• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.20 no.2
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• pp.121-128
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• 2011

As high precision industries such as semiconductor, TFT-LCD manufacturing and MEMS continue to grow, the demand for higher DOF precision stages has been increasing. In general, the stages should accommodate a prescribed range of payloads in order to position various precision manufacturing/inspection instruments. Therefore a nonlinear controller using sliding motion is developed, which bears mass perturbation and makes the upper plate of the stage move in 6 DOF. For the application of the nonlinear control, an observer is also developed based on expected noise covariance. To eliminate the steady state error of step response, integral terms are inserted into the state-space model. The linear term of the controller is designed using optimization scheme in which parameters can be weighted according to their physical significance, whereas the nonlinear term of the controller is designed using trial and error method. A comprehensive simulation study proves that the designed controller is robust against mass perturbation and completely eliminates steady state errors.

• Journal of Mechanical Science and Technology
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• v.16 no.8
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• pp.1053-1063
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• 2002

This paper presents a robust nonlinear controller for a f degree of freedom (DOF) parallel manipulator in the task space coordinates. The proposed control strategy requires information on orientations and translations in the task space unlike the joint space or link space control scheme. Although a 6 DOF sensor may provide such information in a straightforward manner, its cost calls for a more economical alternative. A novel indirect method based on the readily available length information engages as a potential candidate to replace a 6 DOF sensor. The indirect approach generates the necessary information by solving the forward kinematics and subsequently applying alpha-beta-gamma tracker With the 6 DOF signals available, a robust nonlinear task space control (RNTC) scheme is proposed based on the Lyapunov redesign method, whose stability is rigorously proved. The performance of the proposed RNTC with the new estimation scheme is evaluated via experiments. First, the results of the estimator are compared with the rate-gyro signals, which indicates excellent agreement. Then, the RNTC with on-line estimated 6 DOF data is shown to achieve excellent control performance to sinusoidal inputs, which is superior to those of a commonly used proportional-plus-integral-plus-derivative controller with a feedforward friction compensation under joint space coordinates and the nonlinear controller under task space coordinates.

• Transactions of the Korean Society of Mechanical Engineers A
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• v.35 no.1
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• pp.59-65
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• 2011

The aerodynamic power and torque of wind turbines are extremely nonlinear. Therefore, the overall dynamic behavior of a wind turbine exhibits nonlinear characteristics that are dependent on the magnitude of the wind speed. The nonlinear aerodynamic characteristics of the wind turbine also affect the characteristics of the control system of the wind turbine. Therefore, the analysis of the nonlinear aerodynamic characteristics of wind turbine is essential in designing the wind-turbine controller. In this study, the nonlinear aerodynamic characteristics and the effects of these characteristics on the closed-loop pitch system with PI controller for an 1-mass model of the wind turbine are investigated above rated power.

• Journal of Navigation and Port Research
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• v.26 no.2
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• pp.193-197
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• 2002

This paper suggests a method to design TSK(Takagi-Sugeno-Kang) fuzzy nonlinear control system for automatic steering system which contains the nonlinear component of ship's maneuvering equation. A TSk fuzzy model can be identified using input-output data and represent a nonlinear system very well. A TSK fuzzy controller can be designed systematically from a TSK fuzzy model because the consequent part of TSK fuzzy rule is a linear input-output equation having a constant term. Therefore, this paper suggests the method identifying the TSK fuzzy model and designing the TSK fuzzy controller based on the TSK fuzzy model for ship steering.

• Journal of Advanced Marine Engineering and Technology
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• v.38 no.6
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• pp.710-715
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• 2014

This paper investigates the design scheme of fuzzy-based adaptive controller to give adaptability for controlling nonlinear systems. For this, a nonlinear system is linearized by the several subsystems depending on the operating point or parameter changes. Then, the sub-controller is designed by linear control scheme for each subsystem and the sub-controllers are fused with each gain of sub-controllers using fuzzy rules. The proposed method is applied to an inverted pole system which has structurally instability and nonlinearity, and simulation works are shown to illustrate the effectiveness by comparison with the interpolation-based adaptive Controller.

• Proceedings of the Korean Institute of IIIuminating and Electrical Installation Engineers Conference
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• 2009.05a
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• pp.420-423
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• 2009

The conventional fixed gain PI controller is very sensitive to step change of command speed, parameter variation and load disturbances. The precise speed control of interior permanent magnet synchronous motor(IPMSM) drive becomes a complex issue due to nonlinear coupling among its winding currents and the rotor speed as well as the nonlinear electromagnetic developed torque. Therefore, there exists a need to tune the PI controller parameters on-line to ensure optimum drive performance over a wide range of operating conditions. This paper is proposed hybrid intelligent-PI(HIPI) controller of IPMSM drive using adaptive learning mechanism(ALM) and fuzzy neural network(FNN). The proposed controller is developed to ensure accurate speed control of IPMSM drive under system disturbances and estimation of speed using artificial neural network(ANN) controller. The PI controller parameters are optimized by ALM-FNN at all possible operating condition in a closed loop vector control scheme. The validity of the proposed controller is verified by results at different dynamic operating conditions.

• International Journal of Control, Automation, and Systems
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• v.4 no.6
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• pp.756-762
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• 2006

Shape Memory Alloy(SMA) actuators, which have the ability to return to a predetermined shape when heated, have many potential applications such as aeronautics, surgical tools, robotics and so on. Although the conventional PID controller can be used with slow response systems, there has been limited success in precise motion control of SMA actuators, since the systems are disturbed by unknown factors beside their inherent nonlinear hysteresis and changes in the surrounding environment of the systems. This paper presents a new development of a SMA position control system by using a self-tuning fuzzy PID controller. This control algorithm is used by tuning the parameters of the PID controller thereby integrating fuzzy inference and producing a fuzzy adaptive PID controller, which can then be used to improve the control performance of nonlinear systems. The experimental results of position control of SMA actuators using conventional and self-tuning fuzzy PID controllers are both included in this paper.

• 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).

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1132_1133
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• 2009

In this paper, a observer-based PI controller will be developed for PEM fuel cell system. Nonlinear model of PEM fuel cell system is introduced to study the controller design problems. Sliding mode observer will be designed to estimate the cathode and anode pressures of PEMFC system. And a nonlinear state observer is also designed to estimate the other states such as supply manifold pressure, Oxygen pressure, Hydrogen pressure, return manifold pressure, etc. These estimated states are used to design the observer-based PI controller. The validity of the proposed controller will be verified by using computer simulation.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1725_1726
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• 2009

The purpose for this paper is to obtain the ��$H_{\infty}$ LMI with fuzzy PI controller for induction motor which is nonlinear system. The controller type is PI and the control gains are obtained based on $H_{\infty}$ control problem. The PI controller is considered a part of a plant and the problem is changed to get controller with static gains. The nonlinear system is approximated as several linear systems and combined by using fuzzy technique.