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The suspension culture of animal cells is the preferred choice for large-scale culture of animal cells because of its advantages of fast cell proliferation and high production efficiency. The process of animal cells suspension culture is a multi-input and multi-output system with its nonlinear and strong coupling. The control of some biological parameters, such as cell density, matrix concentration and product concentration, is the key to improving the whole production level. The method of neural network inverse system was applied to control the suspension culture of animal cells. According to the characteristics of the culture process, the corresponding mathematical model is given and the reversibility of the system is proved. The inverse system of the original system is identified by the nonlinear approximation of neural network, then it is connected in front of the original system to form a pseudo linear composite system. Thus the process of animal cell suspension culture is linearly decoupled into three subsystems: first order linear cell density subsystem, first order linear matrix concentration subsystem and first order linear product concentration subsystem. Finally, the fuzzy PID controller is designed to control the decoupled linear subsystems, which avoids the difficulty of selecting the optimal parameters of the conventional PID controller. The simulation results show that the method of neural network inverse system can realize the linearization and decoupling of the process of animal cell suspension culture, and the system can realize high performance tracking control for the given input.