• Title/Summary/Keyword: Decoupled PD Control

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Decoupled Neural Network Reference Compensation Technique for a PD Controlled Two Degrees-of-Freedom Inverted Pendulum

  • Seul Jung;Cho, Hyun-Taek
    • International Journal of Control, Automation, and Systems
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    • v.2 no.1
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    • pp.92-99
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    • 2004
  • In this paper, the decoupled neural network reference compensation technique (DRCT) is applied to the control of a two degrees-of-freedom inverted pendulum mounted on an x-y table. Neural networks are used as auxiliary controllers for both the x axis and y axis of the PD controlled inverted pendulum. The DRCT method known to compensate for uncertainties at the trajectory level is used to control both the angle of a pendulum and the position of a cart simultaneously. Implementation of an on-line neural network learning algorithm has been implemented on the DSP board of the dSpace DSP system. Experimental studies have shown successful balancing of a pendulum on an x-y plane and good position control under external disturbances as well.

Decoupled Controller Design of an Autonomous Underwater Vehicle and Performance Test Results (수중운동체에 대한 비연성 제어기 설계 및 성능 평가)

  • Hyun, Chul
    • Journal of Institute of Control, Robotics and Systems
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    • v.19 no.9
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    • pp.768-773
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    • 2013
  • In this paper, decoupled course, depth and roll controller design for an Autonomous Underwater Vehicle (AUV) and its performance test results are presented. Control system design is done using the PD control scheme based on a mathematical model of the AUV. Details of system implementation are given and the results of simulations and experiments using the prototype vehicle model are discussed. The designed controller was successfully applied to the nonlinear and coupled system under non-ideal actuator conditions.

Fuzzy Neural Network Active Disturbance Rejection Control for Two-Wheeled Self-Balanced Robot

  • Wang, Chao;Jianliang, Xiao;Zhang, Cheng
    • Journal of Information Processing Systems
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    • v.18 no.4
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    • pp.510-523
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    • 2022
  • Considering the problems of poor control effect, weak disturbance rejection ability and adaptive ability of two-wheeled self-balanced robot (TWSBR) systems on undulating roads, this paper proposes a fuzzy neural network active disturbance rejection controller (FNNADRC), that is based on fuzzy neural network (FNN) for online correction of active disturbance rejection controller (ADRC)'s nonlinear control rate. Firstly, the dynamic model of the TWSBR is established and decoupled, the extended state observer (ESO) is used to compensate dynamically and linearize the upright and displacement subsystems. Then, the nonlinear PD control rate and FNN are designed, and the FNN is used to modify the control parameters of the nonlinear PD control rate in real time. Finally, the proposed control strategy is simulated and compared with the traditional ADRC and fuzzy active disturbance rejection controller (FADRC). The simulation results show that the control effect of the proposed control strategy is slightly better than ADRC and FADRC.

Decoupled Control of Active and Permanent Magnetic Bearing System (자기 베어링과 영구자석 베어링으로 이루어진 시스템의 비 연성 제어)

  • Park, Sang-Hyun;Lee, Chong-Won
    • Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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    • 2008.04a
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    • pp.63-70
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    • 2008
  • In this paper, we propose a bearing redundant coordinates and decoupled PD controller for 5-axes active magnetic bearing system, which consists of two bearing parts such as three-pole hybrid active magnetic bearing for stabilize the radial direction and ring-type permanent magnetic bearing stabilizing in axial and tilting motion. Based on derived system equation with decoupled control scheme, we conduct the modal analysis and measure of modal controllability and observability.

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Decoupled Controller Design of Small Autonomous Underwater Vehicle and Performance Test using HILS (소형 자율 수중 운동체의 비연성 제어기 설계 및 HILS 기법을 이용한 성능 평가)

  • Chul, Hyun
    • Journal of the Korea Institute of Military Science and Technology
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    • v.16 no.2
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    • pp.130-137
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    • 2013
  • In this paper, decoupled controller design for Autonomous Underwater Vehicle(AUV) and its simulated performance test results and Hardware In the Loop Simulation(HILS) results are presented. Control system design is done using the PD control scheme. Stability analysis and step response of closed loop system under uncertain parameter condition are also presented. The results of full coupled nonlinear model simulation show the well applicability of the designed controller. From the results of HILS, we can verify performance of real time processing and implemented hardware for AUV.

