Improved ANFIS combined with PID for extractive distillation process control of benzene–isopropanol–water mixtures

Abstract

Real-time measurement and control of product composition in extractive distillation continues to remain a challenge; however, composition control has demonstrated the ability to stabilise control systems. In this study, a dynamic control scheme is proposed that uses an improved PID-fused adaptive neuro-fuzzy inference system (ANFIS); herein, ANFIS replaces composition controllers, improving the real-time performance of the control system. The ANFIS algorithm, however, suffers from problems such as easily falling into a local optimum solution. Therefore, the genetic algorithm (GA) and particle swarm optimisation (PSO) algorithm are separately used to optimise the network parameters of ANFIS, and the impact of different number of clusters (NC) on the performance of the control scheme is evaluated. The control scheme of PSO-optimised PID-ANFIS exhibits superior dynamic performance compared to other control schemes; moreover, it does not require the use of component controllers and has a faster response time and smaller transient values.