A Novel Simplified Foraging Optimization Algorithm for Parameter Identification of Nonlinear System Model

A simplified E.Coli foraging optimization algorithm based on the chemotactic behaviour of E.Col is presented in this paper in order to solve the parameter estimation of nonlinear system model (NSM). The simplified E.Coli algorithm consists of a tumbling operator and a swimming operator and at the same time the optimal position of individual E.Coli and the location of all E.Coli swarm are adopted to update the locations of swarm. The effectiveness of the proposed simplified E.Coli foraging optimization algorithm is demonstrated by simulation experiments on the parameter estimation of the NSM for heavy oil thermal cracking. The results indicate that the simplified E.Coli model is valid and provides an attractive method for the estimation of parameters of NSM.