• Title/Summary/Keyword: Steering PID control

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A Study on the Design and Control Method for Unmanned Ground Vehicle System (무인 자율 주행 차량 시스템 설계 및 제어에 관한 연구)

  • Moon, Hee-Chang;Park, Myung-Wook;Kim, Jung-Ha
    • Journal of Institute of Control, Robotics and Systems
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    • v.16 no.5
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    • pp.446-455
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    • 2010
  • The research presented covers the design and control method of unmanned ground vehicle (UGV). An electric vehicle is used and is driven by DC motor. The power system on the UGV has been adjusted and actuators have been installed for steering and brake automation. A toggle switch is implemented to easily switch between manual and autonomous states. The UGV state is monitored by a velocity sensor, as well as steering and brake position sensors. An emergency stop device was designed and installed to quickly and safely stop the UGV. Different control methods, including the PID controller, were studied for improved steering responsiveness, and results were confirmed through experimentation. Satisfactory performance was achieved and several possible areas of future research have arisen.

Development of New Numerical Model and Controller of AFS System (AFS 시스템의 새로운 수학적 모델 및 제어기 개발)

  • Song, Jeonghoon
    • Transactions of the Korean Society of Automotive Engineers
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    • v.22 no.6
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    • pp.59-67
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    • 2014
  • A numerical model and a controller of Active Front wheel Steer (AFS) system are designed in this study. The AFS model consists of four sub models, and the AFS controller uses sliding mode control and PID control methods. To test this model and controller an Integrated Dynamics Control with Steering (IDCS) system is also designed. The IDCS system integrates an AFS system and an ARS (Active Rear wheel Steering) system. The AFS controller and IDCS controller are compared under several driving and road conditions. An 8 degree of freedom vehicle model is also employed to test the controllers. The results show that the model of AFS system shows good kinematic steering assistance function. Steering ratio varies depends on vehicle velocity between 12 and 24. Kinematic stabilization function also shows good performance because yaw rate of AFS vehicle tracks the reference yaw rate. IDCS shows improved responses compared to AFS because body side slip angle is also reduced. This result also proves that AFS system shows satisfactory result when it is integrated with another chassis system. On a split-m road, two controllers forced the vehicle to proceed straight ahead.

Development of a Prototype of Guidance System for Rice-transplanter

  • Zhang, Fang-Ming;Shin, Beom-Soo;Feng, Xi-Ming;Li, Yuan;Shou, Ru-Jiang
    • Journal of Biosystems Engineering
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    • v.38 no.4
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    • pp.255-263
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    • 2013
  • Purpose: It is not easy to drive a rice-transplanter avoiding underlapped or overlapped transplanting in paddy fields. An automated guidance system for the riding-type rice-transplanter would be necessary to operate the rice-transplanter autonomously or to assist the beginning drivers as a driving aid. Methods: A prototype of guidance system was composed of embedded computers, RTK-GPS, and a power-steering mechanism. Two Kalman filters were adopted to overcome sparse positioning data (1 Hz) from the RTK-GPS. A global Kalman filter estimated the posture of rice-transplanter every one second, and a local Kalman filter calculated the posture from every new estimation of the global Kalman filter with an interval of 200 ms. A PID controller was applied to the row-following mode control. A control method of U-turning mode was developed as well. A stepping motor with a reduction gear set was used to rotate the shaft of steering wheel. Results: Test trials for U-turning and row-following modes were done in a paddy field after some parameters have been tuned at the ground speed range of 0.3 ~ 1.2 m/s. The minimum RMS error of offset was 3.13 cm at the ground speed of 0.3 m/s while the maximum RMS error was 13.01 cm at 1.2 m/s. The offset RMS error tended to increase as the ground speed increased. The target point distance, LT also affected the system performance and PID controller parameters should be adjusted on different ground speeds. Conclusions: A target angle-based PID controller plus stationary steering angle controller made it possible for the rice-transplanter to steer autonomously by following a reference line accurately and even on U-turning mode. However, as condition in paddy fields is very complicated, the system should control the ground speed that prevents it from deviating too much due to ditch and slope.

A Study on Driving Control of an Autonomous Guided Vehicle Using Humoral Immune Algorithm(HIA) Adaptive Controller (생체면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, K.S.;Suh, J.H.;Lee, Y.J.
    • Journal of Power System Engineering
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    • v.9 no.4
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    • pp.194-201
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    • 2005
  • In this paper, we propose an adaptive mechanism based on humoral immune algorithm and neural network identifier technique. It is also applied for an autonomous guided vehicle (AGV) system. When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged due to the abrupt change of PID parameters since the parameters are almost adjusted randomly. To slove this problem, we use the neural network identifier technique for modeling the plant humoral immune algorithm (HIA) which performs the parameter tuning of the considered model, respectively. Finally, the experimental results for control of steering and speed of AGV system illustrate the validity of the proposed control scheme. Also, these results for the proposed method show that it has better performance than other conventional controller design method such as PID controller.

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A Study on Implementation of Immune Algorithm Adaptive Controller for AGV Driving Control (AGV의 주행 제어를 위한 면역 알고리즘 적응 제어기 실현에 관한 연구)

  • 이영진;이진우;손주한;이권순
    • Journal of Korean Port Research
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    • v.14 no.2
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    • pp.187-197
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    • 2000
  • In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied to the driving control of the autonomous guided vehicle(AGV). When the immune algorithm is applied to the PID controller, there exists the case that the plant is damaged by the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined through this off-line manner, these parameters are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough initially, the weighting parameters are adjusted more accurately through the on-line fine tuning. The experiment for the control of steering and speed of AGV is performed. The results show that the proposed controller provides better performances than other conventional controllers.

