zbMATH — the first resource for mathematics

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.

a & b logic and
a | b logic or
!ab logic not
abc* right wildcard
"ab c" phrase
(ab c) parentheses
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)
Decomposition of a complex fuzzy controller for the truck-and-trailer reverse parking problem. (English) Zbl 1136.93374
Summary: The use of fuzzy logic has, in the last twenty years, become standard practice in the field of control. The reason lies in the fuzzy logic’s ability to relatively quickly transfer uncertain experience and knowledge about the observed object’s behaviour into the process of decision making. Nevertheless, one of the biggest problems that arises when using a fuzzy approach is the large number of fuzzy rules that have to be processed in order to produce one decision (i.e. one control output). The number of rules in a fuzzy controller primarily originates from the number of input variables that are entering the decision process and one possible solution for decreasing it is to use the method of decomposition. Its main goal is to implement the equivalent control functionality with a hierarchy of simpler fuzzy controllers. Their main characteristic is a lower number of input variables, which as a consequence leads to a smaller number of fuzzy rules. In our paper we apply the decomposition approach to the classical complex control case of the Truck-and-Trailer (T&T) reverse parking control problem. In such cases the implementation of control using only one fuzzy controller is very complex and the existing solutions, in some details, even deviate from the classical fuzzy approach. Our solution is, on the other hand, based only on the uncertain knowledge about the behaviour of the T&T driver and the results achieved are even better than those achieved by using the existing solutions.
93C42Fuzzy control systems
93B50Synthesis problems
93A13Hierarchical systems