The identification of multivariable radial magnetic bearing system based on RLS-DE algorithm

System model of magnetic bearing is the basis for improving control precision, stability and reliability. To achieve the exact model of multivariable radial magnetic bearing system, a method based on recursive least squares differential evolution (RLS-DE) algorithm is proposed. Based on eliminating the synchronous periodic vibration with rotary speed of rotor, recursive least squares (RLS) meheod is applied into elementarily identifying system model of radial magnetic bearing. Furthermore, initialized population of the differential evolution (DE) algorithm on a small scale of model parameters of elementary identification, and the optimal parameters of system model are achieved by repetitive mutation, crossover and selection of the DE algorithm. Based on identifying of RLS algorithm, the simulation indicates the variance of output error of identification model achieved by searching on a small scale is reduced by 92.86%, and the experiment indicates the variance of output is reduced by 80.13%. Results of simulation and experiment show the validity of proposed algorithm in identifying accurately system model of radial magnetic bearing.