“…& Remark 3. Theorem 2, provides a non-systematic way to determine the diagnosability of a class of nonlinear systems described by (9). Moreover, the proof gives the necessary number of outputs or sensors ðmÞ needed to construct the differential algebraic equation associated to the fault.…”
Section: On the Minimal Number Of Measurementsmentioning
confidence: 98%
“…In the next paragraphs some concepts concerning to the diagnosability problem will be presented [9,10].…”
Section: On the Diagnosability Conditionmentioning
confidence: 99%
“…Let consider system (9). The fault vector f is unknown and it can be assimilated as a state with uncertain dynamics.…”
“…& Remark 3. Theorem 2, provides a non-systematic way to determine the diagnosability of a class of nonlinear systems described by (9). Moreover, the proof gives the necessary number of outputs or sensors ðmÞ needed to construct the differential algebraic equation associated to the fault.…”
Section: On the Minimal Number Of Measurementsmentioning
confidence: 98%
“…In the next paragraphs some concepts concerning to the diagnosability problem will be presented [9,10].…”
Section: On the Diagnosability Conditionmentioning
confidence: 99%
“…Let consider system (9). The fault vector f is unknown and it can be assimilated as a state with uncertain dynamics.…”
“…Before proposing the exponential polynomial observer, a definition concerning on algebraic observability condition is given (for more details see [28]). Definition 1.…”
Section: A Note On Algebraic Observability Condition (Aoc)mentioning
“…Some model-based approaches can be found, as the approaches based upon differential geometric methods [4][5]. On the other hand there are approaches proposed in an algebraic and differential framework [6][7][8][9][10][11][12][13][14]. These approaches consist in the observation of the dynamics of the fault variables, which are defined as uncertain inputs [15].…”
In this paper, the fault diagnosis problem for nonlinear systems is treated, some results based on a differential algebraic approach are used in order to solve the diagnosis problem for nonlinear systems. A sliding mode observer is used for estimating the faults. A comparison with other observers is given to assess, via numerical simulations, the performance of the proposed observer.
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