Modelling and control of a continuous distillation tower through fuzzy techniques

Abstract

This paper presents a methodology for the design of a fuzzy controller applicable to continuous processes based on local fuzzy models and velocity linearizations. It has been applied to the implementation of a fuzzy controller for a continuous distillation tower. Continuous distillation towers can be subjected to variations in feed characteristics that cause loss of product quality or excessive energy consumption. Therefore, the use of a fuzzy controller is interesting to control process performance.A dynamic model for continuous distillation was implemented and used to obtain data to develop the fuzzy controller at different operating points. The fuzzy controller was built by integration of linear controllers obtained for each linearization of the system. Simulation of the model with controller was used to validate the controller effectiveness under different scenarios.The results showed that the fuzzy controller was able to keep the target output in the desired range for different inputs disturbances, changing smoothly from a predefined target output to another. The developed techniques are applicable to more complex distillation systems including more operating variables.

Interval type-2 fuzzy logic controller design for distillation column process

“…Canete et al [5] applied a neurofuzzy adaptive control using soft sensors for continuous distillation column. Javadi and Hosseini [6] proposed the PI controller for a binary distillation column. Barceló-Rico et al [7] realized the modeling and the control of a continuous distillation tower through fuzzy technique.…”

Design and Implementation of Optimized Fuzzy Logic Controller for a Nonlinear Dynamic Industrial Plant Using Hysys and Matlab Simulation Packages

“…Two fuzzy logic controllers are developed for control of top and bottom composition of a binary distillation column . Modeling and control of a continuous distillation tower through fuzzy technique is investigated in matlab . For complex and nonlinear chemical processes, a complicated set of mathematical equations that are obtained by applying the laws of mass, energy, and momentum conservation should be solved.…”

Control of Dividing-Wall Columns via Fuzzy Logic

“…Compared to classic control approaches, FLC uses more information from human heuristics and experience and relies less on mathematical models of the physical system, a characteristic particularly suitable for complex, nonlinear systems. FLC has been applied to several processes such as reactors, heat exchangers, conventional distillation, , aircraft flight control, and nuclear reactors . The advantages of FLC over standard PI controllers have also been shown in several applications. ,− The design of a fuzzy controller, however, remains a difficult task due to insufficient analytical design methods in contrast to the well-developed linear control techniques.…”