Robust integral-observer-based fault estimation for Lipschitz nonlinear systems with time-varying uncertainties

Abstract

This paper addresses the problem of state estimation and sensor fault reconstruction conjointly for a class of nonlinear systems with time-varying uncertainties for which the nonlinear characteristic satisfies the Lipschitz circumstance. A hybrid approach based on an integral observer and sliding-mode theory has been proposed in order to model sensor fault as a virtual actuator one. For the augmented model, the observer matching condition is not satisfied. To overcome this problem, a new method, which improves the design approach and enhances the rapidity of the fault estimation convergence, has been proposed. The fault estimation error effect is minimized by integrating the H ∞ disturbance attenuation level. The proposed design is formulated and derived as a linear matrix inequality problem. Parameters of this observer are calculated through the linear matrix inequality technique. The proposed method has been validated through an example of a single-link manipulator robot. Simulation results show that this approach can estimate the state and the sensor fault successfully, despite the time-varying uncertainties and the presence of unknown inputs.

Robust fault tolerant control based on adaptive observer for Takagi-Sugeno fuzzy systems with sensor and actuator faults: Application to single-link manipulator

“…Remark 2: Comparing with our work in Makni et al (2019) and method in Zemzemi et al (2019), this work not only investigates the estimation problem but also the closed-loop stability problem in presence of external disturbance and both sensor and actuator faults. Moreover, the efficiency of the FTC will be illustrated via an application to single-link flexible joint robot and a comparison with recent work.…”

Sliding-mode observer-based fault diagnosis and fault-tolerant control of the main drive system of rolling mill

“…In contrast, Nemati et al (2019) considered uncertain inputs and external perturbations to establish a nonlinear system model, designed a nonlinear observer to eliminate the effects of uncertainty and a nonlinear robust position input observer to isolate actuator faults, and finally used a generalized observer to estimate both faults and states. For time-varying systems, Zemzemi et al (2019) considered nonlinear time-varying uncertain systems that satisfy the Lipschitz condition, proposed a mixed method that models sensor faults as actuator faults based on an integral observer and sliding-mode theory, and proposed an improved design method to improve the fault estimation convergence speed and realize the state estimation and sensor fault reconfiguration. Through the above literature analysis, it has been concluded that observer-based FD techniques have matured, and in order to guarantee the normal operation of the system even after a fault occurs, FTC research is still needed.…”

Multi-fault diagnosis scheme based on robust nonlinear observer with application to rolling mill main drive system

“…However, the residual information contains information about the operating state of the system, which can be used as a basis for fault diagnosis (Gao et al, 2015). In the past few decades, the observer-based method as an effective means in fault diagnosis has been the focus of research in this field, for example, Luenberger observer (Chen et al, 2013), extended state observer (Naghdi and Sadrnia, 2020), unknown input observer (Delshad et al, 2016; Gupta et al, 2018), sliding mode observer (SMO; Rahnavard et al, 2019; Yu et al, 2020), proportional observer (Zemzemi et al, 2019), and so on.…”