Review of Neural Network Algorithm and its Application in Temperature Control of Distillation Tower
Ningrui Zhao *
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China.
Jinwei Lu
School of Chemical Engineering, East China University of Science and Technology, Shanghai 200237, China.
*Author to whom correspondence should be addressed.
Abstract
Distillation process is a complex process of conduction, mass transfer and heat conduction, which is mainly manifested as follows: The mechanism is complex and changeable with uncertainty; the process is multivariate and strong coupling; the system is nonlinear, hysteresis and time-varying. Therefore, traditional control methods are difficult to accurately control, but neural networks can greatly improve this problem. This article introduces the basic concepts of distillation tower temperature control, comprehensively introduces the application of various neural network algorithms in distillation tower temperature control, and compares their advantages and disadvantages and their effect. At present, there are many researches on neural network control of distillation tower temperature. The methods are different and each has its own merits. This article has carried out a systematic review to provide reference for the development of related industries.
Keywords: Neural networks, control process, distillation tower, temperature parameter