Simultaneous actuator and sensor fault reconstruction of singular delayed linear parameter varying systems in the presence of unknown time varying delays and inexact parameters

Abstract

In this article, robust fault diagnosis of a class of singular delayed linear parameter varying systems is considered. The considered system has delayed dynamics with unknown time varying delays and also it is affected by noise, disturbance and faults in both actuators and sensors. Moreover, in addition to the aforementioned unknown inputs and uncertainty, another source of uncertainty related to inexact measures of the scheduling parameters is present in the system. Making use of the descriptor system approach, sensor faults in the system are added as additional states into the original state vector to obtain an augmented system. Then, by designing a suitable proportional double integral unknown input observer (PDIUIO), the states, actuator, and sensor faults are estimated. The uncertainty due to the mismatch between the inexact parameters that schedule the observer and the real parameters that schedule the original system is formulated with an uncertain system approach. In the PDIUIO, the uncertainty induced by unknown inputs (disturbance, noise and actuator, and sensor faults), unknown delays, and inexact parameter measures are attenuated in H ∞ sense with different weights. The constraints regarding the existence and the robust stability of the designed PDIUIO are formulated using linear matrix inequalities. The efficiency of the proposed method is verified using an application example based on an electrical circuit. K E Y W O R D Sactuator and sensor fault reconstruction, inexact parameters, multiple unknown time varying delays, proportional double integral unknown input observer, singular delayed linear parameter varying systems

Robust fault estimation for T‐S fuzzy systems with intermittently sampled data based on finite information learning observer

“…Some studies investigated the problem of actuator fault estimation in linear parametric variable systems. [12][13][14] Some authors described an integrated fault estimation (FE) and fault tolerant control (FTC) strategy for a class of uncertain Lipschitz systems. [15][16][17] However, Fuzzy logic control is a method to deal with complex nonlinear systems, and T-S fuzzy modeling is one of its branches.…”

“…For these reasons, fault estimation for dynamic systems has received a lot of attention from scholars. Some studies investigated the problem of actuator fault estimation in linear parametric variable systems 12‐14 . Some authors described an integrated fault estimation (FE) and fault tolerant control (FTC) strategy for a class of uncertain Lipschitz systems 15‐17 .…”