The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memor...The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.展开更多
Mathematical models are disappointing due to uneven distribution of the air gap magnetic field and significant un- modeled dynamics in magnetic bearing systems. The effectiveness of control deteriorates based on an in...Mathematical models are disappointing due to uneven distribution of the air gap magnetic field and significant un- modeled dynamics in magnetic bearing systems. The effectiveness of control deteriorates based on an inaccurate mathematical model, creating slow response speed and high jitter. To solve these problems, a model-free adaptive control （MFAC） scheme is proposed for a three-degree-of-freedom hybrid magnetic bearing （3-DoF HMB） control system. The scheme for 3-DoF HMB depends only on the control current and the objective balanced position, and it does not involve any model information. The design process of a parameter estimation algorithm is model-free, based directly on pseudo-partial-derivative （PPD） derived online from the input and output data information. The rotor start-of-suspension position of the HMB is regulated by auxiliary bearings with different inner diameters, and two kinds of operation situations （linear and nonlinear areas） are present to analyze the validity of MFAC in detail. Both simulations and experiments demonstrate that the proposed MFAC scheme handles the 3-DoF HMB control system with start-of-suspension response speed, smaller steady state error, and higher stability.展开更多
基金Project(51105170) supported by the National Natural Science Foundation of ChinaProject supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
文摘The hysteresis characteristic is the major deficiency in the positioning control of magnetic shape memory alloy actuator. A Prandtl-Ishlinskii model was developed to characterize the hysteresis of magnetic shape memory alloy actuator. Based on the proposed Prandtl-Ishlinskii model, the inverse Prandtl-Ishlinskii model was established as a feedforward controller to compensate the hysteresis of the magnetic shape memory alloy actuator. For further improving of the positioning precision of the magnetic shape memory alloy actuator, a hybrid control method with hysteresis nonlinear model in feedforward loop was proposed. The control method is separated into two parts: a feedforward loop with inverse Prandtl-Ishlinskii model and a feedback loop with neural network controller. To validate the validity of the proposed control method, a series of simulations and experiments were researched. The simulation and experimental results demonstrate that the maximum error rate of open loop controller based on inverse PI model is 1.72%, the maximum error rate of the hybrid controller based on inverse PI model is 1.37%.
基金Project supported by the National Natural Science Foundation of China （Nos. 51707082 and 51607080）, the Natural Science Foundation of Jiangsu Province, China （Nos. BK20170546 and BK20150510）, the China Postdoctoral Science Foundation （No. 2017M620192）, and the Priority Academic Program Development of Jiangsu Higher Education Institutions
文摘Mathematical models are disappointing due to uneven distribution of the air gap magnetic field and significant un- modeled dynamics in magnetic bearing systems. The effectiveness of control deteriorates based on an inaccurate mathematical model, creating slow response speed and high jitter. To solve these problems, a model-free adaptive control （MFAC） scheme is proposed for a three-degree-of-freedom hybrid magnetic bearing （3-DoF HMB） control system. The scheme for 3-DoF HMB depends only on the control current and the objective balanced position, and it does not involve any model information. The design process of a parameter estimation algorithm is model-free, based directly on pseudo-partial-derivative （PPD） derived online from the input and output data information. The rotor start-of-suspension position of the HMB is regulated by auxiliary bearings with different inner diameters, and two kinds of operation situations （linear and nonlinear areas） are present to analyze the validity of MFAC in detail. Both simulations and experiments demonstrate that the proposed MFAC scheme handles the 3-DoF HMB control system with start-of-suspension response speed, smaller steady state error, and higher stability.
