A fuzzy controller with various T-norms applied in robot navigation

Authors:
Ion Iancu;Mihaela Colhon;Mihai Dupac
Affiliations:
Department of Computer Science, University of Craiova, Romania;Department of Computer Science, University of Craiova, Romania;Department of Design, Engineering and Computing, Bournemouth University, Poole, United Kingdom
Venue:
WSEAS Transactions on Systems and Control
Year:
2010

Citing 8
Cited 0

Dynamic Motion Planning for Mobile Robots Using Potential Field Method

Autonomous Robots
Induction motor drive using fuzzy logic

ISTASC'07 Proceedings of the 7th Conference on 7th WSEAS International Conference on Systems Theory and Scientific Computation - Volume 7
Modelling of rough-fuzzy classifier

WSEAS TRANSACTIONS on SYSTEMS
Optimal adaptive fuzzy control for a class of unknown nonlinear systems

WSEAS Transactions on Systems and Control
Properties of fuzzy systems

WSEAS TRANSACTIONS on SYSTEMS
Towards an approach of fuzzy control motion for mobile robots in unknown environments

WSEAS TRANSACTIONS on SYSTEMS
Interactive Fuzzy Interval Reasoning for smart Web shopping

Applied Soft Computing
Mamdani FLC with Various Implications

SYNASC '09 Proceedings of the 2009 11th International Symposium on Symbolic and Numeric Algorithms for Scientific Computing

Quantified Score

Hi-index	0.00

Visualization

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 subspaces 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.