A neural-network-based control scheme is presented to control unknown nonlinear dynamic processes. A multilayered feedforward neural network is used to model the process dynamics, and the control input is estimated by an extended Kalman filter based on the neural model. The effectiveness of the proposed scheme is verified by both simulations and experiments.