The control system, presented in this paper, is dedicated to maintain automatically the process of 15 N separation, by chemical exchange in Nitrox system, in its optimal operation conditions. For this purpose one of the most important task is: the minimization of the transient response and of the disturbances effects over the process. These requirements are fulfilled by applying a neuro-fuzzy feed-forward control configuration. Fuzzy logic control systems have been successfully applied to a wide variety of practical problems. The fuzzy systems have three significant advantages over conventional control techniques. They are cheaper to develop, cover a wider range of operating conditions, and are more flexible in terms of natural language. Unfortunately the parameters of a fuzzy control system are inherently difficult to tune for the purpose of improving behavior By integrating neural networks in fuzzy systems a new class of control systems results: -intelligent control systems. Intelligent control is a technology that replaces the human mind in making decisions, planning control strategies, and learning new functions whenever the environment does not allow or does not justify the presence of a human operator. The use of intelligent control systems has infiltrated the modern world. Specific features of intelligent control include decision making, adaptation to uncertain media, self-organization, planning and scheduling operations. Ver y often, no preferred mathematical model is presumed in the problem formulation, and information is presented in a descriptive manner. Therefore, it may be the most effective way to solve complex control tasks of chemical plants. General Architecture of the Control System The developed control system uses two controllers: feedback controller and feed-forward controller ( (1) The feedback controller, placed in the feedback loop, compares the process output y with the reference input r, and if there is a deviation e = r -y, the controller takes action according to the control strategy. The feedforward controller placed in the feed-forward loop reduces the transient response and compensates all measurable disturbances
