Automated simulation of robotic dynamic systems using a new fuzzy-fractal-genetic approach

Author

Castillo, Oscar ; Melin, Patricia

Author_Institution

Dept. of Comput. Sci., Tijuana Inst. of Technol., Chula Vista, CA, USA

Volume

1

fYear

2000

fDate

7-10 May 2000

Firstpage

245

Abstract

We describe a new method for automated simulation of nonlinear dynamical systems. This method is based on a hybrid fuzzy-fractal-genetic approach to achieve, in an efficient way, automated simulation of a particular dynamical system given its mathematical model. The use of genetic algorithms is to achieve automated parameter selection for the mathematical models. The use of fuzzy logic is to simulate the process of expert behavior identification, by implementing the knowledge of identification by a set of fuzzy rules. We also use the concept of the fractal dimension of a time series to help make this identification more accurate. Experimental results for the case of robotic dynamic systems show the efficiency and accuracy of this new method for the simulation of complex nonlinear dynamical systems

Keywords

fractals; fuzzy logic; genetic algorithms; identification; nonlinear dynamical systems; robot dynamics; simulation; time series; fractal dimension; fuzzy logic; fuzzy rules; genetic algorithms; identification; nonlinear dynamical systems; robot dynamics; time series; Computational modeling; Computer science; Difference equations; Differential equations; Fuzzy logic; Genetic algorithms; Mathematical model; Nonlinear dynamical systems; Numerical simulation; Robotics and automation;

fLanguage

English

Publisher

ieee

Conference_Titel

Fuzzy Systems, 2000. FUZZ IEEE 2000. The Ninth IEEE International Conference on

Conference_Location

San Antonio, TX

ISSN

1098-7584

Print_ISBN

0-7803-5877-5

Type

conf

DOI

10.1109/FUZZY.2000.838666

Filename

838666