• Transactions of the Korean Society of Mechanical Engineers B
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• v.41 no.6
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• pp.397-407
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• 2017

In this study, a SCR system is employed to selectively reduce $NO_X$, which is a major cause of environmental pollution and issues in diesel engines. In particular, this paper focuses on the combination of feedforward injection strategies, depending on the NO/$NO_X$ ratio, and feedback injection control, using $NH_3$ coverage ratio, based on a SCR model. A 2.2 L passenger diesel engine, which is equipped with a diesel oxidation catalyst (DOC) and a diesel particle filter (DPF), was used in the experiments. The developed control algorithm is implemented on a real-time computer with injection control algorithm. By analyzing the $NO_X$ emission measurement, the performance of the proposed injection control algorithm is verified.

• Proceedings of the KIEE Conference
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• 1997.07f
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• pp.2040-2042
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• 1997

A voltage source PWM converter based on lossless resonator and a source current control system are proposed in this paper. It is proved that steady-state deviation reduces to zero from the transfer function of source current control system, owing to the lossless resonator. The system can be controlled by the feedback control only, because of no need to use a feedforward control in the proposed a source current control system. Therefore, as using lossless resonator, control system can be simply made up. Simulations are described in the case of difference between source current and source current reference.

• Journal of KSNVE
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• v.6 no.5
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• pp.567-574
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• 1996

This paper concerns an articulated space robot with flexible links. The equations of its motion are derived by means of the Lagrangian mechanics. Assuming that magnitude of elastic motions are relatively small, the perturbation approach is taken to separate the original equations of motion into linear and nonlinear equations. Th effect the desired payload motion, open loop control inputs are first determined based on the nonlinear equations. One the other hand, in order to reduce the positional errors during the maneuver, vibration suppression is actively done with a feedforward control for disturbance cancellation to some extent. Additionally, for performance robustness against residual disturbance, an LQ control modified to have a prescribed degree of stability is applied based on the linear equations. Measurement equations are formulated to be used for the maximum likelihood estimator to reconstruct states from the original robot equations of motion. Finally, numerical simulations show effectiveness of the proposed control design scheme.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 1994.04a
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• pp.22-27
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• 1994

본 논문의 목적은 피이드백 제어시스템에서 주기적 외란(periodic disturbances),d$_{\omega}$, 이 출력센서에 감지될 경우, 이를 제거하기 위한 새로운 적응제어기(adaptive controller)를 설계하는 것이다. 2장에서는 주기적 외란을 제거하기 위한 방법으로 많이 사용되어 온 피이드백 제어기 (feedback controller)와 피이드포워드 제어기 (feedforward controller)를 설명한다. 3장에서는 적응 피이드포워드 제어기가 페루프 전달함수를 변경시키는 점에서 피이드백 제어기와 동일함을 보이고, 전달함수를 변경시키지 않아 페루프시스템의 강건성을 저하시키지 않는 효율적인 피이드포워드 제어기를 설계한다. 4장에서는 제안된 피이드포워드 제어기의 학습알고리즘을 유도한다. 5장에서는 모의 실험을 통하여 제안한 피이드포워드 제어기 및 학습 알고리즘의 효율성을 검증하기로 한다.

• Transactions of The Korea Fluid Power Systems Society
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• v.4 no.2
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• pp.21-27
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• 2007

This paper deals with the issue of trajectory tracking control of a clamping cylinder for injection moulding machine, which is directly driven by speed controlled hydraulic pump in combination with AC servomotor. As a fundamental step prior to tracking controller design, feedback control system is developed by implementing a position control loop parallel with a system pressure control loop. A sliding mode controller combining velocity feedforward scheme is developed for enhancing the tracking performance. Consequently a significant reduction in tracking error is achieved for both position and pressure control applications.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.51-53
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• 1993

This paper proposes a design of the tracking controller using artificial neural network and the compare the result with a result of optimal controller. In practical use, conventional Optimal controller has some limits. First, optimal controller can be designed only for linear system. Second, for many systems state observation is difficult or sometimes impossible. But the controller using artificial neural network does not need mathmatical model of the system including state observation, so it can be used for both linear and nonlinear system with no additional cost for nonlinearity. Designed multi layer neural network controller is composed of two parts, feedforward controller gives a steady state input & feedback controller gives transient input via minimizing the quadratic cost function. From the comparison of the results of the simulation of linear & nonlinear plant, the plant controlled by using neural network controller shows the trajectory similar to that of the plant controlled by an optimal controller.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.14 no.7
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• pp.3127-3134
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• 2013

This paper presents the verified results from the examination of the control algorithm, logic composition, and vehicle condition of the engine that has been adapted for DME fuel. It introduces the development process of the control structure and the logic control based on control map and auto-code generation, and finally verifies the reliability and performance of the overall control. The control structure largely consists of the injection control part that implements driver demand into an engine net torque and the air control system part that satisfies characteristics of exhaust gas and power performance. The control logic is designed with feedforward and feedback control for each of its control functions for an enhanced response. Moreover, the control map of the feedforward controller is created by the use of an engine model created by test data of mass product diesel engine, and it was subsequently calibrated in the test process of the engine and vehicle state. A test mode was completed by attaching the developed controller to the vehicle, and a reduction in gas emission is confirmed by the calibration of EGR, VGT, and injection times.

• Journal of the Korean Society for Precision Engineering
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• v.19 no.9
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• pp.106-110
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• 2002

A need fer stable and comfortable cabins in the high-speed passenger ships has increased. For active control of the motion of the ship cabin, a few control algorithms have been applied to the three dimensional real models in the vibration basin. Experimental results show that the feedforward neural network with a linear feedback controller is one of the promising control algorithms for this active control.

• Journal of the Korean Society of Industry Convergence
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• v.18 no.4
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• pp.224-230
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• 2015

In this paper, it is presented a learning controller for repetitive walking control of biped walking robot. We propose the iterative learning control algorithm which can learn periodic nonlinear load change ocuured due to the walking period through the intelligent control, not calculating the complex dynamics of walking robot. The learning control scheme consists of a feedforward learning rule and linear feedback control input for stabilization of learning system. The feasibility of intelligent control to biped robotic motion is shown via dynamic simulation with 25-DOF biped walking robot.

• Proceedings of the KIEE Conference
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• 1995.07b
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• pp.670-672
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• 1995

This paper deals with the robust two-degree-of-freedom multivariable control system using $H_{2}/H{\infty}$optimization method which can achieve the robust stability and the robust performance, simultaneously. The feedback controller can obtain the robust stability property. The feedforward controller can obtain the robust performance property under modelling error. The robust two-degree-of-freedom multivariable control system is applied to the nonlinear multivariable boiler-turbine system. The validity of the proposed method is verified though being compared with LQG/LTR design method.