• Title/Summary/Keyword: Nonlinear PD Control

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Development of Experimental Mobile Robots for Robotics Engineering Education by Using LEGO MINDSTORM (이동로봇을 중심으로 LEGO MINDSTORM을 응용한 로봇공학 교육용 실습 로봇개발)

  • Park, June-Hyung;Jung, Seul
    • The Journal of Korea Robotics Society
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    • v.7 no.2
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    • pp.57-64
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    • 2012
  • This paper introduces several mobile robots developed by using LEGO MIDSTORM for experimental studies of robotics engineering education. The first mobile robot is the line tracer robot that tracks a line, which is a prototype of wheel-driven mobile robots. Ultra violet sensors are used to detect and follow the line. The second robot system is a two-wheel balancing robot that is somewhat nonlinear and complex. For the robot to balance, a gyro sensor is used to detect a balancing angle and PD control is used. The last robot system is a combined system of a line tracer and a two-wheel balancing robot. Sensor filtering and control algorithms are tested through experimental studies.

A Design of the Robust Servo Controller for DC Servo-Motor Using Genetic Algorithm (유전알고리즘을 이용한 강인한 DC 서보제어기의 설계)

  • Kim, Dong-Wan;Hwang, Gi-Hyun;Hwang, Hyun-Joon;Nam, Jing-Lak;Park, June-Ho
    • Proceedings of the KIEE Conference
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    • 1999.07b
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    • pp.812-814
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    • 1999
  • In this paper, we are applied the Genetic Algorithm (GA) to design of fuzzy logic controller (FLC) for a DC Servo-Motor Speed Control. GA is used to design of the membership functions and scaling factor of FLC. To evaluate the performances of the proposed FLC, we make an experiment on FLC for the speed control of an actual DC servo-motor system with nonlinear characteristics. Experimental results show that proposed controller have better performance than those of PD controller.

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Controller Design using PreFilter Type Chaotic Neural Networks Compensator (Prefilter 형태의 카오틱 신경망 속도보상기를 이용한 제어기 설계)

  • Choi, Un-Ha;Kim, Sang-Hee
    • Proceedings of the KIEE Conference
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    • 1998.11b
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    • pp.651-653
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    • 1998
  • This thesis propose the prefilter type control strategies using modified chaotic neural networks #or the trajectory control of robotic manipulator. Since the structure of chaotic neural networks and neurons, chaotic neural networks can show the robust characteristics for controlling highly nonlinear dynamics like robotic manipulators. For its application, the trajectory controller of the three-axis PUMA robot is designed by CNN. The CNN controller acts as the compensator of the PD controller. Simulation results show that learning error decrease drastically via on- line learning and the performance is excellent. The CNN controller have much better controllability and shorter calculation time compared to the RNN controller. Another advantage of the proposed controller could be attached to conventional robot controller without hardware changes.

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Steering Control of Unmaned Container Transporter Using MRAC (MRAC 기법을 이용한 무인 컨테이너 운송차량의 조향 제어)

  • Lee, Y.J.;Huh, N.;Choi, J.Y.;Lee, K.S.;Lee, M.H.
    • Journal of Korean Port Research
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    • v.14 no.3
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    • pp.291-301
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    • 2000
  • T his paper presents the lateral and longitudinal control algorithm for the driving of a 4WS AGV(Automated Guided Vehicle). The control law to the lateral and longitudinal control of the AGV includes adaptive agin tuning ability, that is the controller gain of the gravity compensated PD controller can be changed on a real-time. The gain tuning law is derived from the Lyapunov direct method using the output error of the reference model and the actual model, And to show the performance of the presented lateral and longitudinal control algorithm, we simulate toe nonlinear AGV equations of the motion by deriving the Newton-Euler Method, The read path is from quay yard area to docking position in loading yard area. The quay yard area is where the quay crane loads the container to the AGV and the docking position is where the container is transferred to the gantry crane. The road types are constructed in a straight line and J-turn. When driving the straight line, the driving velocity is 6㎧ and the J-turn is 3㎧.

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Linearized Modeling and Variable Position Control of Magnetic Levitator Using DSP (선형화 기법을 사용한 자기부유기 모델링과 DSP기반 가변 위치 제어)

  • 김정재;송승호
    • The Transactions of the Korean Institute of Power Electronics
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    • v.9 no.2
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    • pp.158-162
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    • 2004
  • The magnetic levitator is the device which can float a magnetic material at the midair by electromagnetic force and it's principle can be applied to the high speed magnetic bearing or magnetic levitation train. There are many difficulties to control, because the magnetic levitator is basically a nonlinear and unstable system. In this paper, this system is modeled assuming that it is a linear system nearby an operating point, and a proportional and derivative(PD) position controller is designed to carry out the variable position control. The performance of position control response is shown through simulation and experiment. A prototype magnetic levitator is constructed using PWM converter and DSP(Digital Signal Processor) based control board.

Unscented Kalman Filtering for Spacecraft Attitude and Rate Determination Using Magnetometer

  • Kim, Sung-Woo;Park, Sang-Young;Abdelrahman, Mohammad;Choi, Kyu-Hong
    • Bulletin of the Korean Space Science Society
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    • 2008.10a
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    • pp.36.1-36.1
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    • 2008
  • An Unscented Kalman Filter(UKF) for estimation of attitude and rate of a spacecraft using only magnetometer vector measurement is presented. The dynamics used in the filter is nonlinear rotational equation which is augmented by the quaternion kinematics to construct a process model. The filter is designed for low Earth orbit satellite, so the disturbance torques include gravity-gradient torque, magnetic disturbance torque, and aerodynamic drag. The magnetometer measurements are simulated based on time-varying position of the spacecraft. The filter has been tested not only in the standby mode but also in the detumbling mode. To stabilize the attitude, linear PD controller is applied and the actuator is assumed to be thruster. A Monte-Carlo simulation has been done to guarantee the stability of the filter performance to the various initial conditions. The UKF performance is compared to that of EKF and it reveals that UKF outperforms EKF.

