One of the major challenges in industrial process control is to deal with nonlinearities in the plants. There have been a significant amount of research efforts towards design and development of appropriate, reliable and promising control techniques to deployed on real-time industrial applications. Some of the widely used and acknowledged control methods lack in terms of tuning unknown system parameters. The reason is their unadaptive or fixed nature. This paves the field well for adaptive controllers. Their biggest advantage is their automatic updation of unknown system paramters, that saves quite some resources and manpower and ensures an overall stable control strategy. In this regard, system modeling happens to be the prime and pertinent task so that it can set the basis for a stable control law synthesis. This reserach work proposes a polynomial adaptive model recently introduced called U-Model to be used for online system identification of Chemical Process Plant. U-Model is a simple, stable and reliable which has previously yielded encouraging results when applied to various application in different scenario. The aforementioned plant shall be used for investigation on its Flow process. The modeling results shall be compared and validated by other commonly known and utilized modeling structures. © 2017 IEEE.