摘要
Particleswarmoptimizer(PSO),anewevolutionarycomputationalgorithm,exhibitsgoodperformanceforoptimizationproblems,althoughPSOcannotguaranteeconvergenceofaglobalminimum,evenalocalminimum.However,therearesomeadjustableparametersandrestrictiveconditionswhichcanaffectperformanceofthealgorithm.Inthispaper,thealgorithmareanalyzedasatime-varyingdynamicsystem,andthesufficientconditionsforasymptoticstabilityofaccelerationfactors,incrementofaccelerationfactorsandinertiaweightarededuced.Thevalueoftheinertiaweightisenhancedto(fi1,1).Basedonthededucedprincipleofaccelerationfactors,anewadaptivePSOalgorithm-harmoniousPSO(HPSO)isproposed.FurthermoreitisprovedthatHPSOisaglobalsearchalgorithm.Intheexperiments,HPSOareusedtothemodelidentificationofalinearmotordrivingservosystem.AnAkaikeinformationcriteriabasedfitnessfunctionisdesignedandthealgorithmscannotonlyestimatetheparameters,butalsodeterminetheorderofthemodelsimultaneously.TheresultsdemonstratetheeffectivenessofHPSO.
出版日期
2007年03月13日(中国期刊网平台首次上网日期,不代表论文的发表时间)