Pareto-Optimality and V.E.G.A. to Multi- Input Multi-Output (M.I.M.O.) System Reduction

Authors : SK Mittal, D Chandra, B Dwived

Pages : 44-54

View : 12 | Download : 7

Publication Date : 2010-06-01

Article Type : Research Paper

Abstract :A VEGA insert ignore into journalissuearticles values(Vector Evaluated Genetic Algorithm); based computer-aided method to derive a reduced order insert ignore into journalissuearticles values(rth-order); approximant for given insert ignore into journalissuearticles values(stable); multi-input multi-output insert ignore into journalissuearticles values(MIMO); linear continuous-time system is presented. In this method, stability and the first r time moments/Markov parameters are preserved as well as the errors between a set of subsequent time moments/Markov parameters of the system and those of the model are minimized. The method is useful as it guarantees improvement as well as alleviates the problems of deciding the values of number of error functions to be minimized and values of weights on the errors which were left unresolved in previous methods. The search area for GA is very wide and it usually converges to a point near global optima
Keywords : Model reduction, Padé approximants, Routh criteria, G A