• Journal of the Institute of Convergence Signal Processing
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• v.8 no.2
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• pp.119-123
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• 2007

This paper investigates a speed sensorless control of induction motor. The control strategy is based on MRAS(Model Reference Adaptive System) using load-torque observer as a reference model for flux estimation. The speed response of conventional MRAS controller characteristics is affected by variations of load torque disturbance. In the proposed system, the speed control characteristics using a load-torque observer control isn't affected by a load torque disturbance. Control algorithm that propose whole system through MATLAB SIMULINK because do modelling simulation result are presented to prove the effectiveness of the adaptive sliding mode controller for the drive variable load of induction motor. Therefore we hope to be extended in industrial application.

• Journal of Advanced Navigation Technology
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• v.24 no.2
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• pp.101-106
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• 2020

In order to smoothly control the speed of the induction motor, it is necessary to obtain the required rotor speed information. In order to obtain the speed information, it must be obtained using a sensor, but it can also be obtained using an appropriate algorithm without using a sensor. In order to obtain speed information, a system was designed using a model reference adaptive system (MARS). Indirect vector control, one of the speed control methods of induction motors, was calculated from the motor current and rotor parameter values. The method of obtaining the position information of the magnetic flux by combining the slip frequency with the rotor speed was used. It is possible to simply perform instantaneous current control in a wide speed range without actual magnetic flux information, and has the advantage that the structure of the controller is simple. Therefore, in this paper, the control system was constructed based on the indirect vector control method, and the speed control system of the induction motor was developed by estimating the required rotor speed information as an intelligent algorithm developed without using it as a sensor.

• Journal of the Korean Institute of Intelligent Systems
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• v.22 no.1
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• pp.36-41
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• 2012

This paper presents torque control of DC motor using the velocity profile based acceleration/deceleration controller for automatic guided vehicles (AGVs). This technique has some advantage; to reduce the damage of motors and to extend the life time of motors. First, we generate velocity profiles for three cases and design the state feedback controller using the generated velocity profile as a reference. The state feedback controller has servo system for solving regulation problem. For the verification, we apply the proposed method to control a cart position and shows some simulation result.

• Proceedings of the KIEE Conference
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• 2015.07a
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• pp.966-967
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• 2015

본 논문은 BLDC 팬모터의 속도제어 선형성(linearity)에 관한 것이다. PWM으로 모터의 속도를 제어할 때에 입력 duty cycle이 증가함에 따라 모터 속도가 선형적으로 증가하지 않는 문제가 발생한다. 모터를 구동하는 드라이브 IC의 출력 PWM duty cycle을 속도제어의 입력값에 해당하는 입력 PWM duty cycle과 비선형적으로 출력함으로써, 모터 속도의 입력 PWM duty cycle에 대해 선형성을 향상시켰다. 또한, 비휘발성 메모리에 설정값을 저장하여 선형성 정도를 조절가능하도록 하였다. 0.35um CMOS 공정으로 단상 BLDC 모터 드라이브 IC를 설계 및 제작하고, 모터 샘플을 이용하여 PWM 입력 duty cycle과 모터 속도와의 선형성 정도를 측정하였다.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2022.11a
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• pp.187-187
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• 2022

