• Journal of Institute of Control, Robotics and Systems
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• v.10 no.1
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• pp.42-46
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• 2004

A 2-mass resonant system is one that has a flexible coupling between a load and a driving motor. Due to this flexibility, the system often suffers vibration especially when the motor is controlled for higher speed command. In order to suppress such a vibration, an iterative learning control is applied to the 2-mass resonant system in this paper. The motor speed is controlled according to the relation with the load speed. The desired speed trajectories are derived under the condition for no vibration. The simulation result suggests that the proposed method effectively suppresses the vibration even when there exist model uncertainties.

• Journal of Power System Engineering
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• v.2 no.2
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• pp.67-72
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• 1998

To improve control performance, especially positioning speed, of a pneumatic positioning system, dynamic characteristics of a control valve should be considered. In case we design controller including dynamic characteristics of a control valve, it's not easy to design controller gain using simple state feedback because degree of a control system is increased. This study designed controller using loop shaping of $H_{\infty}$ control theory for a model composed of a pneumatic actuator and a control valve, and positioning experiment using this controller was performed. As a result, it was verified that the controller is useful for high speed positioning of a pneumatic positioning system.

• Journal of Advanced Marine Engineering and Technology
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• v.17 no.5
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• pp.86-98
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• 1993

The application of A.C. motor for servo system is rapidly increased according to the recent advance of power electronics and digital control techniques. The induction motor which has a simple structure and needs less maintenance has become to be used widely in the industrial field for the speed and position control recently. In this paper, the full-bridge resonant inverter is applied to the speed control of single phase inducting motor. The digital PID control algorithm is used and the control parameter is determined by the Zigler-Nichols transient response method. The speed control is carried out by the one chip micro-processor(intel EV 8097BH) and control program is developed by the assembly language. By the experimental result, it is confirmed that the speed of single phase induction motor driven by full bridge series inverter can be smoothly controlled by a digital PID controller.

• Journal of the Korean Society for Precision Engineering
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• v.18 no.2
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• pp.192-198
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• 2001

In this study, a methodology of synchronous control which can be applied to position synchronization of a two-axes driving system has been developed. The synchronous error is caused by model uncertainties and torque disturbance of each axis. To overcome these problems, the proposed synchronous control system has been composed of two speed controllers and one synchronous controller. The speed controllers based on PID control law are aimed at the following to speed reference. And the parameters of speed controllers have been designed in order that speed response of the second axis corresponds with one of first axis. Especially, considering to model uncertainties of each axis, the synchronous controller has been designed using H$\infty$ control theory. The controller eliminates the synchronous error by controlling speed of the second axis. The effectiveness of the proposed method has been verified through simulation.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.56 no.2
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• pp.74-82
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• 2007

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. This paper proposes efficiency optimization control of IPMSM drive using adaptive fuzzy learning control fuzzy neural network (AFLC-FNN) controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The controllable electrical loss which consists of the copper loss and the iron loss can be minimized by the optimal control of the armature current. The minimization of loss is possible to realize efficiency optimization control for the proposed IPMSM. The optimal current can be decided according to the operating speed and the load conditions. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using AFLC-FNN controller. Also, this paper proposes speed control of IPMSM using AFLC-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled AFLC-FNN controller, the operating characteristics controlled by efficiency optimization control are examined in detail.

• Journal of Electrical Engineering and information Science
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• v.3 no.2
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• pp.251-260
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• 1998

A DSP-based robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) which is robust to unknown parameter variations and speed measurement error is presented. The model reference adaptive system(MRAS) based adaptation mechanisms for the estimation of slowly varying parameters are derived using the Lyapunov stability theory. For the disturbances or quickly varying parameters. a quasi-linearized and decoupled model including the influence of parameter variations and speed measurement error on the nonlinear speed control of a PMSM is derived. Based on this model, a boundary layer integral sliding mode controller to improve the robustness and performance of the nonlinear speed control of a PMSM is designed and compared with the conventional controller. To show the validity of the proposed control scheme, simulations and experimental works are carried out and compared with the conventional control scheme.

