Automated simulation of non-linear dynamical systems with a Lotka-Volterra population based approach

We describe a new method for the automated simulation of non-linear dynamical systems. This method is based on a hybrid fuzzy-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. Our genetic algorithm uses a Lotka-Volterra approach to change the size of the population in each generation. The use of fuzzy logic simulates 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