Parameter identification of dynamical systems

This paper deals with the problem of identification of the unknown parameters of a dynamical system. Our work in this paper largely simulation related, follows the approach suggested by Kim and Lee [IEEE Int. Conf. Neural Networks (1993) 438-443] and it depends on the introduction of auxiliary polynomial. The merit of our work lies on the facts that no assumptions are placed on the stability of auxiliary polynomial and also that it does not require the a priori knowledge of the stability of the dynamical system, in question. Our method applies to both linear and quasi-linear dynamical systems. The results obtained involve the construction of appropriate neural networks. A variety of configurations of the dynamical systems are considered for simulation.