Comparison of GSA and hybrid PSOGSA tuned controller for a nonlinear SISO system

Priya Chandrasekar and Lakshmi Ponnusamy

International Journal of Enterprise Network Management, 2015, vol. 6, issue 3, 175-184

Abstract: Many new optimisation algorithms have been coming in recent years. In this paper, two such recent population-based optimisation techniques namely gravitational search algorithm (GSA) and hybrid particle swarm optimised gravitational search algorithm (PSOGSA) are discussed and applied to tune the proportional integral (PI) controller parameters of a conical tank system in order to demonstrate its applicability to a nonlinear single input single output system which may be further extended to complex multi input multi output systems. Though the system is simple it has nonlinearity present in it and from control engineering side there is always a need to come up with new control techniques. The performance of the proposed optimisation algorithms are compared with Ziegler Nichols tuned PI controller as it is a classical candidate for comparison in terms of performance index criterion. From the analysis, it is found that the hybrid PSOGSA optimised PI controller gives improved performance comparatively for a conical tank process.

Keywords: nonlinear systems; SISO systems; single input single output; conical tank systems; gravitational search algorithm; GSA; hybrid PSOGSA; PI controller; particle swarm optimisation; PSO; controller tuning. (search for similar items in EconPapers)
Date: 2015
References: Add references at CitEc
Citations:

Downloads: (external link)
http://www.inderscience.com/link.php?id=71132 (text/html)
Access to full text is restricted to subscribers.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ids:ijenma:v:6:y:2015:i:3:p:175-184

Access Statistics for this article

More articles in International Journal of Enterprise Network Management from Inderscience Enterprises Ltd
Bibliographic data for series maintained by Sarah Parker ().