Hybrid model identification for fault diagnosis of non-linear dynamic processes

2004 ◽  
Author(s):  
S. Simani
Keyword(s):  
Fault Diagnosis ◽  
Hybrid Model ◽  
Model Identification ◽  
Dynamic Processes ◽  
Linear Dynamic ◽  
Non Linear

Fault diagnosis for flight control systems using subspace method and adaptive two-stage Kalman filter

2016 ◽  
Vol 38 (12) ◽  
pp. 1480-1490 ◽  
Author(s):  
Jianchen Wang ◽  
Xiaohui Qi
Keyword(s):  
Kalman Filter ◽  
Fault Diagnosis ◽  
Control Systems ◽  
Linear Model ◽  
Flight Control ◽  
Model Identification ◽  
Identification Algorithm ◽  
Actuator Fault ◽  
Two Stage ◽  
Non Linear

Model-based fault diagnosis has attracted considerable attention from researchers and developers of flight control systems, thanks to its hardware simplicity and cost-effectiveness. However, the airplane model, which is adopted commonly in fault diagnosis, only exists theoretically and is linearized in approximation. For this reason, uncertainties such as system non-linearity and subjectivity will degrade the fault diagnosis results. In this paper, we propose a novel actuator fault diagnosis scheme for flight control systems based on model identification techniques. With this scheme, system identification can be achieved with a linear model that uses a closed-loop subspace model identification algorithm, and a non-linear model that uses an extended state observer and neural networks. On this basis, the current actuator fault is estimated using an adaptive two-stage Kalman filter. Finally, the non-linear six-degree-of-freedom model of a B747 airplane is simulated in the Matlab/Simulink environment, where the effectiveness of the proposed scheme is verified from fault diagnosis tests.

scholarly journals Predictive Control of the Iron Ore Beneficiation Process Based on the Hammerstein Hybrid Model

2019 ◽  
Vol 13 (4) ◽  
pp. 262-270
Author(s):  
Olga Porkuian ◽  
Vladimir Morkun ◽  
Natalia Morkun ◽  
Oleksandra Serdyuk
Keyword(s):  
Hybrid Model ◽  
Predictive Control ◽  
Iron Ore ◽  
Parallel Model ◽  
Error Criterion ◽  
Minimum Error ◽  
Linear Dynamic ◽  
Non Linear

Abstract Non-linear, dynamic, non-stationary properties characterize objects of the iron ore beneficiation line. Therefore, for their approximation, it is advisable to use models of the Hammerstein class. As a result of comparing the three models of Hammerstein: simple, parallel and recursive-parallel, it was shown that the best result for identifying the considered processes of magnetic beneficiation of iron ore by the minimum error criterion was obtained using the Hammerstein recursive-parallel model. Hence, it is recommended for the identification of beneficiation production objects.

ON THE DIFFERENTIAL REALIZATION THEORY OF NON-LINEAR DYNAMIC PROCESSES IN HILBERT SPACE

2015 ◽  
Vol 97 (4) ◽  
pp. 495-532 ◽  
Author(s):  
V. A. Rusanov ◽  
A. V. Daneev ◽  
A. V. Lakeev ◽  
Yu. É. Linke
Keyword(s):  
Hilbert Space ◽  
Dynamic Processes ◽  
Realization Theory ◽  
Linear Dynamic ◽  
Non Linear
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