Adjustable parameter-based multi-objective fault estimation observer design for continuous-time/discrete-time dynamic systems

2017 ◽  
Vol 15 (3) ◽  
pp. 1077-1088 ◽  
Author(s):  
Ke Zhang ◽  
Vincent Cocquempot ◽  
Bin Jiang
Keyword(s):  
Discrete Time ◽  
Dynamic Systems ◽  
Continuous Time ◽  
Adjustable Parameter ◽  
Observer Design ◽  
Fault Estimation ◽  
Time Dynamic ◽  
Multi Objective

Modelling of Continuous-Time Dynamic Systems

2007 ◽  
pp. 249-273
Author(s):  
Louis G. Birta ◽  
Gilbert Arbez
Keyword(s):  
Dynamic Systems ◽  
Continuous Time ◽  
Time Dynamic

scholarly journals Observer Design for Simultaneous State and Fault Estimation for a Class of Discrete-time Descriptor Linear Models

2021 ◽  
Vol 229 ◽  
pp. 01020
Author(s):  
Kaoutar Ouarid ◽  
Abdellatif El Assoudi ◽  
Jalal Soulami ◽  
El Hassane El Yaagoubi
Keyword(s):  
Discrete Time ◽  
Linear Models ◽  
Estimation Error ◽  
Equivalent Form ◽  
Observer Design ◽  
Fault Estimation ◽  
Linear Matrix ◽  
Sensor Faults ◽  
Actuator Faults ◽  
Algebraic Equations

This paper investigates the problem of observer design for simultaneous states and faults estimation for a class of discrete-time descriptor linear models in presence of actuator and sensor faults. The idea of the present result is based on the second equivalent form of implicit model [1] which permits to separate the differential and algebraic equations in the considered singular model, and the use of an explicit augmented model structure. At that stage, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. Next, the explicit structure of the augmented model is established. Then, an observer is built to estimate simultaneously the unknown states, the actuator faults, and the sensor faults. By using the Lyapunov approach, the convergence of the state estimation error of the augmented system is analyzed, and the observer’s gain matrix is achieved by solving only one linear matrix inequality (LMI). At long last, an illustrative model is given to show the performance and capability of the proposed strategy.

Data-driven fault identifiability analysis for discrete-time dynamic systems

2020 ◽  
Vol 51 (2) ◽  
pp. 404-412
Author(s):  
Fangzhou Fu ◽  
Dayi Wang ◽  
Wenbo Li ◽  
Fanbiao Li
Keyword(s):  
Discrete Time ◽  
Dynamic Systems ◽  
Data Driven ◽  
Identifiability Analysis ◽  
Time Dynamic

Stability of Markov modulated discrete-time dynamic systems

Automatica ◽  
2003 ◽  
Vol 39 (8) ◽  
pp. 1339-1351 ◽  
Author(s):  
G. Yin ◽  
Q. Zhang
Keyword(s):  
Discrete Time ◽  
Dynamic Systems ◽  
Time Dynamic ◽  
Markov Modulated
Sign in / Sign up

Export Citation Format

Share Document