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Hybrid control based on inverse Prandtl-Ishlinskii model for magnetic shape memory alloy actuator

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【作者】 周淼磊高巍田彦涛

【Author】 ZHOU Miao-lei, GAO Wei, TIAN Yan-tao Department of Control Science and Engineering, Jilin University, Changchun 130022, China

【机构】 Department of Control Science and Engineering,Jilin University

【摘要】 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%.

【Abstract】 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(51105170) supported by the National Natural Science Foundation of China;Project supported by the Scientific Research Foundation for the Returned Overseas Chinese Scholars,Ministry of Education,China
  • 【文献出处】 Journal of Central South University ,中南大学学报(英文版) , 编辑部邮箱 ,2013年05期
  • 【分类号】TP273
  • 【被引频次】15
  • 【下载频次】151
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