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EN
A theoretical class of nonlinear systems is considered. An n-dimensional pipeline system is examined, as an example system, for investigating the effectiveness of a high-gain observer-based residual for detecting faults. Detailed conditions are given for the investigation of residual effectiveness, such as selection of operating points, control inputs, sensor faults, component faults, fault positions and observer eigenvalues. Then, for various values of n, defined fault types and defined fault positions, the observer-residual performance is noted and characteristics are derived and compared. Qualitative and quantitative evidence in graphical and table form shows, in several ways, how the performance and effectiveness of observer-based residuals change as n, and system complexity, increases.
EN
A robust fault detection observer (RFDO), which includes a robust residual, is designed for a general nonlinear system with polynomial-type nonlinearities. Two main theoretical results are given for the existence, stability and the detectability of the RFDO. The approach is applied to a three-tank hydraulic system where two fault scenarios are considered. Three different degree observers, with corresponding residuals, are assessed. This observer approach is then compared to the performance of a neural network approach under the same fault conditions.
EN
A fault detection observer is considered for a class of nonlinear models which consist of bilinear and polynomial nonlinearities up to degree N. The performance of the observer is assessed when applied to a three-tank system.
EN
A fault detection observer is proposed for classes of discrete nonlinear models which consist of bilinear and polynominal nonlinearities up to degree three. The observer is designed such that the error dynamics are independent of unknown inputs. Conditions are given, in an efficient compact form, for a robust fault detection observer to exist and be robust with respect to unknown inputs. A design procedure is presented for calculating the observer matrices and illustrated by an example.
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