• Journal of the Korean Society for Precision Engineering
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• v.16 no.12
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• pp.14-23
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• 1999

This paper proposes a method to generate the velocity trajectory which guarantees user specified contour errors at corners for high speed and high precision motion control of CNC machines. The relation among the desired trajectory, system bandwidth and corner contour error are derived. Experiments show that the corner contour error specified by users can be guaranteed with the proposed velocity trajectory.

• Transactions on Control, Automation and Systems Engineering
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• v.3 no.4
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• pp.272-282
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• 2001

Uncertainties are the main reasons of deterioration of contour control of industrial articulated robot arm. In this paper, a high-precision contour control method was proposed to overcome some main uncertainties, such as torque saturation, system delay dynamics, interference between robot links, friction, and so on. Firstly, each considered factor of uncertainties was introduced briefly. Then proper realizable objective trajectory generation was presented to avoid torque saturation from objective trajectory. According to the model of industrial articulated robot arm, construction of Gaussian neural network controller with considering system delay dynamic, interference between robot links and friction was explained in detail. Finally, through the experiment and simulation, the effectiveness of proposed method was verified. Furthermore, based on the results it was shown that the Gaussian neural network controller can be also adapted for the various kinds of friction and high-speed motion of industrial articulated robot arm.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.4
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• pp.64-71
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• 2004

The growing need for higher precision and productivity in manufacturing industry has lead to an increased interest in computer numerical control (CNC) systems. It is well known fact that the cross-coupling controller (CCC) is an effective method for contouring applications. In this paper, a multi-axis contour error controller (CEC) based on a contour error vector using parametric curve interpolator is introduced. The contour error vector is a vector from the actual tool position to the nearest point on the desired path. The contour error vector is the closest error model to the contour error. The simulation results show that the CEC is more accurate than the conventional CCC for a biaxial motion system. In addition, the experimental results on 3-axis motion system show that the CEC is simply applied to 3-axis motions and contouring accuracy is significantly improved.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.341-344
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• 1997

The higher precision in manufacturing field is demanded, the more accurate servo controller is needed. To achieve the high precision, Koren proposed the cross-coupled control (CCC) method. The objective of the CCC is reducing the contour error rather than decreasing the individual axial error. The performance of CCC depends on the contour error model. In this paper we propose a new contour error model which utilizes contour error vector based on parametric curve interpolator. The experimental results show that the new CCC is more accurate than the variable-gain CCC during free-form curve motion.

• Journal of the Korean Society for Precision Engineering
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• v.17 no.11
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• pp.108-114
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• 2000

In this paper, a new adaptive cross-coupling control(CCC) method with an improved contour error model is proposed to maintain contouring precision in high-speed nonlinear contour machining. The proposed method utilizes variable controller gains based on the instantaneous curvature of a contour and the feedrate command. The proposed method is evaluated and compared with the conventional CCC for nonlinear contouring motion through computer simulations. The simulation results show that the proposed CCC improves the contouring accuracy more effectively than the existing method.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.26 no.8
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• pp.1480-1486
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• 2002

In this study, the cross-coupling control (CCC) with three new features is proposed to maintain contour precision in high-speed nonlinear contour machining. One is an improved contour error model that provides almost exact calculation of the errors. Another is the utilization of variable controller gains based on the instantaneous curvature of the contour and the variable command. For this scheme, a stability is analyzed. As a result, the stability region is obtained, and the variable gains are decided within that region. The other scheme in the proposed CCC is a real-time feedrate adaptation module to regulate cutting force fur better surface finish through regulation of material removal rate (MRR). The simulation results show that the proposed CCC system can provide better precision than the existing method particularly in high-speed machining of nonlinear contours.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.28 no.1
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• pp.40-47
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• 2004

This paper proposes a three-axis coupling controller designed to improve the contouring accuracy in machining of 3D nonlinear contours. The proposed coupling controller is based on an innovative 3D contour error model and a PID control law. The novel contour error model provides almost exact calculation of contour errors in real-time for arbitrary contours and can be integrated with any type of existing interpolator. In the proposed method, three axes of motion are coordinated by the proposed coupling controller along with a proportional controller for each axis. The proposed contour error model and coupling controller are evaluated through computer simulations. The simulation results show that the proposed 3-axis coupling controller with the new contour error model substantially can improve the contouring accuracy by order of magnitude compared with the existing uncoupled controllers in high-speed machining of nonlinear contours.

• Proceedings of the KSME Conference
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• 2000.04a
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• pp.446-451
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• 2000

In this paper, a new adaptive cross-coupling control (CCC) algorithm with an improved contour error model is proposed to maintain contouring precision in high-speed nonlinear contour machining. The proposed method utilizes variable controller gains based on the instantaneous curvature of a contour and the feedrate command. The proposed method is evaluated and compared with the conventional CCC for nonlinear contouring motion through computer simulations. The simulation results show that the proposed CCC improves the contouring accuracy more effectively than the existing method.

• Proceedings of the Korean Society of Machine Tool Engineers Conference
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• 2000.10a
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• pp.8-13
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• 2000

In this paper, a new adaptive cross-coupling control (CCC) method with an improved contour error model is proposed to maintain contouring precision in high-speed nonlinear contour machining. The proposed method utilizes variable controller gains based on the instantaneous curvature of a contour and the feedrate command. In addition, a real-time federate adaptation scheme is included in the proposed CCC to regulate cutting force. The proposed method is evaluated and compared with the conventional CCC for nonlinear contouring motion through computer simulations. The simulation results show that the proposed CCC improves the contouring accuracy and regulates cutting force more effectively than the existing method.

• Journal of the Korean Institute of Intelligent Systems
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• v.7 no.5
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• pp.1-7
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• 1997

In this paper, a neuro-contouring control scheme for the high precision machining of CNC machine tools is descrihed. The proposed control system consists of a conventional controller for each axis and an additional neuro-controller. For contouring control, the contour error must be computed during realtime motion, but generally the contour error for nonlinear contours is difficult to he directly computed. We, therefore, propose a new contour error model to approximate real error more exactly, and here we also introduce a cost function for better contouring performance and derive a learning law to adjust the weights of the neuro-controller. The derived learning law guarantees good contouring performance. Usefulness of the proposed control scheme is demonstrated hy computer simulations.