The University of Southampton
University of Southampton Institutional Repository

The online optimisation of stator vane settings in multi-stage axial compressors

Roh, H. and Daley, Stephen (2009) The online optimisation of stator vane settings in multi-stage axial compressors International Journal of Advanced Mechatronic Systems, 1, (4), p. 266. (doi:10.1504/IJAMECHS.2009.026332).

Record type: Article


Axial compressors for high efficiency industrial gas turbines are required to operate over a wide range of mass flow rates and rotational speeds. However, the useful range of operation of the axial-flow compressor is limited by the onset of two instabilities known as surge and rotating stall. To resolve these problems, variable stator blades or VGV's are considered by optimising the blade setting in order to avoid the stall and subsequent surge. A steady state model of a 15 stage multi-stage axial compressor is utilised here to investigate the performance, particularly for obtaining acceptable optimisation convergence time for practical purposes. For the effective search for an optimum setting, the variation in VGV's with respect to a different combination of objective functions is considered. In this paper, self-tuning extremum control and a particle swarm optimisation method are proposed and implemented to obtain the best value for a normalised objective function. The results demonstrate the relative effectiveness of the two algorithms and the suitability for their use in this proposed application. The study clearly demonstrates that the PSO provides the best performance in seeking the optimum of the chosen objective functions.

Full text not available from this repository.

More information

Published date: 2009
Organisations: Signal Processing & Control Grp


Local EPrints ID: 334368
ISSN: 1756-8412
PURE UUID: 8fac931c-12df-48ab-8472-bf78de3c9071

Catalogue record

Date deposited: 07 Mar 2012 14:53
Last modified: 18 Jul 2017 06:12

Export record



Author: H. Roh
Author: Stephen Daley

University divisions

Download statistics

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics

Atom RSS 1.0 RSS 2.0

Contact ePrints Soton:

ePrints Soton supports OAI 2.0 with a base URL of

This repository has been built using EPrints software, developed at the University of Southampton, but available to everyone to use.

We use cookies to ensure that we give you the best experience on our website. If you continue without changing your settings, we will assume that you are happy to receive cookies on the University of Southampton website.