Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters
Peer reviewed, Journal article
Accepted version
Permanent lenke
https://hdl.handle.net/11250/3050595Utgivelsesdato
2020Metadata
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Originalversjon
Gómez‐Peñate, S., López‐Estrada, F. R., Valencia‐Palomo, G., Rotondo, D., & Guerrero‐Sánchez, M. E. (2021). Actuator and sensor fault estimation based on a proportional multiple‐integral sliding mode observer for linear parameter varying systems with inexact scheduling parameters. International Journal of Robust and Nonlinear Control, 31(17), 8420-8441. 10.1002/rnc.5371Sammendrag
This article proposes an approach for the estimation of states, actuator, and sensor faults in nonlinear systems represented by a polytopic linear parameter varying (LPV) system with inexact scheduling parameters. In the traditional LPV approaches, the scheduling variables are considered to be perfectly known. However, in practical applications, their measurement may contain precision and calibration errors or noise that can affect the performance of the diagnostic systems. Therefore, this work proposes the design of a proportional multiple-integral sliding mode observer for fault diagnosis (FD) that copes with LPV systems with inexact scheduling parameters. Due to the introduction of some nonlinear functions, the proposed observer is a nonlinear parameter varying system for which stability and robustness performance are formulated using the Lyapunov technique and a H∞ performance criterion. It is shown that the design conditions boil down to a set of linear matrix inequalities whose solution allows computing the observer gain matrix along with the tunable parameters of the nonlinear functions. Results obtained using the simulator of an octocopter-type unmanned aerial vehicle are used to demonstrate the applicability and performance of the proposed FD scheme.