• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.486-489
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• 1998

In this paper, we introduced the neural network to reduce force ripple of current controller for a linear pulse motor. In general, conventional position controllers of linear pulse motor disregard the modeling error and load variations, which cause inaccuracy in position control. The proposed current controller based on neural network teaming modifies the current commands in order to reduce force ripple due to these factors. The experiment results show that the proposed controller works efficiently for accurate position control of linear pulse motor.

• Journal of Institute of Control, Robotics and Systems
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• v.16 no.2
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• pp.134-139
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• 2010

In order to overcome some problems of existing anti-windup methods, this paper defines LQ (Linear Quadratic) observer and proposes a new anti-windup method using the LQ observer. LQ observer is derived by linear quadratic optimization in order to calculate controller states, which make the controller outputs equal to the plant inputs. And we propose an algorithm so that it can be implemented by a digital controller easily. The relationship between the design parameters and the anti-windup performance is shown via some numerical examples, which cover the cases with the anti-windup method using LQ observer designed and the case without it. Finally, the anti-windup performance of the proposed method is exemplified via comparison with the existing model-based conditioning scheme method[4].

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.10a
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• pp.94-99
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• 2005

Though the technology on the ultra-precise machining has been developed intensively, the high speed and high precision for large machining range is still very hard to achieve. The linear motor system fur the universal machining center is proper fur high speed and high precision, but it has drawback of sensitivity to disturbance. In this research, two degrees of freedom controller based on the zero phase error tracking controller (ZPETC) and disturbance observer are proposed to improve the tracking performance and dynamic stiffness of linear motor system. The proposed controller is verified in simulations and experiments on a nano-positioner system, and the experimental result shows that the tracking performance improved. In addition, the PID optimization method is proposed for the commercialized controller such as the PMAC based system. The tracking as well as impedance is included in the cost function of optimization.

• Transactions on Control, Automation and Systems Engineering
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• v.2 no.4
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• pp.244-247
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• 2000

In this paper, a discrete-time sliding mode controller for linear time-varying systems with disturbances is proposed. The proposed method guarantees the systems state is globally uniformly ultimately bounded(G.U.U.B) under the existence of time-varying disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2003.10a
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• pp.1382-1386
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• 2003

In this paper, we propose a controller for the position of a cart and the angle of a pendulum. To achieve both purposes simultaneously, we divide the system into the dominant subsystem and the dominated one after partial feedback linearization. The proposed controller is composed of a nonlinear controller stabilizing the dominant subsystem and a linear quadratic controller. Using the proposed controller, the controllable region is increased by the nonlinear control part and the control input minimized by the linear control part (LQR).

• International Journal of Automotive Technology
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• v.8 no.4
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• pp.445-453
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• 2007

This paper presents a robust controller design approach for improving vehicle dynamic roll motion performance and guaranteeing the closed-loop system stability in spite of vehicle parameter variations resulting from aging elements, loading patterns, and driving conditions, etc. The designed controller is linear parameter-varying (LPV) in terms of the time-varying parameters; its control objective is to minimise the $H_{\infty}$ performance from the steering input to the roll angle while satisfying the closed-loop pole placement constraint such that the optimal dynamic roll motion performance is achieved and robust stability is guaranteed. The sufficient conditions for designing such a controller are given as a finite number of linear matrix inequalities (LMIs). Numerical simulation using the three-degree-of-freedom (3-DOF) yaw-roll vehicle model is presented. It shows that the designed controller can effectively improve the vehicle dynamic roll angle response during J-turn or fishhook maneuver when the vehicle's forward velocity and the roll stiffness are varied significantly.

• Journal of the Korean Society for Precision Engineering
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• v.29 no.1
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• pp.79-86
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• 2012

This paper proposes PID and RIC (Robust Internal-loop Compensator) based motion controller using dual learning algorithm for position control of linear synchronous motor respectively. Its gains are auto-tuned by using two learning algorithms, reinforcement learning and neural network. The feedback controller gains are tuned by reinforcement learning, and then the feedforward controller gains are tuned by neural network. Experiments prove the validity of dual learning algorithm. The RIC controller has better performance than does the PID-feedforward controller in reducing tracking error and disturbance rejection. Neural network shows its ability to decrease tracking error and to reject disturbance in the stop range of the target position and home.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.3 no.4
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• pp.875-885
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• 1999

This paper presents an application of LMI-based techniques to the mixed $H_2/ H_\infty$ control of an inverted pendulum. The linear model of the inverted pendulum represented by an LFR(Linear Fractional Representation) model of uncertainties is derived. Considered uncertainties are three nonlinear components and a parameter uncertainty Augmenting the LFR model by adding weighting functions, we get a generalized plant, for which we design a mixed $H_2/ H_\infty$ controller using the LMI technique. To evaluate control performances and robust stability of the mixed $H_2/ H_\infty$ controller designed, we compare it with the $ H_\infty$controller through the simulation and experiment. The mixed $H_2/ H_\infty$ controller shows the better control performances and robust stability than the $H_\infty$controller in the sense of pendulum angle.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.51 no.4
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• pp.195-202
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• 2002

The high performance position controller named 'Unified PID Position Controller'is presented in part 1 of this paper. In part 2, we provide smart gain adjustment methods including the freedom utilizations for rare sensitivity toward the system parameter variation and for increasing the stiffness of the system. Owing to the provided gain tuning strategy, the overall system characteristics can be stabilized without over-shoot phenomena when the system parameter is changed in the rate of from 0.5 to 2∼4. Moreover, for the actual feasibility to the industrial fields, a simple butt effective anti-windup strategy prohibiting the integral component of the PID position controller from saturation is presented too. All of the presented algorithms are verified through the experiment works with commercial linear motor.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.75.5-75
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• 2001

In this paper, we study design of a ILQ(Inverse Linear Quadratic optimal control) looper control system for hot strip mills. The looper which is placed between stands plays an important role in controlling strip width by regulating strip tension variation generated from the velocity difference of main work rolls. A Looper servo controller is designed by ILQ control theory which is an inverse problem of LQ(Linear Quadratic optimal control) control. The mathematical model for looper system is obtained by Taylor´s linearization of nonlinear differential equations. Then we designed linear controller for linearization model by using the ILQ control algorithm. Thereafter this controller is applied to the nonlinear model for model identification. As a result, we show the controller´s robustness for the model error, external disturbance and sensor noise.