• Proceedings of the Korean Society of Precision Engineering Conference
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• 2010.05a
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• pp.639-640
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• 2010

• Journal of the Korean Society for Precision Engineering
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• v.22 no.12 s.177
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• pp.51-60
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• 2005

This paper describes a robust control scheme for high-speed and long stroke scanning motion of high precision linear motor system consisting of linear motor, air bearing guide and position measurement system using heterodyne interferometer. Nowadays, semiconductor process and inspection of wafer or LCD need high speed and long travel length for their high throughput and extremely small velocity fluctuations or tracking errors. In order to satisfy these conditions, linear motor system are widely used because they have large thrust force and do not need motion conversion mechanisms such as ball screw, rack & pinion or capstan with which the system are burdened. However linear motors have a problem called force ripple. Force ripple deteriorates the tracking performances and makes periodic position errors. So, force ripple must be compensated. To maximize the tracking performance of linear motor system, we propose the control scheme which is composed of a robust control method, Time Delay Controller (TDC) and a feedforward control method, Zero Phase Error Tracking Control (ZPETC) for accurate tracking a given trajectory and an adaptive force ripple compensation (AFC) algorithm fur estimating and compensating force ripple. The adaptive ripple compensation is continuously refined on the basis of tracking error. Computer simulation results based on modeled parameters verify the effectiveness of the proposed control scheme for high-speed, long stroke and high precision scanning motion and show that the proposed control scheme can achieve a sup error tracking performance in comparison to conventional TDC control.

• Journal of Aerospace System Engineering
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• v.13 no.3
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• pp.1-8
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• 2019

The electromagnetic forces generate a torque on the gimbal motor, and changes in the coil current causes torque ripple. This affects the gimbals' speed and results to unstable satellite attitude. It is therefore essential to reduce the torque ripple of the gimble motor with the aim of improving the attitude control accuracy of the satellite. This paper theoretically analyzes the torque generated from the modeling of a motor for general concentrated winding and distributed winding. The prototype was designed and fabricated through selection of the winding that reduces the torque ripple through simulation results. The results of the magnetic fields' theoretical analysis and the back electromotive force of the prototype were compared with the calibrated results for verification of conformity and manufacture of the design. The low-speed test proved that the torque ripple is reduced by improving the speed stability.

• Journal of the Semiconductor & Display Technology
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• v.7 no.1
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• pp.17-22
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• 2008

The proposed hybrid controller consists of PID controller, feedforward controller and RLSE (Recursive Least Square Estimating) adaptive controller to compensate the force ripple that is periodic function of position in a linear motor. The modeling of force ripple is divided into the current-dependent and current-independent components. The current independent components never change as the current into the linear motor changes. On the other hand, the current-dependent components change as current varies when the velocity and load of the linear motor change. The proposed controller can compensate both force ripples. The feedforward controller compensates the current-independent components and the RLSE adaptive controller compensates the current-dependents components. We verified the performance of the controller by simulation and experiments.

• 제어로봇시스템학회:학술대회논문집
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• 2000.10a
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• pp.362-362
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• 2000

The purpose of this thesis is to reduce force ripple of linear pulse motor(LPM) using neural network and to enhance precision. In order to this, we propose a new controller using a neural network to compensate disturbances. The structure includes adaptation block which learns the dynamics of the periodic disturbance and forces the interferences, caused by disturbances. The proposed controller compensates an unmodeled dynamics in the LPM. The neural network changes a current command to reduce position error and force ripple of the LPM. We compare proposed controller with PI controller. Simulation result shows that the proposed controller has better performance than a PI controller without neural network.