• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.3
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• pp.611-614
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• 2007

In this paper, a Direct Learning Control (DLC) method is presented to generate a virtual reference input for linear feedback systems to improve the output tracking performance. The original reference input is effectively modified by the DLC without any iterative learning process. The presented DLC is designed based on the information on the relative degree of a system and previously generated virtual reference inputs. It is illustrated by simulations that the virtual reference input generated by the proposed DLC can achieve high tracking performance, although the reference input cannot be appropriately shaped by using existing DLC methods.

• Journal of Power System Engineering
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• v.19 no.4
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• pp.24-29
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• 2015

This paper designs a looper-tension controller for strip top-tail parts in hot strip finishing mills. A three-degree linear model of the looper-tension system is derived by a Taylor's linearization method, where the actuator's dynamics are ignored because of their fast responses. A feedforward shaping controller for the strip top part and a feedforward model reference controller for the strip tail part are respectively designed, they are combined with an ILQ(Inverse Linear Quadratic optimal control) feedback controller for the strip middle part. It is shown from by a computer simulation that the proposed controller is very effective to the strip top-tail parts including the middle part.

• Transactions of the Korean Society of Mechanical Engineers
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• v.12 no.2
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• pp.389-396
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• 1988

Microprocessor-based software DDA interpolator is developed and applied to two axis contouring control of X-Y table. Developed assembly program is composed of feedrate, linear and circular DDA interpolation routines. Reference-pulse type of open-loop stepping motor control system in which the micro-computer produces a sequence of reference pulses for each axis of motion is adopted. To test performance of the developed program, X-Y table drive system based on stepping motor and shaft encoder is designed. Conturing error of the system in linear and circular path is within .+-. 0.2mm under start stop pulse rate of stepping motor.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2299-2301
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• 2000

In this paper, the design of PID controller using Neural networks for the control of non-linear system is presented. First, non-linear system is identified using BPN(Backpropagation Network) algorithm. This identified model is connected to the PID controller and the parameters of PID controller are updated to the direction of reducing the difference between the identified model output and model reference output in arbitrary input signal. Therefore, identified model output tracks the model reference output in an acceptable error range and the parameters of controller are updated adaptively. The output of the system has a good performance in case of both noisy and noiseless model reference and we can control the system stable in off-line when the dynamics of the system is changed.

• 제어로봇시스템학회:학술대회논문집
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• 1989.10a
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• pp.483-488
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• 1989

In this paper, the concept of persistent excitation(PE) is examed and the model reference adaptive control of a linear plant subjected to bounded disturbances is considered. Computer simulation reasults of nonlinear differential equations shows that the global behavior of the adaptive system depends upon the PE of the reference input as well as the amplitude of the external disturbances. The sufficient conditions on the PE of the reference input for the signals in the adaptive system to be globally bounded has been derived.

• Transactions on Control, Automation and Systems Engineering
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• v.4 no.4
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• pp.330-340
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• 2002

In this Paper. a non-linear approach to a design of model reference adaptive control is presented. The approach is demonstrated by a case study of a simple single-pole and no zero, linear, discrete-time plant. The essence of the idea is to generate a full non-linear model of the plant dynamics and the parameter adaptation dynamics as a gradient descent algorithm with respect to a Riemannian metric. It is shown how a Riemannian metric can be chosen so that the modelled plant dynamics do in fact match the true plant dynamics. The performance of the proposed scheme is compared to a traditional model reference adaptive control scheme using the classical sensitivity derivatives (Euclidean gradients) for the descent algorithm.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.2
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• pp.157-163
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• 2014

In this paper, a robust MRAC (model reference adaptive control) scheme is applied to control an electrohydraulic positioning system under various loads. The inverse dead-zone compensator in the control system cancels out the dead-zone response, and an integrator added to the controller provides good position-tracking ability. LQG/LTR (linear quadratic Gaussian control with loop transfer recovery) closed-loop model is used as the reference model for learning the MRAC system. LQG/LTR provides a systematic technique to design the linear controller that optimizes the objective function using some compromise between the control effort and the system performance in the frequency domain. Different external load tests are performed to investigate the effectiveness of the designed MRAC system in real time. The experimental results show that the tracking performance of the proposed system is highly accurate, which offers considerable robustness even with a large change in the load.

• Proceedings of the KIEE Conference
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• 2008.04a
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• pp.51-52
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• 2008

In this paper, we propose two control schemes. The first control scheme is an adaptive passivity-based excitation control which regulates the terminal voltage to its reference. This controller is obtained through two steps: firstly, a simple direct adaptive passivation controller is designed for the power system with parametric uncertainties; then a linear PI controller is applied to converge the terminal voltage to its reference. The second control scheme is a linear governor control which consists of the frequency and the mechanical power. It is shown that the internal dynamics are locally stable with controllable damping. In the end, the boundness of all electrical variables, the frequency, the mechanical power, and the convergence of the terminal voltage to its reference can be achieved by these control schemes.

• Journal of the Korean Society for Precision Engineering
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• v.16 no.11
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• pp.197-203
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• 1999

Increasing demands on precision machining have necessitated the tool to move not only position error as small as possible, but also with smoothly varying feedrates. Because of the lack of accurate and efficient algorithms for generation of 3-dimensional lines and circles, a full accomlishment for available machine tool resolution is generally unavailable. In this paper, a reference-pulse type 3-axis PC_NC milling system is developed for the precision machining of complex shapes in 3-dimensional space. Three AC servomotors are used as the actuator instead of the hand wheel to operate a 3-axis milling machine under the same mechanical structure. A PC is used to handle the control signal calculation for various types of motion command. To achieve the synchronous 3-axis motion, a real-time reference-pulse 3-dimensional linear and circular interpolator based on the intersection criteria is developed in software. The performance test via computer simulation and actual machining have shown that the PC-NC milling system is useful for the machining of arbitrary lines and circles in 3-dimensional space.

• Proceedings of the KIEE Conference
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• 2002.11c
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• pp.54-57
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• 2002

In this paper model reference adaptive control (MRAC) of linear time-varying(LTV) systems is considered. MRAC for a linear time invariant(LTI) system does not assure the boundedness of the output and parameter estimation errors in the presence of time variations of the parameters. However, changing the adaptive laws such as use of $\sigma$-modification can result in the boundedness of the output and parameter estimation errors[5]. Together with the $\sigma$-modification in the adaptive law, we also modify the control law by adding an additional term to the standard control law. The additional term leads to smaller bounds of the output and parameter estimation errors when compared to the case where only the standard control law is applied.