Incipient Fault Detection Based on Robust Threshold Generators: A Sliding Mode Interval Estimation Approach

This paper presents an incipient fault detection framework for systems with process disturbances and sensor disturbances based on a novel proposed threshold generator. Firstly, the definition of incipient faults is given using the H? from the quantitative point of view. Then, from the generated residuals and RMS evaluation function, the threshold generator is proposed based on sliding mode interval estimation module to ensure that the RMS evaluation of residuals is less than the generated threshold. By using recent results of the bounded real lemma for internally positive systems, a set of su?cient conditions to detect incipient faults via linear matrix inequality (LMI) is presented. Case study on an electrical traction device is presented to verify the e?ectiveness of the proposed method

Stability of a class of switched positive linear time-delay systems

This paper addresses the problem of stability for a class of switched positive linear time-delay systems. As first attempt, the Lyapunov-Krasovskii functional is extended to the multiple co-positive type Lyapunov-Krasovskii functional for the stability analysis of the switched positive linear systems with constant time delay. A sufficient stability criterion is proposed for the underlying system under average dwell time switching. Subsequently, the stability result for system under arbitrary switching is presented by reducing multiple co-positive type Lyapunov-Krasovskii functional to the common co-positive type Lyapunov-Krasovskii functional. A numerical example is given to show the potential of the proposed techniques. Copyright © 2012 John Wiley & Sons, Ltd.Xudong Zhao, Lixian Zhang and Peng Sh

International Journal of Robust and Nonlinear Control

This paper addresses the problem of estimating the state for a class of uncertain discrete-time linear systems with constraints by using an optimization-based approach. The proposed scheme uses the moving horizon estimation philosophy together with the game theoretical approach to the H∞ filtering to obtain a robust filter with constraint handling. The used approach is constructive since the proposed moving horizon estimator (MHE) results from an approximation of a type of full information estimator for uncertain discrete-time linear systems, named in short H∞-MHE and H∞-full information estimator, respectively. Sufficient conditions for the stability of the H∞-MHE are discussed for a class of uncertain discrete-time linear systems with constraints. Finally, since the H∞-MHE needs the solution of a complex minimax optimization problem at each sampling time, we propose an approximation to relax the optimization problem and hence to obtain a feasible numerical solution of the proposed filter. Simulation results show the effectiveness of the robust filter proposed