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Reduced order modeling using genetic-fuzzy algorithm
2009
2009 IEEE International Conference on Systems, Man and Cybernetics
many high-order systems have a large state space. Such systems need to additional computation time for complex calculation to find the output response. Traditionally, Iteration methods have been applied to solve this problem. In this paper advantages of stability equation method derived by Parmer, [1], and the error minimization technique used in genetic-fuzzy algorithm have been combined to propose a new method for order reduction of linear dynamic systems described via statespace models.
doi:10.1109/icsmc.2009.5346072
dblp:conf/smc/AbdulsaddaI09a
fatcat:paf37sebr5gclk64hlb54sh2uq