Process control of pH neutralization based on adaptive algorithm of universal learning network

This paper presents an adaptive algorithm of universal learning network (ULN) and its application to identify pure time delay of a plant model. Universal learning network can be used in model predictive control for stabilizing a class of nonlinear systems with long time delay. Depending on ULN model with single neuron controller, the control architectures are introduced and applied to pH neutralization process. Simulation results prove the applicability and effectiveness of the ULN model. The general architecture and adaptive learning algorithm give ULN more representing abilities to model and control the nonlinear black box systems with long time delay.