Caponio A., Cascella G.L., Neri F., Salvatore N., Sumner M.

This paper appears in: Systems, Man, and Cybernetics, Part B: Cybernetics, IEEE Transactions on
Issue Date: Feb. 2007
Volume: 37 , Issue:1
On page(s): 28 - 41
ISSN: 1083-4419
INSPEC Accession Number: 9299478
Digital Object Identifier: 10.1109/TSMCB.2006.883271
Date of Current Version: 22 January 2007
Sponsored by: IEEE Systems, Man, and Cybernetics Society

ABSTRACT

A fast adaptive memetic algorithm (FAMA) is proposed which is used to design the optimal control system for a permanent-magnet synchronous motor. The FAMA is a memetic algorithm with a dynamic parameter setting and two local searchers adaptively launched, either one by one or simultaneously, according to the necessities of the evolution. The FAMA has been tested for both offline and online optimization. The former is based on a simulation of the whole system-control system and plant-using a model obtained through identification tests. The online optimization is model free because each fitness evaluation consists of an experimental test on the real motor drive. The proposed algorithm has been compared with other optimization approaches, and a matching analysis has been carried out offline and online. Excellent results are obtained in terms of optimality, convergence, and algorithmic efficiency. Moreover, the FAMA has given very robust results in the presence of noise in the experimental system