An adaptive fuzzy neural network control system in cylindrical grinding process was proposed. In this system, the initial cylindrical grinding parameters were decided by the expert system based on fuzzy neural network. Multi-feed and setting overshoot optimization methods were also adopted during the grinding process, and a human machine cooperation system (composed of human and two fuzzy – neural networks) could revise the process parameters in real-time. The experiment of the cylindrical grinding was implemented. The results showed that this control system was valid, and could greatly improve the cylindrical grinding quality and machining efficiency.