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A Fuzzy PID Control of Nonholonomic Mobile Robot (Nonholonomic 모바일 로봇의 퍼지 PID제어)

  • Kim, Do-Won;Yang, Hai-Won;Jung, Won-Chul;Hwang, Yong-Ho;Kim, Hong-Phil
    • Proceedings of the KIEE Conference
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    • 2000.07d
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    • pp.2756-2759
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    • 2000
  • In this paper. A PID motion controller based on the fuzzy concept is discussed for nonholonomic mobile robot. The difficulties in controlling such a Mobile robot vehicle lies in the fact that it usually has only two degrees of freedom for motion control in a tracking mode. It makes the control of speed and steering possible to decompose the error between the reference posture and the current posture. The Gyro compass is used to measure the position of robot. The proposed nonholonomic mobile robot is shown to follow the reference trajectory and compensate the dynamics. Simulation results are provided to validate the proposed controller. Experiments have been used to verify the effectiveness and robustness of the motion controller.

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A Study of the Control System on the Manta-type UUV (만타형 UUV의 제어기 설계에 관한 연구)

  • Kim, Hyeong-Dong;Kim, Joon-Young;Kim, Si-Hong;Lee, Seung-Keon
    • Journal of Navigation and Port Research
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    • v.35 no.5
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    • pp.359-363
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    • 2011
  • In this paper, automatic control system for the Manta UUV are constructed for the diving and steering maneuver. PID controller and Fuzzy controller are adopted in this system. Based on the 6DOF dynamic equation, simulation program has been developed using the Matlab. Using this program, depth control system and heading control system with tidal current are evaluated.

An AGV Driving Control using immune Algorithm Adaptive Controller (면역알고리즘 적응 제어기를 이용한 AGV 주행제어에 관한 연구)

  • Lee, Yeong-Jin;Lee, Gwon-Sun;Lee, Jang-Myeong
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.4
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    • pp.201-212
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    • 2000
  • In this paper, an adaptive mechanism based on immune algorithm is designed and it is applied for the autonomous guided vehicle(AGV) driving. When the immune algorithm is applied to the PID controller, there exists the cast that the plant is damaged due to the abrupt change of PID parameters since the parameters are adjusted almost randomly. To solve this problem, a neural network is used to model the plant and the parameter tuning of the model is performed by the immune algorithm. After the PID parameters are determined in this off-line manner, these gains are then applied to the plant for the on-line control using immune adaptive algorithm. Moreover, even though the neural network model may not be accurate enough intially, the weighting parameters are adjusted to be accurate through the on-line fine tuning. The computer simulation for the control of steering and speed of AGV is performed. The results show that the proposed controller has better performances than other conventional controllers.

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A Study for AGV Steering Control using Evolution Strategy (진화전략 알고리즘을 이용한 AGV 조향제어에 관한 연구)

  • 이진우;손주한;최성욱;이영진;이권순
    • 제어로봇시스템학회:학술대회논문집
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    • 2000.10a
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    • pp.149-149
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    • 2000
  • We experimented on AGV driving test with color CCD camera which is setup on it. This paper can be divided into two parts. One is image processing part to measure the condition of the guideline and AGV. The other is part that obtains the reference steering angle through using the image processing parts. First, 2 dimension image information derived from vision sensor is interpreted to the 3 dimension information by the angle and position of the CCD camera. Through these processes, AGV knows the driving conditions of AGV. After then using of those information, AGV calculates the reference steering angle changed by the speed of AGV. In the case of low speed, it focuses on the left/right error values of the guide line. As increasing of the speed of AGV, it focuses on the slop of guide line. Lastly, we are to model the above descriptions as the type of PID controller and regulate the coefficient value of it the speed of AGV.

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The linear model analysis and Fuzzy controller design of the ship using the Nomoto model (Nomoto모델을 이용한 선박의 선형 모델 분석 및 퍼지제어기 설계)

  • Lim, Dae-Yeong;Kim, Young-Chul;Chong, Kil-To
    • Journal of the Korea Academia-Industrial cooperation Society
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    • v.12 no.2
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    • pp.821-828
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    • 2011
  • This paper developed the algorithm for improving the performance the auto pilot in the autonomous vehicle system consisting of the Track keeping control, the Automatic steering, and the Automatic mooring control. The automatic steering is the control device that could save the voyage distance and cost of fuel by reducing the unnecessary burden of driving due to the continuous artificial navigation, and avoiding the route deviation. During the step of the ship autonomic navigation control, since the wind power or the tidal force could make the ship deviate from the fixed course, the automatic steering calculates the difference between actual sailing line and the set course to keep the ship sailing in the vicinity of intended course. first, we could get the transfer function for the modeling of ship according to the Nomoto model. Considering the maneuverability, we propose it as linear model with only 4 degree of freedoms to present the heading angle response to the input of rudder angle. In this paper, the model of ship is derived from the simplified Nomoto model. Since the proposed model considers the maximum angle and rudder rate of the ship auto pilot and also designs the Fuzzy controller based on existing PID controller, the performance of the steering machine is well improved.