Decoupling Control Based on Fuzzy Neural-Network Inverse System in Marine Biological Enzyme Fermentation Process

Abstract

The marine biological enzyme fermentation process is a time-varying, nonlinear, uncertain, and multivariable system, so high performance decoupling control is a target to seek. A decoupling control method based on a fuzzy neural-network inverse system for the marine biological enzyme fermentation process is proposed, in which the inverse system linearizing method of the nonlinear system is combined with the nonlinear identifying technology of the fuzzy neural network. First, based on the characteristics of the fermentation process, the model of a fermentation system is obtained, and the reversibility of the system is proved. Second, the $a$ th-order inverse system of the fuzzy neural network is constructed and connected in series with the fermentation system to be a pseudo-linear compound system. Finally, closed-loop control is carried out to obtain good control performance by introducing an expert controller. The simulation experiments demonstrate that good control performance (high accuracy and good robust) can be obtained in the multivariable fermentation process based on the fuzzy neural-network inverse system.