ln control systems, the most natural way to model failures of hardware components is introducing additional inputs (fault inputs) that equal the difference between actual and assumed values of the faulty quantities. However, when applied to faults affecting the measure of the state of a nonlinear system, this natural modelling procedure results, in general, in non-standard models that are nonlinear in the fault inputs, whereas an affine dependence is desired to exploit the available fault detection and isolation techniques. A method has been proposed for modelling failures of the sensors measuring the state of a nonlinear system, so as to preserve the affine form in all (control and fault) inputs. As a result, for any physical sensor failure, a set of (always concurrent) fault inputs is introduced in the model, so that the problem of detecting and isolating any single sensor failure can be formulated according to the recently developed concept of Fault Set Detection and Isolation (FSDI). Through the analysis of a case study (the IFATIS Heating System Benchmark), we illustrate how to alternatively model the failure of a sensor, in particular, by a set of (always concurrent) fault inputs, so that the standard, affine in the inputs, form of nonlinear systems is kept. For this case study, we have provided a bank of residual generators that solve the sensor fault detection and isolation problem. With the model in this form, the recently developed idea of FSDI can be applied to detect sensor failures under the hypothesis of their non-concurrency. Simulations confirm the validity of this global nonlinear approach.
Detection and isolation of sensor faults in nonlinear systems: A case study
Aufspührung und Isolierung von Sensorfehlern in nichlinearen Systemen: Eine Fallstudie
2003
6 Seiten, 4 Bilder, 1 Tabelle, 8 Quellen
Conference paper
English
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