A novel approach for the actuator fault diagnosis of time-delay systems is presented by using an adaptive observer technique. Systems without model uncertainty are initially considered, followed by a discussion of a general situation where the system is subjected to either model uncertainty or external disturbance. An adaptive diagnostic algorithm is developed to diagnose the fault, and a modified version is proposed for general system to improve robustness. The selection of the threshold for fault detection is also discussed. Finally, a numerical example is given to illustrate the efficiency of the proposed method.
This paper deals with the problem of fault diagnosis problem for a class of linear systems with delayed state and uncertainty. The systems are transformed into two different subsystems. One is not affected by actuator faults so that a robust observer can be designed under certain conditions. The other whose states can be measured is affected by the faults. The proposed observer is utilized in an analytical-redundancy-based approach for actuator and sensor fault detection and diagnosis in time-delay systems. Finally, the applicability and effectiveness of the proposed method is illustrated through numerical examples.
Based on a new special co-inner-outer factorization, a factorization approach for design fault detection observer for LSFDJ was proposed. It is a simple state-space method and can deal with time-varying LSFDJ with sensor noise and sensor faults. The performance of the fault detection observer is optimized in an H ∞ setting, where the ratio between the gains from disturbance and fault to residual respectively is minimized. The design parameters of the detection observer were given in terms of the solution to the Riccati differential equation with jumps.
Proposes an H_∞ deconvolution design for time-delay linear continuous-time systems. We first analyze the general structure and innovation structure of the H_∞ deconvolution filter. The deconvolution filter with innovation structure is made up of an output observer and a linear mapping, where the latter reflects the internal connection between the unknown input signal and the output estimate error. Based on the bounded real lemma, a time domain design approach and a sufficient condition for the existence of deconvolution filter are presented. The parameterization of the deconvolution filter can be completed by solving a Riccati equation. The proposed method is useful for the case that does not require statistical information about disturbances. At last, a numerical example is given to demonstrate the performance of the proposed filter.
