zbMATH — the first resource for mathematics

Examples
Geometry Search for the term Geometry in any field. Queries are case-independent.
Funct* Wildcard queries are specified by * (e.g. functions, functorial, etc.). Otherwise the search is exact.
"Topological group" Phrases (multi-words) should be set in "straight quotation marks".
au: Bourbaki & ti: Algebra Search for author and title. The and-operator & is default and can be omitted.
Chebyshev | Tschebyscheff The or-operator | allows to search for Chebyshev or Tschebyscheff.
"Quasi* map*" py: 1989 The resulting documents have publication year 1989.
so: Eur* J* Mat* Soc* cc: 14 Search for publications in a particular source with a Mathematics Subject Classification code (cc) in 14.
"Partial diff* eq*" ! elliptic The not-operator ! eliminates all results containing the word elliptic.
dt: b & au: Hilbert The document type is set to books; alternatively: j for journal articles, a for book articles.
py: 2000-2015 cc: (94A | 11T) Number ranges are accepted. Terms can be grouped within (parentheses).
la: chinese Find documents in a given language. ISO 639-1 language codes can also be used.

Operators
a & b logic and
a | b logic or
!ab logic not
abc* right wildcard
"ab c" phrase
(ab c) parentheses
Fields
any anywhere an internal document identifier
au author, editor ai internal author identifier
ti title la language
so source ab review, abstract
py publication year rv reviewer
cc MSC code ut uncontrolled term
dt document type (j: journal article; b: book; a: book article)
Actuator fault diagnosis: An adaptive observer-based technique. (English) Zbl 0858.93040
An adaptive observer technique is considered for the detection and diagnosis of actuator faults in deterministic systems. Two observers, a fixed detection observer, and an adaptive diagnostic observer are constructed separately to detect and diagnose the fault. A general situation where the system is under either model uncertainty or external disturbances is discussed in detail and a modification of the adaptive diagnostic algorithm is proposed to enhance robustness. Under the assumption that the observer gain matrix can be selected such that the resulting observation error is strictly positive real, it is shown that the adaptive diagnostic algorithms yield a desired dynamic performance for fault diagnosis. Furthermore, the selection of the threshold for fault detection is discussed, and some simulation examples are given.
MSC:
93C40Adaptive control systems
90B25Reliability, availability, maintenance, inspection, etc. (optimization)
93B07Observability