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Improvement in the Position and Speed Control of a Dc-Servo Motor Using Back Propagation Method (역전달 학습법(BP)을 이용한 직류 서보 전동기의 위치및 속도 제어 특성개선)

  • Kim, Cheol-Am;Lee, Eun-Chul;Kim, Soo-Hyun;Kim, Nak-Kyo;Nam, Moon-Hyun
    • Proceedings of the KIEE Conference
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    • 1992.07a
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    • pp.242-244
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    • 1992
  • Conventionally in the industrial control, PlD controller has been used because of its robustness, and nonlinear characteristic of a system under control. Although the PlD controller produce suitable parameter of the each system and also variable of PlD controller should be changed according to environment, disturbance, load. In this paper, the convergence and learning accuracy of the back-propagation(BP) method in neural network are investigated by analyzing the reason for decelerating the convergence of BP method. and examining the rapid deceleration of the convergence when the learning is executed on the part of sigmoid activation function with the very small first derivative. The modified logistic activation function it proposed by defining the convergence factor based on the analysis and applied to the position and speed control of a DC-servo motor. This paper revealed for experimental, a neural network and a PD controller combined off-line system using developed the position and speed characteristics of a DC-servo motor.

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Robust Adaptive Sliding Mode Controller for PMSM Servo Drives System (강인 적응성 슬라이딩을 이용한 PMSM 서보드라이브 시스템 제어기)

  • Park, Ki-Kwang;Han, Byung-Jo;Kim, Hong-Pil;Yang, Hai-Won
    • Proceedings of the KIEE Conference
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    • 2009.07a
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    • pp.1640_1641
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    • 2009
  • Dynamic friction and force ripple are the most predominant factors that affect the positioning accuracy of permanent magnet synchronous motor(PMSM) servo drives system, and it is desirable to compensate them in finite time with a continuous control law. In this paper, based on LuGre dynamic friction model, a robust adaptive skidding mode controller is proposed to compensate the nonlinear effect of friction and force ripple. The controller scheme consists of a PD component and a robust adaptive sliding mode controller for estimating the unknown system parameter. Using Lyapunov stability theorem, asymptotic stability analysis and position tracking performance are guaranteed. Simulation results well verify the feasibility and the effectiveness of the proposed scheme for high0precision motion trajectory tracking.

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Unscented KALMAN Filtering for Spacecraft Attitude and Rate Determination Using Magnetometer

  • Kim, Sung-Woo;Abdelrahman, Mohammad;Park, Sang-Young;Choi, Kyu-Hong
    • Journal of Astronomy and Space Sciences
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    • v.26 no.1
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    • pp.31-46
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    • 2009
  • An Unscented Kalman Filter (UKF) for estimation of the attitude and rate of a spacecraft using only magnetometer vector measurement is developed. The attitude dynamics used in the estimation is the nonlinear Euler's rotational equation which is augmented with the quaternion kinematics to construct a process model. The filter is designed for small satellite in low Earth orbit, so the disturbance torques include gravity-gradient torque, magnetic disturbance torque, and aerodynamic drag torque. The magnetometer measurements are simulated based on time-varying position of the spacecraft. The filter has been tested not only in the standby mode but also in the detumbling mode. Two types of actuators have been modeled and applied in the simulation. The PD controller is used for the two types of actuators (reaction wheels and thrusters) to detumble the spacecraft. The estimation error converged to within 5 deg for attitude and 0.1 deg/s for rate respectively when the two types of actuators were used. A joint state parameter estimation has been tested and the effect of the process noise covariance on the parameter estimation has been indicated. Also, Monte-Carlo simulations have been performed to test the capability of the filter to converge with the initial conditions sampled from a uniform distribution. Finally, the UKF performance has been compared to that of the EKF and it demonstrates that UKF slightly outperforms EKF. The developed algorithm can be applied to any type of small satellites that are actuated by magnetic torquers, reaction wheels or thrusters with a capability of magnetometer vector measurements for attitude and rate estimation.

Design of a Fuzzy Logic Controller Using an Adaptive Evolutionary Algorithm for DC Series Motors (적응진화 알고리즘을 사용한 DC 모터 퍼지 제어기 설계에 관한 연구)

  • Kim, Dong-Wan;Hwang, Gi-Hyun;Lee, Jae-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.11 no.5
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    • pp.1019-1028
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    • 2007
  • In this paper, adaptive evolutionary algorithm(AEA) is proposed, which uses both genetic algorithm(GA) with good global search capability and evolution strategy(ES) with good local search capability in an adaptive manner, when population evolves to the next generation. In the reproduction procedure, proportion of the population for GA and ES is adaptively determined according to their fitness. The AEA is used to design membership functions and scaling factors of the fuzzy logic controller(FLC). To evaluate the performance of the proposed FLC design method, we make an experiment on the FLC for the speed control of an actual DC series motor system with nonlinear characteristics. Experimental results show that the proposed controller has better performance than PD controller.