• Transactions of the Korean Society of Machine Tool Engineers
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• v.17 no.5
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• pp.44-51
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• 2008

In this paper, the optimal tuning of a cross-coupled controller linked with the feedforward controller is studied to reduce contouring and tracking errors of a bi-axial servomechanisms by using the previously developed integrated tuning method. The CCC system for an arbitrary curve, which is combined with the feedforward controller, is formulated by a state-space based on a series of linear motion trajectories. An optimal tuning problem is formulated as a nonlinear constrained optimization problem including relevant controller parameters of the servo. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm that both tracking and contouring errors are significantly reduced by applying the proposed control and tuning system.

• Proceedings of the KSME Conference
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• 2008.11a
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• pp.926-931
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• 2008

In order to design a high-performance controller with excellent positioning and tracking performance, an optimal tuning method based on the integrated design concept is studied. DOBs, feedforward controllers and CCC are applied to control the bi-axial linear servomechanism. To derive accurate dynamic models of mechanical subsystems equipped with linear servos for the integrated tuning, system identification processes are conducted through the sine sweeping. An optimal tuning problem with stability, robustness and overshoot constraints is formulated as a nonlinear constrained optimization problem. Optimal gains are obtained through the SQP method. Experimental results confirm that both tracking and contouring errors are significantly reduced by applying the proposed controller and integrated tuning method.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.5
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• pp.589-597
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• 2011

In this paper, optimal tuning of a cross-coupled controller linked with the feedforward controller and the disturbance observer is studied to improve contouring and tracking accuracy as well as robustness against disturbance. Previously developed integrated design and optimal tuning methods are applied for developing the robust tuning method. Strict mathematical modeling of the multivariable system is formulated as a state-space equation. Identification processes of the servomechanism are conducted for mechanical servo models. An optimal tuning problem to minimize both the contour error and settling time is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servo control system. Constraints such as relative stability, robust stability and overshoot, etc. are considered for the optimization. To verify the effectiveness of the proposed optimal tuning procedure, linear and circular motion experiments are performed on the xy-table. Experimental results confirm the control performance and robustness despite the variation of parameters of the mechanical subsystems.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.62.1-62
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• 2001

This paper suggests an inverse optimal PID control design method for the trajectory tracking case of mechanical systems. Also, simple coarse/fine performance tuning laws are suggested based on the analysis for performance limitation of inverse optimal PID controller. Experimental results for a robot manipulator show the validity of our analysis for the performance tuning methods.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.30 no.10 s.253
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• pp.1209-1218
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• 2006

Precision servomechanisms are widely used in machine tool, semiconductor and flat panel display industries. It is important to improve contouring accuracy in high-precision servomechanisms. In order to improve the contouring accuracy, cross-coupled control systems have been proposed. However, it is very difficult to select the controller parameters because cross-coupled control systems are multivariable, nonlinear and time-varying systems. In this paper, in order to improve contouring accuracy of a biaxial servomechanism, a cross-coupled controller is adopted and an optimal tuning procedure based on an integrated design concept is proposed. Strict mathematical modeling and identification process of a servomechanism are performed. An optimal tuning problem is formulated as a nonlinear constrained optimization problem including the relevant controller parameters of the servomechanism. The objective of the optimal tuning procedure is to minimize both the contour error and the settling time while satisfying constraints such as the relative stability and maximum overshoot conditions, etc. The effectiveness of the proposed optimal tuning procedure is verified through experiments.

• Journal of the Korean Data and Information Science Society
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• v.26 no.3
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• pp.549-559
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• 2015

The MDPDE is an attractive alternative to maximum likelihood estimator because of the strong robustness properties that it inherently possess. The characteristics of MDPDE can be varied with the tuning parameter, in general, there is a trade-off between robustness and asymptotic efficiency. Hence, selection of optimal tuning parameter is important but complicated task. In this study, we introduce two optimal tuning parameter selection methods proposed by Fujisawa and Eguchi (2005) and Warwick (2006). Through simulation study, we found out that Warwick's method yields excessively small optimal tuning parameter in certain cases while Fujisawa and Eguchi's method performs well. Therefore, we think Fujisawa and Eguchi's method can be used commonly for finding optimal tuning parameter of MDPDE.

• 제어로봇시스템학회:학술대회논문집
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• 2002.10a
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• pp.102.5-102
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• 2002

In this paper auto-tuning scheme of PID controller based on the reference model has been studied by immune algorithm for a process. Up to this time, many sophisticated tuning algorithms have been tried in order to improve the PID controller performance under such difficult conditions. However, in the actual plant, they are manually tuned through a trial and error procedure, and the derivative action is switched off. Therefore, it is difficult to tune. Simulation results by immune based tuning reveal that tuning approaches suggested in this paper is an effective approach to search for optimal or near optimal process control.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2003.06a
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• pp.117-120
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• 2003

A method for PID controller tuning based on process models for unstable processes was introduced. The optimal. proportional and derivative gains of the AMBs were determined by the tuning method and utilized for the chatter stability analysis in order to search for the chatter-free cutting region. The stability analysis results showed that the optimal gains give wider chatter-free cutting region, and as a result the proposed tuning method was confirmed to be an effective tuning method for determining the optimal gains of the AMBs.

• Proceedings of the KIEE Conference
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• 2004.11c
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• pp.62-65
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• 2004

An optimal robust controller design method for gun driving system is discussed in this paper. The parameters of the gun driving controller are tuned by using the LQR characteristics for the performance and robustness. Tuning method that optimize velocity error gives a significant improvement over the existing PID tuning methods. It is shown that the tuning result of real gun driving system which is regarded as rigidness model or stiffness model satisfy performance and robustness.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10b
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• pp.192-194
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• 1996

This paper propose an optimal scaling gain tuning method of the fuzzy PI controller using Genetic Algorithm(GA). Scaling gains can reflect the control resolution and fuzziness of input/output variables. By the scaling gain method, the design of a fuzzy logic controller(FLC) can be simplified without affecting the system performance in comparison with multi-decision table method. In designing a fuzzy logic controller, the analytic approach method for the optimization is unavailable. Therefore GA is excellent optimization algorithms for scaling gain tuning. Using this optimal scaling gain tuning method, a good performance can be achieved both in transient and steady state.