Feedforward Decoupling Intelligent Algorithm for Multivariable Based on FNN and Its Application in Biology Fermentation Control

The coupling relations of all variables during fermentation process with fermentation are discussed. Since the parameters are always changing as time-varying, nonlinearity and randomicity during biology fermentation control process. the scheme for biology fermentation control process using feed forward decoupling intelligent algorithm for multivariable based on FNN is presented. Fuzzy-Neural controller and decoupling units were designed independently, where the Fuzzy controller combined with neural network and the radial basis function neural network was employed for decoupling. The optimized training algorithm based on the system output error was used for online adjustment of network weights, thus realizing dynamic decoupling, which eliminated the need of identifying the plants. This method, with a simple architecture and a small amount of computation is proved to be effective by simulation and application results.