• The Journal of the Korea institute of electronic communication sciences
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• v.16 no.4
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• pp.699-708
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• 2021

In this paper, a steering control and speed control algorithm was presented for autonomous driving based on two vision sensors and road speed sign board. A car speed control algorithm was developed to recognize the speed sign by using TensorFlow, a deep learning program provided by Google to the road speed sign image provided from vision sensor B, and then let the car follows the recognized speed. At the same time, a steering angle control algorithm that detects lanes by analyzing road images transmitted from vision sensor A in real time, calculates steering angles, controls the front axle through PWM control, and allows the vehicle to track the lane. To verify the effectiveness of the proposed algorithm's steering and speed control algorithms, a car's prototype based on the Python language, Raspberry Pi and OpenCV was made. In addition, accuracy could be confirmed by verifying various scenarios related to steering and speed control on the test produced track.

• The Transactions of the Korean Institute of Electrical Engineers B
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• v.55 no.2
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• pp.89-97
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• 2006

Interior permanent magnet synchronous motor(IPMSM) has become a popular choice in electric vehicle applications, due to their excellent power to weight ratio. The paper is proposed maximum torque control of IPMSM drive using learning mechanism-fuzzy neural network(LM-FNN) controller and artificial neural network(ANN). The control method is applicable over the entire speed range and considered the limits of the inverter's current and voltage rated value. For each control mode, a condition that determines the optimal d-axis current $i_{d}$ for maximum torque operation is derived. This paper considers the design and implementation of novel technique of high performance speed control for IPMSM using LM-FNN controller and ANN controller. The hybrid combination of neural network and fuzzy control will produce a powerful representation flexibility and numerical processing capability. Also, this paper is proposed speed control of IPMSM using LM-FNN and estimation of speed using ANN controller. The back propagation neural network technique is used to provide a real time adaptive estimation of the motor speed. The proposed control algorithm is applied to IPMSM drive system controlled LM-FNN and ANN controller, the operating characteristics controlled by maximum torque control are examined in detail. Also, this paper is proposed the analysis results to verify the effectiveness of the LM-FNN and ANN controller.

• Journal of Power Electronics
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• v.4 no.4
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• pp.217-227
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• 2004

A robust controller that combines the merits of the feed-back, feed-forward and model-following control for induction motor drives utilizing field orientation control is designed in this paper. The proposed controller is a two-degrees-of­freedom (2DOF) integral plus proportional & rate feedback (I-PD) speed controller combined with a model-following (2DOF I-PD MFC) speed controller. A systematic mathematical procedure is derived to find the parameters of the 2DOF I-PD MFC speed controller according to certain specifications for the drive system. Initially, we start with the I-PD feed­back controller design, then we add the feed-forward controller. These two controllers combine to form the 2DOF I-PD speed controller. To realize high dynamic performance for disturbance rejection and set point tracking characterisitics, a MFC controller is designed and added to the 2DOF I-PD controller. This combination is called a 2DOF I-PD MFC speed controller. We then study the effect of the 2DOF I-PD MFC speed controller on the performance of the drive system under different operating conditions. A computer simulation is also run to demonstrate the effectiveness of the proposed controller. The results verify that the proposed 2DOF I-PD MFC controller is more accurate and more reliable in the presence of load disturbance and motor parameter variations than a 2DOF I-PD controller without a MFC. Also, the proposed controller grants rapid and accurate responses to the reference model, regardless of whether a load disturbance is imposed or the induction machine parameters vary.

• Journal of Advanced Marine Engineering and Technology
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• v.23 no.3
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• pp.369-378
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• 1999

This paper presents position control of an electro-hydraulic servo system whoch is operated by four 2-2way high speed on-off valves with either PWM PID control method or sliding mode control method, The advantages of using high speed on-off valves instead of electo-hydraulic servo valves or electro-hydraulic proportional valves are low price robustness for oil contamination and direct control without a D/A converter. The system consists of load cylinder inertia car potentiometer and external load cylinder. The experiments were carried out under several conditions and the results were compared. As a result the sliding mode method has shown good control performance and the robust and stable positioning of the elector-hydraulic servo system can be achieved accurately.