• Journal of Institute of Control, Robotics and Systems
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• v.9 no.1
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• pp.82-89
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• 2003

A robust motion control method is proposed fur the point-to-point position control of a XY positioning system which consists of a base cart, elastic ben and moving mass. The horizontal motion controller consists of the feedforward controller to suppress the single mode vibration of the elastic beam and the feedback controller to get the high-accuracy positioning performance of the base cart. Input preshaping vibration suppression method based on system modeling with analytic frequency equation is proposed and integrated into the robust internal-loop compensator(RIC) to increase the robustness of the whole closed-loop system The vertical motion controller is proposed based on the dual RIC structure. Through experiments, it is shown that the proposed method can stabilize the system and suppress the vibration in the presence of uncertainties and disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.581-586
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• 2003

This paper presents control designs using neural networks (NN) for a XY positioning table. The proposed neurocontroller is composed of an outer PD tracking loop for stabilization of the fast flexible-mode dynamics and an NN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NN weights, so that the NN compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded weight estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The proposed neuro-controller is implemented and tested on an IBM PC-based XY positioning table, and is applicable to many precision XY tables. The algorithm, simulation, and experimental results are described. The experimental results are shown to be superior to those of conventional control.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.3
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• pp.375-382
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• 2004

This paper presents control designs using neural networks (NN) for a XY positioning table. The proposed neuro-controller is composed of an outer PD tracking loop for stabilization of the fast flexible-mode dynamics and an NN inner loop used to compensate for the system nonlinearities. A tuning algorithm is given for the NN weights, so that the NN compensation scheme becomes adaptive, guaranteeing small tracking errors and bounded weight estimates. Formal nonlinear stability proofs are given to show that the tracking error is small. The proposed neuro-controller is implemented and tested on an IBM PC-based XY positioning table, and is applicable to many precision XY tables. The algorithm, simulation, and experimental results are described. The experimental results are shown to be superior to those of conventional control.