• Journal of the Korean Institute of Telematics and Electronics S
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• v.35S no.8
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• pp.32-38
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• 1998

In this paper, we design a robust controller for trajectory control of n-link robot manipulators with bounded parametric uncertainties. The proposed control scheme with integral control improves tracking error due to limit of the robust feedback gains and use of continuous control input for chattering rejection. The integral of the tracking error is augmented to the error system equation and the stability of the closed-loop system is achieved. The performance of the proposed method is demonstrated by simulation on a 2-link manipulator.

• Journal of Institute of Control, Robotics and Systems
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• v.17 no.6
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• pp.573-578
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• 2011

We propose a switching-based adaptive state feedback controller for a class of nonlinear systems that have uncertain nonlinearity. The base of the proposed conditions on the nonlinearity is the feedforward form, then it is extended via a nonlinear function containing all the states and the control input. As a result, more generalized systems containing feedforward and nonfeedforward terms are allowed as long as the ratio condition of the nonlinear function is satisfied. Moreover, the information on the growth rate of nonlinearity is not required a priori in our control scheme.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.98-106
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• 2006

This paper proposes to position and speed control of interior Permanent magnet synchronous motor(IPMSM) drive without mechanical sensor. Also, this paper develops a adaptive fuzzy controller based fuzzy logic control for high performance of PMSM drives. In the proposed system, fuzzy control is used to implement the direct controller as well as the adaptation mechanism. A Gopinath observer is used for the mechanical state estimation of the motor. The observer was developed based on nonlinear model of IPMSM, that employs a d-q rotating reference frame attached to the rotor. A Gopinath observer is implemented to compute the speed and position feedback signal. The validity of the proposed scheme is confirmed by various response characteristics.

• Proceedings of the Safety Management and Science Conference
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• 1999.11a
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• pp.217-236
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• 1999

Engineering process control (EPC) is one of the techniques very widely used in process. EPC is based on control theory which aims at keeping the process on target. Statistical process control (SPC), also known as statistical process monitoring. The main purpose of SPC is to look for assignable causes (variability) in the process data. The combined SPC/EPC scheme is gaining recognition in the process industries where the process frequently experiences a drifting mean. This paper aims to study the difference between SPC and EPC in simple terms and presents a case study that demonstrates successful integration of SPC and EPC for a product in drifting industry. Statistical process control (SPC) monitoring of the special causes of a process, along with engineering feedback control such as proportional-integral-derivative (PID) control, is a major tool for on-line quality improvement.

• Transactions of the Korean Society of Automotive Engineers
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• v.9 no.3
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• pp.92-99
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• 2001

This paper presents a simulation study using a robust controller to improve the roll stability of a vehicle. The controller is designed in the framework of an output feedback H$_{\infty}$ control scheme based on the 3DOF linear vehicle model, solving the mixed-sensitivity problem to guarantee the robust stability and disturbance rejection with respect to parameter variations due to laden and running vehicle conditions. In order to investigate the feasibility of the active roll control system in a real car, its performance is evaluated by simulation in a 10DOF full vehicle model with actuator dynamics and tire characteristics.

• Proceedings of the KIEE Conference
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• 1992.07a
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• pp.279-281
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• 1992

In this paper, an LQG/LTR procedure for stable nonminimum phase systems is suggested using predictor scheme. In the method, the performance of the target feedback loop can be easily adjusted and the recovery error is less dependent on the location of NMP zeros than previous methods. The gain and phase margin and the robust ness for modeluncertainty of the suggested control system are obtained.

• Proceedings of the KAIS Fall Conference
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• 2008.11a
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• pp.191-196
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• 2008

The intent of this paper is to describe a neural network structure called dynamic neural processor(DNP), and examine how it can be used in developing a learning scheme for computing robot inverse kinematic transformations. The architecture and learning algorithm of the proposed dynamic neural network structure, the DNP, are described. Computer simulations are provided to demonstrate the effectiveness of the proposed learning using the DNP.

• Journal of Power Electronics
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• v.4 no.3
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• pp.169-179
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• 2004

This paper presents the steady-state analysis of the three-phase self-excited induction generator (SEIG). The three-phase SEIG with a squirrel cage rotor is driven by a variable-speed prime mover (VSPM) or a constant-speed prime mover (CSPM) such as a wind turbine or a micro gas turbine. Furthermore, a PI closed-loop feedback voltage regulation scheme of the three-phase SEIG driven by a VSPM on the basis of the static VAR compensator (SVC) is designed and evaluated for the stand-alone AC and DC power applications. The simulation and experimental results prove the practical effectiveness of the additional SVC with the PI controller-based feedback loop in terms of its fast responses and high performances

• Proceedings of the KIEE Conference
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• 1988.11a
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• pp.49-52
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• 1988

This paper deal with the robust high gain controller design technique by inner-loop feedback, output feedback, feedforward compensation, and presented the algorithm to be required the determination of gain matrix. Using this control scheme, simulation results have bean tested for the linearized model of the aircraft.

• 제어로봇시스템학회:학술대회논문집
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• 1988.10b
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• pp.1014-1017
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• 1988

Direct-drive robots have excellent features including no backlash, small friction, and high mechanical stiffness. However, dynamic coupling among joints as well as nonlinear effects become more prominent than traditional robots with reducers. Another critical issue is that the robot becomes more sensitive to the change of load. In this paper, we develop a simple current feedback scheme for reducing the influence of dynamic coupling and load sensitivity on the direct-drive robots. The method is implemented on a 2 d.o.f. planar direct-drive robot. Then the validity of the method is demonstrated through experiments.