scholarly journals Distributed Fault Detection and Isolation of Large-Scale Discrete-Time Nonlinear Systems: An Adaptive Approximation Approach

2012 ◽  
Vol 57 (2) ◽  
pp. 275-290 ◽  
Author(s):  
R. M. G. Ferrari ◽  
T. Parisini ◽  
M. M. Polycarpou
Keyword(s):  
Nonlinear Systems ◽  
Fault Detection ◽  
Discrete Time ◽  
Large Scale ◽  
Fault Detection And Isolation ◽  
Approximation Approach ◽  
Adaptive Approximation ◽  
Distributed Fault Detection

An unknown input observer-based decentralized fault detection and isolation for a class of large-scale interconnected nonlinear systems

2017 ◽  
Vol 40 (8) ◽  
pp. 2599-2606 ◽  
Author(s):  
Amir Abbasi ◽  
Javad Poshtan
Keyword(s):  
Nonlinear Systems ◽  
Fault Detection ◽  
Large Scale ◽  
Sufficient Conditions ◽  
Fault Detection And Isolation ◽  
Linear Matrix ◽  
Unknown Input ◽  
Unknown Input Observer ◽  
High Convergence Rate ◽  
Interconnected Nonlinear Systems

In this paper, using a bank of decentralized nonlinear unknown input observers, a novel scheme for actuator fault detection and isolation of a class of large-scale interconnected nonlinear systems is presented. For each of the interconnected subsystems, a local nonlinear unknown input observer is designed without the need to communicate with other agents. Sufficient conditions for the observer existence are derived based on the Lyapunov stability theory. To facilitate the observer design, the achieved conditions are formulated in terms of a set of linear matrix inequalities and optimal gain matrices are obtained. By using both system output and its difference with the estimated output in observer equation, each local observer shows a high convergence rate. Simulation of an automated highway system is used to demonstrate the effectiveness of the proposed methodology.

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