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Adaptive Kalman filter and dynamic recurrent neural networks-based control design of macro-micro manipulator 被引量:1
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作者 Lijun ZHANG Lixin YANG +1 位作者 Lining SUN Xingwen ZHANG 《控制理论与应用(英文版)》 EI 2012年第4期504-510,共7页
In this paper, a composite control scheme for macro-micro dual-drive positioning stage with high accel- eration and high precision is proposed. The objective of control is to improve the precision by reducing the infl... In this paper, a composite control scheme for macro-micro dual-drive positioning stage with high accel- eration and high precision is proposed. The objective of control is to improve the precision by reducing the influence of system vibration and external noise. The positioning stage is composed of voice coil motor (VCM) as macro driver and piezoelectric actuator (PEA) as micro driver. The precision of the macro drive positioning stage is improved by the com- bined PID control with adaptive Kalman filter (AKF). AKF is used to compensate VCM vibration (as the virtual noise) and the external noise. The control scheme of the micro drive positioning stage is presented as the integrated one with PID and intelligent adaptive inverse control approach to compensate the positioning error caused by macro drive positioning stage. A dynamic recurrent neural networks (DRNN) based inverse control approach is proposed to offset the hysteresis nonlinearity of PEA. Simulations show the positioning precision of macro-micro dual-drive stage is clearly improved via the proposed control scheme. 展开更多
关键词 Macro-micro dual-drive positioning stage Piezoelectric actuator Adaptive Kalman filter Dynamic re-current neural networks
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