Research Article Brain Emotional Learning Based Intelligent Decoupler for Nonlinear Multi-Input Multi-Output Distillation Columns M. H. El-Saify, 1 A. M. El-Garhy, 1 and G. A. El-Sheikh 2 1 Electronics, Communications, and Computers Department, Faculty of Engineering, Helwan University, Cairo, Egypt 2 Electronics and Communications Department, Pyramids High Institute (PHI) for Engineering and Technology, 6th of October, Giza, Egypt Correspondence should be addressed to M. H. El-Saify; mhelsaify@hotmail.com Received 27 August 2016; Revised 24 December 2016; Accepted 9 January 2017; Published 31 January 2017 Academic Editor: Asier Ibeas Copyright © 2017 M. H. El-Saify et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Te distillation process is vital in many felds of chemical industries, such as the two-coupled distillation columns that are usually highly nonlinear Multi-Input Multi-Output (MIMO) coupled processes. Te control of MIMO process is usually implemented via a decentralized approach using a set of Single-Input Single-Output (SISO) loop controllers. Decoupling the MIMO process into group of single loops requires proper input-output pairing and development of decoupling compensator unit. Tis paper proposes a novel intelligent decoupling approach for MIMO processes based on new MIMO brain emotional learning architecture. A MIMO architecture of Brain Emotional Learning Based Intelligent Controller (BELBIC) is developed and applied as a decoupler for 4 input/4 output highly nonlinear coupled distillation columns process. Moreover, the performance of the proposed Brain Emotional Learning Based Intelligent Decoupler (BELBID) is enhanced using Particle Swarm Optimization (PSO) technique. Te performance is compared with the PSO optimized steady state decoupling compensation matrix. Mathematical models of the distillation columns and the decouplers are built and tested in simulation environment by applying the same inputs. Te results prove remarkable success of the BELBID in minimizing the loops interactions without degrading the output that every input has been paired with. 1. Introduction In chemical industries, distillation is one of the most impor- tant processes. Te objective of distillation is to separate a mixture of chemical components. Te purpose of control is to maintain bottom and top product (distillate) purity despite variations in feed fow and feed concentration. As the distillation columns process is a MIMO system, many researches utilize decentralized approaches to control it [1]. Te two-coupled distillation columns is a 4 input/4 output process. Normally, control engineers decouple the process into four independent loops via a decoupler [2]. Ten, every loop is controlled separately by SISO controller [3]. Tis work is aimed at proposing MIMO decoupling unit based on brain emotional learning technique and applying it to the two- coupled distillation columns. Te design of intelligent systems is one of the most growing felds that have received considerable attentions in recent years. Biologically motivated intelligent control is the discipline in which control algorithms are developed by emulating certain characteristics of intelligent biolog- ical systems. Many control techniques, such as artifcial neural networks [4, 5], fuzzy control [6, 7], and genetic algorithms [8, 9], had proven its efectiveness in solving wide range of complex control problems. Recently, a new member was added to this family of biologically motivated intelligent control, which mimics the emotional learning process in the limbic system of the mammalian brains. Te model of brain emotional learning algorithm had been proposed in [10, 11] and then was developed and shared for control engineering applications [12]. Since then, BELBIC is increasingly being utilized in many control engineering applications such as electric motors [13, 14], servo systems [15, 16], motion control [17, 18], and power systems [19, 20]. Some recent researches utilize other intelligent techniques in cooperation with BELBIC to control the system such as fuzzy logic [21, 22]. Tese applications had utilized BELBIC as a SISO system. In [3], the two-coupled distillation columns is Hindawi Mathematical Problems in Engineering Volume 2017, Article ID 8760351, 13 pages https://doi.org/10.1155/2017/8760351