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The Design of the Simple Structure-Specified Controller of Magnetic Bearings for the High-Speed SRM

Magnetic bearing system controllers using H∞ algorithms provide excellent interference rejection capability and robustness. However, in the conventional H∞ control design, the order of the controller is much higher than that of the plant, making implementation in practical engineering applications difficult. To solve the problem, based on the requirements of the theory of mixed sensitivity design method, this paper designs a simple structure-specified controller of magnetic bearings for the highspeed magnetic levitated switched reluctance motor (SRM) using backpropagation neural network function approximation characteristics. The proposed controller is of lower order than the traditional H∞ controller, and meets performance of H∞ controller, which is more suitable for practical implementation. By contrast with the traditional mixed sensitivity controller, results of simulations verify that the controller is reasonable. The controller is applied on the high-speed magnetic levitated SRM platform, and experimental results verify that the controller can achieve control of magnetic bearing systems with good disturbance rejection and robustness.