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Observer-based Fault Detection in Nonlinear Systems ; Beobachter gestützte Fehlererkennung in nichtlinearen Systemen
Interests in fault detection and isolation for nonlinear systems have grown significantly in recent years due to the fact that most of the systems, we face in practice, are nonlinear in nature. There exist a number of techniques for fault detection, among them; the so-called observer-based fault detection is widely studied. In addition, this technique has been proven efficient in detecting faults. In a typical observer-based scheme, the process of fault detection is carried out in two steps: residual generation and residual evaluation. The purpose of residual generation is to produce the so-called residual signal by comparing the process outputs with their estimates generated by the observer. Roughly speaking, the residual signal, thus generated, carries the information of faults only. It means that under fault-free operation, the residual should go to zero and deviates only in the presence of fault. However, due to model uncertainties and unknown inputs (process disturbances, measurement noises, and faults of no interest), the residual signal is non-zero even in the fault-free operation of the process. In order to extract the information of faults in the presence of model uncertainties and unknown inputs, additional efforts need to be done. The process of residual evaluation serves this purpose. In this step, some function of the residual signal (evaluation function) is compared with a bound, the so-called threshold, regarding all possible unknown inputs and model uncertainties. An alarm is generated if the former exceeds the later which shows the presence of fault. Selection of a suitable threshold is very critical task in fault detection. The performance of a typical fault detection system can be evolved by a threshold. If it is selected too low, some unknown inputs may cause the evaluated residual to cross it which results into a false alarm. Conversely, selecting it too high may result into a missed detection, which means some set of faults may remain undetected. This thesis presents novel methods for ...
Observer-based Fault Detection in Nonlinear Systems ; Beobachter gestützte Fehlererkennung in nichtlinearen Systemen
Interests in fault detection and isolation for nonlinear systems have grown significantly in recent years due to the fact that most of the systems, we face in practice, are nonlinear in nature. There exist a number of techniques for fault detection, among them; the so-called observer-based fault detection is widely studied. In addition, this technique has been proven efficient in detecting faults. In a typical observer-based scheme, the process of fault detection is carried out in two steps: residual generation and residual evaluation. The purpose of residual generation is to produce the so-called residual signal by comparing the process outputs with their estimates generated by the observer. Roughly speaking, the residual signal, thus generated, carries the information of faults only. It means that under fault-free operation, the residual should go to zero and deviates only in the presence of fault. However, due to model uncertainties and unknown inputs (process disturbances, measurement noises, and faults of no interest), the residual signal is non-zero even in the fault-free operation of the process. In order to extract the information of faults in the presence of model uncertainties and unknown inputs, additional efforts need to be done. The process of residual evaluation serves this purpose. In this step, some function of the residual signal (evaluation function) is compared with a bound, the so-called threshold, regarding all possible unknown inputs and model uncertainties. An alarm is generated if the former exceeds the later which shows the presence of fault. Selection of a suitable threshold is very critical task in fault detection. The performance of a typical fault detection system can be evolved by a threshold. If it is selected too low, some unknown inputs may cause the evaluated residual to cross it which results into a false alarm. Conversely, selecting it too high may result into a missed detection, which means some set of faults may remain undetected. This thesis presents novel methods for ...
Observer-based Fault Detection in Nonlinear Systems ; Beobachter gestützte Fehlererkennung in nichtlinearen Systemen
Khan, Abdul Qayyum (Autor:in) / Ding, Steven X.
20.01.2011
Hochschulschrift
Elektronische Ressource
Englisch
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