A New Hybrid BFOA-PSO Optimization Technique for Decoupling and Robust Control of Two-Coupled Distillation Column ProcessReport as inadecuate




A New Hybrid BFOA-PSO Optimization Technique for Decoupling and Robust Control of Two-Coupled Distillation Column Process - Download this document for free, or read online. Document in PDF available to download.

Computational Intelligence and Neuroscience - Volume 2016 2016, Article ID 8985425, 17 pages -

Research Article

Department of Electronics, Communications and Computers, Faculty of Engineering, Helwan University, 1 Sherif Street, Helwan, Cairo 11792, Egypt

Department of Electrical Engineering, Faculty of Engineering, Cairo University, University Street, Giza 12316, Egypt

Received 22 April 2016; Revised 31 July 2016; Accepted 9 August 2016

Academic Editor: J. Alfredo Hernández-Pérez

Copyright © 2016 Noha Abdelkarim et al. This 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.

Abstract

The two-coupled distillation column process is a physically complicated system in many aspects. Specifically, the nested interrelationship between system inputs and outputs constitutes one of the significant challenges in system control design. Mostly, such a process is to be decoupled into several input-output pairings loops, so that a single controller can be assigned for each loop. In the frame of this research, the Brain Emotional Learning Based Intelligent Controller BELBIC forms the control structure for each decoupled loop. The paper’s main objective is to develop a parameterization technique for decoupling and control schemes, which ensures robust control behavior. In this regard, the novel optimization technique Bacterial Swarm Optimization BSO is utilized for the minimization of summation of the integral time-weighted squared errors ITSEs for all control loops. This optimization technique constitutes a hybrid between two techniques, which are the Particle Swarm and Bacterial Foraging algorithms. According to the simulation results, this hybridized technique ensures low mathematical burdens and high decoupling and control accuracy. Moreover, the behavior analysis of the proposed BELBIC shows a remarkable improvement in the time domain behavior and robustness over the conventional PID controller.





Author: Noha Abdelkarim, Amr E. Mohamed, Ahmed M. El-Garhy, and Hassen T. Dorrah

Source: https://www.hindawi.com/



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