Energy-Saving Dynamic Bias Current Control of Active Magnetic Bearing Positioning System Using Adaptive Differential Evolution

2019 ◽  
Vol 49 (5) ◽  
pp. 942-953 ◽  
Author(s):  
Syuan-Yi Chen ◽  
Min-Han Song
Author(s):  
Satoshi Ueno ◽  
M. Necip Sahinkaya

This paper introduces an adaptive bias current control method for an active magnetic bearing (AMB). The bearing force is analyzed theoretically, and the dynamic performance of the magnetic bearing for various bias currents is discussed. Then power consumption is analyzed and the optimum bias current that minimizes power consumption is derived. A novel optimization method using a steepest descent method is proposed. This requires less computing power than the former optimization method using a recursive Fourier transform algorithm. Experimental results show that the optimized bias current can be achieved by the proposed method. However, the dynamics of the rotor is affected by the bias current variation. In order to overcome this problem, the effects of parameter errors are investigated and correction methods are introduced. Experimental results show that the rotor dynamics are not affected by the variable bias current if the parameters are corrected. Results are also presented for machine run-up and run-down.


Author(s):  
Hai Rong ◽  
Kai Zhou

The zero-bias current controlled way is proposed to cut down the power consumption of the active magnetic bearing in a power magnetically levitated spindle system. The zero-bias current controlled way is easier to realize than the zero-bias flux controlled way, since current can be detected directly, while flux is hard to be measured in practice. Besides, the active magnetic bearing suffers from lumped uncertainty including parameter uncertainty and external load, and the displacement of rotor caused by lumped uncertainty is undesirable. In practice, the upper bound of the lumped uncertainty especially the external load is hard to obtain, making it hard to choose parameters for a traditional sliding mode control. The adaptive backstepping sliding mode control method combining both the advantages of sliding mode procedure and backstepping procedure is proposed to solve this problem. Furthermore, the upper bound of lumped uncertainty is estimated in real time by an adaptive law. In this paper, first a new zero-bias current active magnetic bearing system model with lumped uncertainty is built; then two controllers based on the sliding mode control and adaptive backstepping sliding mode control methods are designed, respectively, and the stability analyses are given for the two controllers via Lyapunov function; finally, the effectiveness of the proposed adaptive backstepping sliding mode control approach for a zero-bias current active magnetic bearing system is verified by the simulation and experiment results.


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