Abstract: The bio-fermentation process has highly nonlinear, time-varying, higher and more variable and large uncertain characteristics. In order to achieve automatic control of the fermentation process, improve the level of production of biotechnology products, and make the detection of fermentation process parameters, operation monitoring and automatic control intelliget, we constructed a feedforward decoupling method for the multi-variable fuzzy neural control system, with analysising of the main factors affecting the fermentation process as well as the variable coupling and applicating the integrated application of the traditional PID control and fuzzy neural network technology. And the method is applicated in the fermentation process. While the problem of emissions and bacterial contamination of the tank leakage are solved with using the condensation, recovery, and the tail gas of fermentation technology. Fuzzy neural controller and decoupling are independent designed. Neural Network is introduced in the fuzzy controller, and the decoupling network applys a layer of hidden layer. Network weights are on-line adjusted based on a simplified learning algorithm according to the system output error.with the purpose of dynamic decoupling without the need to identify the controlled object model. The method is simple and computation, and the actual application results show that this algorithm has good control effect.