Grey wolf RNA-GA modeling method for FCCU main fractionator

This paper proposes a grey wolf RNA-GA modeling method for FCCU main fractionator. In this method, the grey wolf search strategy is used to design the new crossover operator to improve the local optimization ability, and the grey wolf RNA-GA algorithm is proposed. The validity of the grey wolf RNA-GA is illustrated with some typical test functions. The grey wolf RNA-GA is adopted for parameter estimation of the FCCU main fractionator model. The simulation results show that the proposed modeling method can accurately reflect the dynamic characteristics of the main fractionator.