In this paper, the robust fault detection filter design problem for linear time invariant (LTI) systems with unknown inputs and modeling uncertainties is studied. The basic idea of our study is to formulate the robust fault detection filter design as a H∞ model-matching problem. A solution of the optimal problem is then presented via a linear matrix inequality (LMI) formulation. The main result...

In this paper, we address fault-tolerant control for non-linear plants. We perform soft fault detection and isolation for partial fault detection. A new method is proposed that combines model predictive controllers with fuzzy Takagi-Sugeno models. An example is presented to illustrate the functionality of the proposed approach. Keywords— Fault detection and isolation, multiple models, fuzzy Tak...

In diagnostic testing faults detectable by test vectors are partitioned into groups. This partitioning is such that a fault is distinguishable from faults in all other groups, but is indistinguishable from those in its own group. Diagnostic fault coverage (DC) is defined as the number of fault groups divided by the total number of faults. We present a new diagnostic fault simulation algorithm t...

Guaranteeing 100% fault free products is becoming an emerging standard in many branches of manufacturing. This paper addresses the design of an end–quality diagnostic system for detection of mechanical faults in electronically commutated motors. One of the main requirements of an end–quality diagnostic system is its ability for detecting faults in their earliest stages. Main issue in detecting ...

In this paper, fault tolerant compensation for non-linear plants is addressed. Soft fault detection and isolation is performed for a partial sensor fault detection. New method is proposed that combine model predictive controllers with fuzzy Takagi-Sugeno models. An example is presented that illustrates the functionality of the proposed method. Keywords— Fault tolerant control, Fault detection a...

In the paper, two novel negative selection algorithms (NSAs) were proposed: FB-NSA and FFB-NSA. FBNSA has two types of detectors: constant-sized detector (CFB-NSA) and variable-sized detector (VFBNSA). The detectors of traditional NSA are generated randomly. Even for the same training samples, the position, size, and quantity of the detectors generated in each time are different. In order to el...