Modelling of continuous stirred tank reactor using artificial intelligence techniques

Abstract

Continuous Stirred Tank Reactor System (CSTR) is a typical chemical reactor system with complex nonlinear dynamic characteristics. There has been considerable interest in its state estimation and real time control based on mathematical modelling. However, the lack of understanding of the dynamics of the process, the highly sensitive and nonlinear behaviour of the reactor, has made difficult to develop the precise mathematical modelling of the system. An efficient control of the product concentration in CSTR can be achieved only through accurate model. In this paper, attempts are made to alleviate the modelling difficulties using “Artificial Intelligence” (AI) techniques such as neural, fuzzy and neuro-fuzzy. Simulation results demonstrate the effectiveness of Artificial Intelligence modelling techniques. The performance comparison of different modelling techniques has been given in terms of root mean square error. (Received in October 2008, accepted in May 2009. This paper was with the authors 2 months for 1 revision.)