Two nonlinear control algorithms for controlling nonlinear systems include the receding horizon method and the nonlinear neural network inverse model methods. These methods have been found to be useful in dealing with difficult-to-control nonlinear systems, especially in simulated systems. However although much simulation work has been performed with these methods, simulation only is inadequate to guarantee that these algorithms could be successfully implemented in real plants. For this reason, a relatively low cost and simple online experimental configuration of a partially simulated continuous reactor has been devised which allows for the realistic testing of a wide range of nonlinear estimation and control techniques i.e. receding horizon control and neural network inverse model control methods. The results show that these methods are viable and attractive nonlinear methods for real-time application in chemical reactor systems.