Control of magnetic levitation positioning stage with an eddy current damper

To enhance the system damping,a permanent magnet set which served as an eddy current damper was added to the magnetic levitation positioning stage which consists of a moving table,four Halbach permanent magnetic arrays,four stators and displacement sensors.The dynamics model of this stage was a complex nonlinear,strong coupling system which made the control strategy to be a focus research.The nonlinear controller of the system was proposed based on the theory of differential geometry.Both simulation and experimental results show that either the decoupling control of the movement can be realized in horizontal and vertical directions,and the control performance was improved by the damper,verifying the validity and efficiency of this method.

Adaptive Kalman filter and dynamic recurrent neural networks-based control design of macro-micro manipulator

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.