The problem of active vibration control of a plate has been vastly researched and described in recent years. Theoretical and experimental results demonstrate the effectiveness of the designed controllers and indicate the potential of control techniques for reducing transient and steady state dynamics in structural acoustic systems. The examples from the computational studies, confirmed that vibration levels could be effectively reduced, however, the implementation procedures are not yet ideal, still exists the gap between experimental and simulations findings. To overcome this problem, authors propose extension for the Fuzzy-PID controller, with an on-line identification technique coupled with a control scheme, for a plate vibration suppression. It is assumed, that the system to be regulated is unknown, the control schemes presented in this work have the ability to identify and suppress a plate vibrations with only an initial estimate of the system order. A prediction method implemented was designed using a neural network (NN) identification algorithm, based on the well-known Runge-Kutta methods. This algorithm is similar to described by Wang and Lin [14], but it uses a computation structure of Runge-Kutta-3/8, with radial cosine basis neural network.