This paper is concerned with the problems of robust state estimation and fault reconstruction for a class of time-delay systems with uncertainty. First, a sliding mode observer (SMO) is synthesized to achieve system state estimation. The basic design idea consists of exploiting the SMO concept with an adequate choice of a Lyapunov-Krasovskii functional and the Linear Matrix inequality (LMI) technique. Besides, the developed SMO can force the state estimation error to converge to zero and can drive and maintain this error on the sliding surface in finite time. Thereafter, using the developed SMO and introducing the Bounded Real Lemma (BRL) and the$H_{\infty}$concept, a robust actuator fault reconstruction scheme is established. A numerical example is given to illustrate the validity and the applicability of the proposed approaches. At last, a Williams-Otto reactor is introduced to prove the effectiveness of the proposed approaches.

This article evaluates fault tolerant control (FTC) in a specific group of delayed systems that involve actuator faults, uncertainty, and time-delay. To address this problem, a separated approach fault tolerant control technique (SFFTC) is introduced. The FTC element is developed based on fault estimation, which works to counteract the consequences of faults. The primary goal of FTC is to maintain desired performance standards of stability and robustness, incorporating$H$∞performance while mitigating the effects of actuator faults, decreasing uncertainty, and minimizing delay impact. The proposed approach's effectiveness is demonstrated through its implementation in a two-stage chemical reactor system.

This paper is concerned with the problems of sliding mode observer (SMO) design and robust fault reconstruction for one-sided Lipschitz (OSL) nonlinear systems with uncertainty and time-delay. Bounded uncertainty and varying time-delay are considered. First, the linear matrix inequality (LMI) optimization and a Lyapunov-Krasovskii functional are exploited to obtain a new observer. A sufficient condition is given such that the reachability condition can be ensured. Then, using the new SMO and by selecting an appropriate Lyapunov-Krasovskii functional, the$H_{\infty}$concept and a bounded real lemma (BRL), a robust actuator fault reconstruction is achieved. At last, a single-link flexible joint robotic system is included to illustrate the validity and the applicability of the proposed approaches.

this paper studies the problem of simultaneously estimating the state and the fault of linear stochastic discrete-time varying systems with unknown disturbances. The method is based on the assumption that no prior knowledge about the dynamical evolution of the fault and the disturbance is available. As the fault affects both the state and the output, but the disturbance affects only the state systems. We study the case when the direct feedthrough matrix of the fault has full rank. This paper extends previous work by considering that the noises affect the state and measurement output are correlated. A numerical example is given in order to illustrate the performance of the proposed filter.

In this paper, we propose to apply the dynamic Bayes approach, to optimise the maintenance program for locomotive diesel engines of the SNCFT company. This approach is based on subjective probability. It permits us to follow the evolution of the failing average rate and in particular to deduce ageing phenomena to supervise the work safety, availability and reliability.