A takagi-sugeno type controller for mobile robot navigation
Authors: Iancu, I., Colhon, M. and Dupac, M.
Pages: 29-34
Abstract:Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decomposing the input space into several partial fuzzy spaces and representing the output space with a linear equation. The output control action is obtained from the rule-base and a set of crisp inputs. A Takagi-Sugeno type Fuzzy Logic Controller (FLC), to work with crisp data, intervals and fuzzy sets inputs, is proposed in connection with a mobile robot navigation model. The model also works with a set of t-norms, and for any t-norm an output value is obtained. Finally, these outputs are combined to obtain the overall output of the system.
Source: Scopus
A Takagi-Sugeno Type Controller for Mobile Robot Navigation
Authors: Iancu, I., Ghindeanu, M. and Dupac, M.
Editors: Grigoriu, M., Mladenov, V., Bulucea, C.A., Martin, O. and Mastorakis, N.
Pages: 29-35
Publisher: WSEAS Press
Place of Publication: US
ISBN: 978-960-474-179-3
Abstract:Fuzzy set theory and fuzzy logic are the convenient tools for handling uncertain, imprecise, or unmodeled data in intelligent decision-making systems. The utility of fuzzy logic in system controls domain is presented in the context of a mobile robot navigation control application. The Takagi-Sugeno controller is a fuzzy model capable of approximating a wide class of nonlinear systems by decomposing the input space into several partial fuzzy spaces and representing the output space with a linear equation. The output control action is obtained from the rule-base and a set of crisp inputs. A Takagi-Sugeno type Fuzzy Logic Controller (FLC), to work with crisp data, intervals and fuzzy sets inputs, is proposed in connection with a mobile robot navigation model. The model also works with a set of t-norms, and for any t-norm an output value is obtained. Finally, these outputs are combined to obtain the overall output of the system.
http://www.wseas.us/conferences/2010/bucharest/ci/index.html
Source: Manual
Preferred by: Mihai Dupac