Title :
A general method for automated simulation of non-linear dynamical 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
Abstract :
We describe in this paper a new method for automated simulation of non-linear 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 non-linear dynamical systems
Keywords :
fractals; fuzzy logic; genetic algorithms; identification; nonlinear dynamical systems; numerical analysis; robot dynamics; simulation; time series; accuracy; automated parameter selection; automated simulation; complex nonlinear dynamical systems; efficiency; expert behavior identification; fractal dimension; fuzzy logic; fuzzy rule; fuzzy-fractal-genetic approach; genetic algorithms; identification; mathematical model; nonlinear dynamical systems; robotic dynamic systems; time series; Computational modeling; Difference equations; Differential equations; Fuzzy logic; Genetic algorithms; Intelligent robots; Mathematical model; Nonlinear dynamical systems; Numerical simulation; Vectors;
Conference_Titel :
Evolutionary Computation, 1999. CEC 99. Proceedings of the 1999 Congress on
Conference_Location :
Washington, DC
Print_ISBN :
0-7803-5536-9
DOI :
10.1109/CEC.1999.785565