Nonlinear Adaptive Control of Unmanned Helicopter Using Neural Networks Compensator (신경회로망 보상기를 이용한 무인헬리콥터의 비선형적응제어)

  • Park, Bum-Jin;Hong, Chang-Ho
    • Journal of the Korean Society for Aeronautical & Space Sciences
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    • v.38 no.4
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    • pp.335-341
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    • 2010
  • To improve the performance of inner loop based on PD controller for a unmanned helicopter, neural networks are applied. The performance of PD controller designed on the response characteristics of error dynamics decreases because of uncertain nonlinearities of the system. The nonlinearities are decoupled to modified dynamic inversion model(MDIM) and are compensated by the neural networks. For the training of the neural networks, online weight adaptation laws which are derived from Lyapunov's direct method are used to guarantee the stability of the controller. The results of the improved performance of PD controller by neural networks are illustrated in the simulation of unmanned helicopter with nonlinearities,

A Study on the Static Levitation Control of Magnetic Bearing using Optical Fiber Displacement Sensors (광파이버 변위 센서를 적용한 자기베어링 정적 부상 제어 연구)

  • 강종규;신우철;홍준희
    • Proceedings of the Korean Society of Machine Tool Engineers Conference
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    • 2003.10a
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    • pp.131-136
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    • 2003
  • Five expensive sensors are necessary to control a magnetic bearing system. The sensor price rate of magnetic bearing system is high. So it is necessary that cheap and good sensor is developed. The optical fiber displacement sensor is adaptive to satisfy this condition. We can design magnetically suspended spindle based on static characteristic of optical fiber displacement sensor developed. The controller can be designed by decoupled feedback PD. Therefore, it is simpler than any other controller comparatively.

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Design and DSP-based Implementation of Robust Nonlinear Speed Control of Permanent Magnet Synchronous Motor (영구자석 동기전동기의 강인 비선형 속도제어기의 설계 및 DSP에 기반한 구현)

  • 백인철;김경화;윤명중
    • The Transactions of the Korean Institute of Power Electronics
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    • v.4 no.1
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    • pp.1-12
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    • 1999
  • A design and DSP-based implementation of robust nonlinear speed control of a permanent magnet synchronous motor(PMSM) under the 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 MIT rule. For the disturbances or quickly varying parameters, a quasilinearized and decoupled model which includes 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 which employs Proportional plus Derivative(PD) control. To show the validity of the proposed scheme, simulations and DSP-based experimental works are carried out and compared with the conventional control scheme.

Modeling and Control of Cone-Shaped Active Magnetic Bearing System (원추형 능동 자기베어링계의 모형화 및 제어)

  • 정호섭;김철순;이종원
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.17 no.12
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    • pp.3073-3082
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    • 1993
  • A magnetically suspended robot joint is developed, which is free of dust and oil generation. Two radial bearings consisting of cone-shaped magnet cores control the rotor motion in the axial and radial directions. A linearized dynamic model is developed for active control of the magnetic bearing system. The control algorithm is constructed such that the axial displacement of the joint is controlled by radial control current to the pairs of facing radial bearings. The stability and control performance is tested through numerical simulation based on the nonlinear model. Experiments are also performed to verify the theoretical development.

Robust Control of Flexible Joint Robot Using ISMC and IDA-PBC (ISMC와 IDA-PBC를 이용한 유연관절로봇의 강인제어)

  • Asignacion, Abner Jr.;Park, Seung-kyu;Lee, Min-wook
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.21 no.6
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    • pp.1203-1211
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    • 2017
  • This paper proposes a robust controller for flexible joint robots to achieve tracking performance and to improve robustness against both matched and mismatched disturbances. The proposed controller consists of a disturbance observer(DOB), passivity-based controller, and integral sliding mode controller(ISMC) in a backstepping manner. The DOB compensates the mismatched disturbance in the link-side and formulates the reference input for the motor-side controller. Interconnection and damping assignment passivity-based controller (IDA-PBC) performs tracking control of motor-side, and it is integrated to nominal control of ISMC to guarantee the over-all stability of the nominal system, while, matched disturbances are decoupled by the discontinuous control of ISMC. In the design of the link-side controller, PD type impedance controller is designed with DOB and this leads the continuous control input which is suitable to the reference input for the motor-side.