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Model Reference Adaptive Control of HMB Based on PSO-LS-SVM Inverse

To realize the hybrid magnetic bearing (HMB) nonlinear decoupling control with high precision, a strategy of model reference adaptive control (MRAC) based on the least square support vector machine (LS-SVM) inverse is proposed. After analyzing the reversibility of HMB, the LS-SVM regression theory is used to identify the inverse model, the parameters of LS-SVM are optimized by Particle Swarm Optimization (PSO) algorithm. Then the nonlinear system is transformed into a pseudo-linear system by connecting the optimized the inverse model and the original unit. MRAC is designed to realize the compound linear control for HMB. Simulation results confirm that the identified inverse model has high precision and the compound control strategy has good performance.