• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.12
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• pp.2365-2370
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• 2008

In this paper, applications of wavelet neural network controller to position control of nonlinear system are considered. Wavelet neural network is used in the objectives which improve the efficiency of LQR controllers. It is possible to make unstable nonlinear systems stable by using LQR(Linear Quadratic Regulator) technique. And, in order to be adapted to disturbance effectively in this system it uses wavelet neural network controller. Applying this method to the position control of nonlinear system, its usefulness is verified from the results of experiment.

• The Transactions of the Korean Institute of Power Electronics
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• v.24 no.6
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• pp.389-395
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• 2019

This paper presents the sensorless position control of an auxiliary scaffolding step system for vehicles using DC motors. The designed auxiliary scaffolding step has a mechanical protector at the stop position. At this position, the scaffolding is forcibly stopped by the mechanical protector, and the motor current is dramatically increased to the stall current of the DC motor, thereby increasing the electrical damage. In this study, the estimated back EMF- and current model-based observers are proposed to estimate the motor speed and stop position. A simple V/F acceleration voltage pattern is used to operate the auxiliary scaffolding system. The estimated moving position is adopted to determine the stop position of the DC motor with the load current state. The operating current of the DC motor can be reduced by the estimated moving position and V/F acceleration pattern. At the stop position, the proposed sensorless position controller can smoothly stop the DC motor with the estimated moving position and reduced load current without any mechanical and electrical stress from the stall current from the mechanical protector. The proposed control scheme is verified by the comparison of simulations and experiments.

• Journal of Advanced Marine Engineering and Technology
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• v.29 no.3
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• pp.251-259
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• 2005

A discrete time model reference adaptive control has been applied in order to compensate the nonlinear friction characteristics in a hydraulic proportional position control system. As nonlinear friction, static and coulomb friction forces are considered and modeled as dead zone and external disturbance respectively. The model reference adaptive control system consists of a cascade combination of the dead zone. external disturbance and linear dynamic block. For adaptive control experiment. the DSP(Digital Signal Processor) board has been interfaced the hydraulic proportional position control system. The experimental results show that the MRAC(Model Reference Adaptive Control) for compensation of static and coulomb friction are very effective.

• KIEE International Transaction on Electrical Machinery and Energy Conversion Systems
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• v.5B no.2
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• pp.189-195
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• 2005

This paper presents a new velocity estimation strategy for a non-salient permanent magnet synchronous motor drive without high frequency signal injection or special PWM pattern. This approach is based on the d-axis current regulator output voltage of the drive system, which contains the rotor position error information. The rotor velocity can be estimated through a rotor position tracking PI controller that controls the position error at zero. For zero and low speed operation, the PI gain of the rotor position tracking controller has a variable structure according to the estimated rotor velocity. Then, at zero speed, the rotor position and velocity have sluggish dynamics because the varying gains are very low in this region. In order to boost the bandwidth of the PI controller during zero speed, the loop recovery technique is applied to the control system. The PI tuning formulas are also derived by analyzing this control system by frequency domain specifications such as phase margin and bandwidth assignment.

• Journal of Institute of Control, Robotics and Systems
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• v.7 no.5
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• pp.399-406
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• 2001

This paper presents a dynamic modeling and a sliding mode controller for the high-speed/high-accuracy position control system. The selected target system is the wire bonder assembly which is used in the semiconductor assembly process. This system is a reciprocating one around the pivot point that consists of VCM(voice coil motor) as an actuator and transducer horn as a bonding tool. For the modeling elements, the sys-tem is divided into electrical circuit, magnetic circuit and mechanical system. Each system is modeled using the bond graph method and united into the full system. Two major aims are considered in the design of the controller. The first one is that the horn must track the given reference trajectory. The second one is that the controller must be realizable by using the DSP board. Computer simulation and experimental results show that the designed sliding mode controller provides better performance than the PID controller.

• Transactions of the Korean Society of Machine Tool Engineers
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• v.12 no.6
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• pp.77-83
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• 2003

This paper deals with a position control problem of a hydraulic proportional position control system using a nonlinear friction compensation control. As nonlinear friction, stiction and coulomb friction forces are considered and modeled as deadzone and external disturbance respectively. In order to compensate this nonlinearities, we designed the controller which is the adaptive friction compensator using discrete time Model Reference Adaptive Control method in this paper. Digital Signal Processing board is employed for data acquisition and manipulation. The experimental results show that response is slow and steady-state error cannot be compensated properly without friction compensation but this compensator is effective to obtain fast response and good steady-state response.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1992.04a
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• pp.385-389
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• 1992

The position control of the electro-hydraulic servo indexing system in a flexible forging machine was investigated. The role of an Electro-hydraulic servoindexing system is to rotate a workpiect fast and accurately to a desired position. Since the inertia of a workpiece changes during each forging step, an adapt control scheme could be adopted to the position control of the workpiece. A generalized predictive control method which depends on predicting the plant output over several steps ahead based on the assumption about future control actions is proposed. The perormance of the proposed GPC algorithm is investigated experimentally and compared with that of PID control. Experimental results show that the proposed GPC algorithm is satisfactory for the position control of the workpiece of an electrohydraulic indexing system.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.7
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• pp.84-90
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• 2003

This paper develops a control method that is composed of the proportional control algorithm and the learning algorithm based on the recurrent neural networks (RNN) for the position control of a pneumatic rodless cylinder. The proportional control algorithm is suggested for the modeled pneumatic system, which is obtained easily simplifying the system, and the RNN is suggested for the compensation of the modeling errors and uncertainties of the pneumatic system. In the proportional control, two zones are suggested in the phase plane. One is the transient zone for the smooth tracking and the other is the small movement zone for the accurate position control with eliminating the stick-slip phenomenon. The RNN is connected in parallel with the proportional control for the compensation of modeling errors and frictions, compressibilities, and parameter uncertainties in the pneumatic control system. This paper experimentally verifies the feasibility of the proposed control algorithm for such pneumatic systems.

• Proceedings of the IEEK Conference
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• 1998.06a
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• pp.897-900
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• 1998

Through fuzzy logic controller is very useful to many areas, it is difficult to build up the rule-base by experience and trial-error. So, effective self-tuning fuzzy controller for the position control of ball and beam is designed. In this paper, we developed the neural network control system with fuzzy-neuron which conducts the adjustment process for the parameters to satisfy have nonlinear property of the ball and beam system. The proposed algorithm is based on a fuzzy logic control system using a neural network learinign algorithm which is a back-propagation algorithm. This system learn membership functions with input variables. The purpose of the design is to control the position of the ball along the track by manipulating the angualr position of the serve. As a result, it is concluded that the neural network control system with fuzzy-neuron is more effective than the conventional fuzzy system.

• 제어로봇시스템학회:학술대회논문집
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• 1996.10a
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• pp.380-384
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• 1996

This paper represents an adaptive position controller with the disturbance observer for multi-axis servo system. The overall control system consists of three parts : the position controller, the disturbance observer with free parameters and cross-coupled controller which enhances contouring performance by reducing errors. Using two-degrees-of freedom conception, we design the command input response and the closed loop characteristics independently. The servo system can improve the closed loop characteristics without affecting the command input response. The characteristics of the closed loop system is improved by suppressing disturbance torque effectively with the disturbance observer. Moreover, the cross-coupled controller enhances tracking performance. Thus total position control performance is improved. Finally, the performance of the proposed controller shows that it improves the contouring performance along with the reference trajectory in the XY-table.