Sensor fault reconstruction for a class of 2-D nonlinear systems with application to fault compensation

Abstract

This paper considers the problem of sensor fault reconstruction and compensation for a class of two dimensional (2-D) nonlinear systems. The 2-D nonlinear system is described by the Fornasini-Marchesini local state-space second model with Lipschitz nonlinearity. The sensor fault considered in this study could be of arbitrary form and its size can be even unbounded. An integrated fault/state observer is proposed to obtain the asymptotic estimation of sensor faults and system states at the same time. A sufficient condition for the existence of the integrated observer is given in terms of linear matrix inequalities. H ∞ sensor fault estimation/reconstruction is also considered for the 2-D nonlinear system when there are both sensor faults and input disturbances. Based on the estimation of sensor faults, a sensor compensation scheme can be performed by subtracting the fault term from the measurement output, and the existing output feedback controller can run normally without the switchover of sensors or reconfiguration when sensor faults occur. An example is provided to illustrate the effectiveness of the proposed method for both sensor fault reconstruction and compensation.

Sensor Fault Reconstruction based on Adaptive Sliding Mode Observer for Forklift Fault-Tolerant Control System

“…where f i denotes the i th sensor fault. If state variable z is defined as the first-order low-pass filtering output of y(t) [21], the sensor fault can be transformed into an actuator fault:…”

Fault diagnosis and compensation for two‐dimensional discrete time systems with sensor faults and time‐varying delays

“…As it is obvious that if and only if the square matrix l 2 is of full rank, is non‐singular. Hence, letting l 2 be non‐singular, then the following equations are obtained: Consider the following 2‐D DSAO for referring to …”

“…However, most of the reported results are for one‐dimensional (1‐D) systems. As we know, 2‐D systems have some special properties that are markedly different from its 1‐D counterpart, like insufficient time‐domain theory tools, two updating directions, and special observer constraints . Hence, most published 1‐D results cannot be extended into their 2‐D cases directly.…”

“…However, it should be noted that fault cases have not yet been taken into account in the studies of 2‐D time delay systems. Recently, the authors have achieved some preliminary results on FTC of 2‐D systems ; however, time delay and an integrated FTC design (it will be introduced in the following) are not considered in these studies. Based on the aforementioned discussion about 2‐D FTC, particularly the FTC of 2‐D delay systems, the insufficient state of the art, challenges, and the increasing demands from the practice have motivated this study.…”

Stochastic finite-time H∞ filtering for nonlinear Markovian jump systems with partly known transition probabilities

“…9 Their jump mode is governed by a Markovian stochastic process. 10–39 However in real engineering, Markovian transition probabilities (TPs) are not easy to obtain. Hence, it is meaningful to study the MJSs with deficient mode jump information.…”