Resumen

CUEVAS, Erik; GALVEZ, Jorge  y  AVALOS, Omar. Parameter Estimation for Chaotic Fractional Systems by Using the Locust Search Algorithm. Comp. y Sist. [online]. 2017, vol.21, n.2, pp.369-380. ISSN 2007-9737.  https://doi.org/10.13053/cys-21-2-2741.

Due to its multiple applications, parameter identification for fractional-order chaotic systems has attracted the interests of several research communities. In the identification, the parameter estimation process is transformed into a multidimensional optimization problem where fractional orders, as well as functional parameters of the chaotic system are considered the decision variables. Under this approach, the complexity of fractional-order chaotic systems tends to produce multimodal error surfaces for which their cost functions are significantly difficult to minimize. Several algorithms based on evolutionary computation principles have been successfully applied to identify the parameters of fractional-order chaotic systems. However, most of them maintain an important limitation; they frequently obtain sub-optimal results as a consequence of an inappropriate balance between exploration and exploitation in their search strategies. This paper presents an algorithm for parameter identification of fractional-order chaotic systems. In order to determine the parameters, the proposed method uses the evolutionary method called Locust Search (LS), which is based on the behavior of swarms of locusts. Different to the most of existent evolutionary algorithms, it explicitly avoids the concentration of individuals in the best positions, eliminating critical flaws such as the premature convergence to sub-optimal solutions and the limited exploration-exploitation balance. Numerical simulations have been conducted on the fractional-Order Van der Pol oscillator to show the effectiveness of the proposed scheme.

Palabras llave : Locust search; fractional-order systems; evolutionary computation; parameter identification; Van der Pol oscillator.