An application of a hybrid algorithm to identification of parameters of semi-empirical model describing a real process

In the paper the problem of identification is formulated and solved using a hybrid algorithm. The identification means calculation of parameters of a model describing a real process. The method proposed is applied to a semi-empirical model of the working cycle of an engine which enables calculations of the pressure courses in a cylinder. The identification procedure determines the values of the computational model parameters in order to ensure the minimal difference between the measured and calculated pressure courses in the cylinder. The identification is performed by solving dynamic optimization task using a hybrid approach. In the hybrid algorithm genetic algorithms are connected with the gradientless Nelder-Mead method. Results of the identification for different vectors of input to the model are presented as well.