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Identification of a nonlinear model in syntheticmicrobial systems

Liu Guangjun, Xu Xiaoping, Wang Feng

To well understand the mechanism of microbial behavior, mathematic models of microbial systems have become a key issue. In particular, it is important for complex microbial systems. Currently, in complex synthetic microbial systems, block oriented nonlinear model can be widely used to represent and approximate many real complex processes. In this paper, the parameter estimation approach for the Hammerstein model is investigated. The basic idea is as follows. Firstly, the nonlinear transfer function of the model can be converted to an intermediate model. Secondly, the estimates of the parameters of the intermediate model are found by using an improved fish swarm optimization algorithm. Thirdly, the relations of the parameters of the intermediate model and those of the Hammerstein model are established. Then, the estimates of the parameters of the Hammerstein model are obtained. Finally, in simulation experiment, compared with other methods, the simulation results show the effectiveness of the proposed algorithm.