A P systems based hybrid optimization algorithm for parameter estimation of FCCU reactor–regenerator model

Abstract

Fluid catalytic cracking unit (FCCU) reactor–regenerator is a complex multivariable system and suitable model is useful to understand and design FCCU reaction–regeneration processes. Inspired by the concepts of P systems (membrane computing) and quantum computing, a P systems based hybrid optimization algorithm (PHOA) is proposed to estimate the parameters of FCCU reactor–regenerator model. The expansion of the search space makes the novel algorithm realize exploration and the dynamic contraction of the search space makes it realize exploitation. The quantum update rules and adaptive mutation rule in combination with the new membrane structure contribute to the improvement of global searching performance. Studies on some benchmark functions indicate that the PHOA outperforms DNA based genetic algorithm (DNA-GA) and genetic algorithm (GA) both in search efficiency and accuracy. With the parameters obtained by PHOA, the transfer function matrix model of FCCU reactor–regenerator in an oil refinery is established. Experimental results reveal that model curves gained by this proposed method are in good agreement with the measured data with smaller sum of squared error. The effectiveness of the model is also validated by experiments.