lyapunov theory and the stability condition is given in term of linear matrix inequality (LMI). Finally, to illustrate the efficiency of the proposed methodology, a heat exchanger pilot model is considered.


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