Abstract
A new technique, based on differential evolution algorithm, is proposed for solving the parameter identification problem of nonlinear systems. The technique improves the accuracy of parameter identification. Two kinds of process systems have been used as examples for demonstration. The effectiveness of differential evolution algorithm is compared with that of genetic algorithms in terms of obtained parameter accuracy and objective function value. The simulation results show that the accurate estimation of unknown system parameters and small values of objective function can be achieved by the proposed technique.