최근 선박의 자율운항기술이 활발하게 연구되어 오면서, 경로추종 제어 및 충돌회피 등의 자율운항 기술 연구가 많이 진행되고 있으며 그에 따른 시뮬레이션과 실해역 시험 등도 활발하게 수행되고 있다. 이러한 자율운항기술 중 본 연구에서는 AUV(Autonomous Underwater Vehicle) 진회수 시 모함에 활용되며 쌍동선형을 갖는 쌍동형 무인수상선을 대상으로 경로추종 제어에 대한 실해역 시험을 수행한 내용을 소개한다. 대상선인 쌍동형 무인수상선은 배수량이 약 10ton, 최대속도 10knots를 기준으로 설계된 선형이며 Sail drive 타입의 쌍축 추진기를 탑재하고 있으며 Fig. 1에 나타내었다. 실해역 시험은 경기도 화성시에 위치한 제부마리나 전면 해역에서 여러 속도에 대해 Fig. 2의 경로(빨간색)를 활용하여 수행되었다. 해당 경로는 변침각이 45도까지 이루어져 있다. 경로추종 제어 알고리즘은 목표경유점을 향하기 위해 선수각을 제어하는 부분과 목표속도로 추진하기 위해 속도를 제어하는 부분으로 나뉘어져 있다. 선수각 제어 시 경로와 무인선과의 위치 오차를 줄이는 방향으로 선수각이 향할 수 있도록 알고리즘이 설계되었다. 속도 제어의 경우 RPM 별로 실제 속도를 계측하여 데이터화 한 후, 실제 속도가 명령 속도와 다를 경우 RPM을 가감하여 명령 속도로 추진하기 위해 제어할 수 있도록 하였다. Fig. 2에서 파란색 선은 설계한 알고리즘을 활용하여 경로추종 제어를 한 결과의 궤적을 보여준다.

• The Transactions of the Korean Institute of Power Electronics
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• v.9 no.3
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• pp.253-259
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• 2004

This paper presents a speed controller method based on the disturbance torque observer for high-performance speed control of the brushless DC (RLDC) motor. In case of the speed control of robot arms and tracking applications with lower stiffness, we cannot design the speed controller gain to be very large from the viewpoint of the system stability Thus, the feedforward compensation method using disturbance torque observer was proposed. This method can improve the speed characteristic without increasing the speed controller gain. The speed characteristic against disturbance torque can be improved when the bandwidth of the speed controller cannot be made large enough. Consequently, the speed control of the BLDC motor for the high-performance application become achieved.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.4
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• pp.886-890
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• 2011

Induction motors are relatively cheap and rugged machines. For the vector control of induction motors, a position or speed sensor is needed. But a speed sensor increases motor cost and reduces reliability in harsh environment. Recently, many studies have been performed for sensorless speed control. This paper investigates an improved flux observer with the parameter error compensation for a sensorless induction motor. The proposed algorithm is verified through simulation and experiment.

• 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.

• Proceedings of the KIEE Conference
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• 2011.07a
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• pp.27-28
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• 2011

본 논문에서는 싱글전류센서를 이용하여 브러시리스 직류 전동기의 속도제어시스템 시뮬레이션 방법 및 그 결과을 제시한다. BLDC 전동기 제어에 매우 중요한 역할을 가지고 있는 피드백 센서 방식으로 싱글 전류검출센서를 이용한 속도제어 방법은 모터 설계의 비용을 낮추고, 심플한 제어기 설계를 가능하게 한다. 또한, 전동기에 손상을 줄 수 있는 오류조건을 감지함으로서 신뢰성을 향상시켜 줄 수 있다. 시뮬레이션에 사용하는 BLDC 전동기는 3상 Y결선 전동기를 모델로 하며 MATLAB/SIMULINK를 사용한 시뮬레이션을 수행하여 그 성능을 분석하였다.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.15 no.9
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• pp.1871-1880
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• 2011

In this paper, a controller for two wheeled inverted pendulum robot, i.e., Segway type robot that is a convenient and easily handled vehicle is designed to have more stable balancing and faster velocity control compared to the conventional method. First, a widely used PID control structure is applied to the two wheeled inverted pendulum robot and proper PID control gains for some specified weights of users are obtained to get accurate balancing and velocity control by use of experimental trial-and-error method. Next, neural network is employed to generate appropriate PID control gains for arbitrarily selected weight. Here the PID gains based on the trial-and-error method are used as training data. Simulation study has been carried out to find that the performance of the designed controller using the neural network is more excellent than the conventional PID controller in terms of faster balancing and velocity control.