Evolutionary Optimization of Feedback Controllers for
                 Thermoacoustic Instabilities

  Hansen, N., A.S.P. Niederberger, L. Guzzella, P. Koumoutsakos

 We present the system identifcation and the online optimization of
 feedback controllers applied to combustion systems using evolutionary
 algorithms.  The algorithm is applied to gas turbine combustors that
 are susceptible to thermoacoustic instabilities resulting in
 imperfect combustion and decreased lifetime.  In order to mitigate
 these pressure oscillations, feedback controllers sense the pressure
 and command secondary fuel injectors. The controllers are optimized
 online with an extension of the CMA evolution strategy capable of
 handling noise associated with the uncertainties in the pressure
 measurements. The presented method is independent of the specifc
 noise distribution and prevents premature convergence of the
 evolution strategy. The proposed algorithm needs only two additional
 function evaluations per generation and is therefore particularly
 suitable for online optimization. The algorithm is experimentally
 verifed on a gas turbine combustor test rig. The results show that
 the algorithm can improve the performance of controllers online and
 is able to cope with a variety of time dependent operating
 conditions.

In: 
  Morrison, Jonathan F.; Birch, D. M.; Lavoie, P. (Eds.) 2008.  
  IUTAM Bookseries , Vol. 7
  IUTAM Symposium on Flow Control and MEMS
  Proceedings of the IUTAM Symposium held at the Royal Geographical Society, 
  19-22 September 06, hosted by Imperial College, London, England
  ISBN: 978-1-4020-6857-7