Sliding mode observers for fault detection and isolation

By Chee Pin Tan. 2002

857 citations recorded by the source corpus.

View Paper: https://www.semanticscholar.org/paper/faa6f72ed1f7cc12f35545694c8f676352402d08

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Citations in the corpus

Finite-time converging jump observer for switched linear systems with unknown inputs ☆ (2011, methodology): “…Barbot et al. (2002), Xiong and Saif (2001)) are widely used due to their attractive features of: a) insensitivity with respect to a class of unknown inputs; b) possibility of using the equivalent output injection principle for the unknown input identification (see, e.g. Edwards et al. (2000)).”
Recent Advances on Recursive Filtering and Sliding Mode Design for Networked Nonlinear Stochastic Systems: A Survey (2013, methodology): “Most research on SMO design has been carried out along this line; see, for example, [141, 142, 144–149].”
A bounded-error approach to simultaneous state and actuator fault estimation for a class of nonlinear systems (2017, methodology): “estimation methods, essentially observer–based [24, 25, 26, 27], Kalman filter– based [28], or parameter identification–based [29] are used.”
Sliding mode observers: a survey (2008, background): “Their main advantages in this domain are that they exhibit fundamental robustness against certain kinds of parameter variations and that they also enable faults and/or values of immeasurable system parameters to be reconstructed using the principle of the equivalent injection signal (Edwards et al. ”
Nonlinear robust fault reconstruction and estimation using a sliding mode observer (2007, methodology): “More recently Edwards et al. (2000) proposed an approach based on the concept of equivalent output injection in which the resulting reconstruction signal can approximate the fault to any required accuracy. This is called ‘precise’ fault reconstruction in this paper. Later it was extended by Tan and ”
Robust Model-Based Fault Diagnosis for PEM Fuel Cell Air-Feed System (2016, methodology): “In this part, an ST SMO-based fault reconstruction approach will be designed for the system (16) via equivalent output error injection technique [16].”
Observer design for systems with unknown inputs (2005, background): “Observers for systems with unknown inputs play an essential role in robust model-based fault detection (Chen and Patton, 1999; Edwards et al., 2000; Edwards and Spurgeon, 1998; Jiang et al., 2004; Saif and Xiong, 2003).”
Fault diagnosis of a class of nonlinear uncertain systems with Lipschitz nonlinearities using adaptive estimation (2010, background): “As described in Edwards, Spurgeon, and Patton (2000), under Assumption 1, there exists a linear transformation of coordinates z = Tx = [z>1 z > 2 ] > with z1 ∈ (n−p) and z2 ∈ p, such that • TAT−1 = [ A11 A12 A21 A22 ] , where the matrixA11 ∈ (n−p)×(n−p) is Hurwitz stable.”
Adaptive sensor and actuator fault estimation for a class of uncertain Lipschitz nonlinear systems (2016, methodology): “In [19, 20], actuator fault is reconstructed with the so-called equivalent output estimation error injection concept.”
Design of sliding mode unknown input observer for uncertain Takagi-Sugeno model (2007, unknown): “This interesting property has been utilized either for state estimation [7], [8], [9] and fault detection and isolation [10].”
H ∞ sliding mode observer design for a class of nonlinear discrete time‐delay systems: A delay‐fractioning approach (2012, background): “Remark 2: As pointed out in [7, 40], Assumption 1 is a constraint on the input matrix and implies that rank(B̄)≤rank(C̄).”
Observers design for uncertain Takagi-Sugeno systems with unmeasurable premise variables and unknown (2011, unknown): “Several approaches are reported in the literature along the last decades in order to design observers for nonlinear systems: the extended Kalman filtering [1,2], the methods based on Lyapunov functions [3,4], the methods based on coordinate transformation using canonical observer forms [5,6], the hi”
On Sliding Mode Observers for Systems with Unknown Inputs (2006, methodology): “Remark: These observers have also been recently used in the field of fault detection and identification [14], [28] where the unknown input w (in this case a fault) is reconstructed by analyzing the so-called equivalent output error injection (which is the counterpart of the equivalent control in the”
Robust discrete‐time nonlinear sliding mode state estimation of uncertain nonlinear systems (2007, methodology): “Continuous approximation of equivalent injection signal by using a small positive scalar was implemented in [31].”