• Title/Summary/Keyword: LQR Controller

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A Learning Method of LQR Controller Using Jacobian (자코비안을 이용한 LQR 제어기 학습법)

  • Lim, Yoon-Kyu;Chung, Byeong-Mook
    • Journal of the Korean Society for Precision Engineering
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    • v.22 no.8 s.173
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    • pp.34-41
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    • 2005
  • Generally, it is not easy to get a suitable controller for multi variable systems. If the modeling equation of the system can be found, it is possible to get LQR control as an optimal solution. This paper suggests an LQR learning method to design LQR controller without the modeling equation. The proposed algorithm uses the same cost function with error and input energy as LQR is used, and the LQR controller is trained to reduce the function. In this training process, the Jacobian matrix that informs the converging direction of the controller Is used. Jacobian means the relationship of output variations for input variations and can be approximately found by the simple experiments. In the simulations of a hydrofoil catamaran with multi variables, it can be confirmed that the training of LQR controller is possible by using the approximate Jacobian matrix instead of the modeling equation and this controller is not worse than the traditional LQR controller.

An LQR Controller for Autonomous Underwater Vehicle (무인잠수정의 LQR 제어기 설계)

  • Bae, Seol B.;Shin, Dong H.;Kwon, Soon T.;Joo, Moon G.
    • Journal of Institute of Control, Robotics and Systems
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    • v.20 no.2
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    • pp.132-137
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    • 2014
  • In this paper, An LQR controller is proposed for way-point tracking of AUV (Autonomous Underwater Vehicle). The LQR controller aims at tracking a series of way-points which operator registers arbitrarily in advance. It consists of a depth controller and a steering controller and AUV's surge speed is assumed varying to consider the dynamic environment of the underwater. In order to show the performance, a conventional state feedback controller is compared with the proposed controller by the simulation using Matlab/Simulink. The parameters of AUV developed by the author's laboratory are used. In the simulation, we verify that the LQR controller can track all the way-points within 1 m error range under the varying surge speed, which proves the robustness of the LQR controller.

Active Vibration Control Using Saturated LQR Controller (포화 LQR 제어기를 이용한 능동 진동 제어)

  • Lim, Chae-Wook
    • Transactions of the Korean Society for Noise and Vibration Engineering
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    • v.18 no.11
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    • pp.1105-1110
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    • 2008
  • In this paper, a saturated LQR controller considering control input's saturation for stable linear time-invariant systems with single control input is studied. Based on Lyapunov stability, two linear matrix inequality sufficient existence conditions for this controller are presented. Through numerical simulations for 2DOF vibrating system, it is confirmed that the saturated LQR controller is stable in the presence of control input's saturation and it is also shown that this controller can be applied to vibrating system practically.

A controller comprising tail wing control of a hybrid autonomous underwater vehicle for use as an underwater glider

  • Joo, Moon G.
    • International Journal of Naval Architecture and Ocean Engineering
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    • v.11 no.2
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    • pp.865-874
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    • 2019
  • A controller for an underwater glider is presented. Considered underwater glider is a torpedo-shaped autonomous underwater vehicle installing adjustable buoyancy bag and movable battery in it. The controller is composed of an LQR controller to maintain zigzag vertical movement for gliding and two PD controllers to control elevator/rudder angles. The LQR controller controls the pumping speed into the buoyancy bag and the moving speed to locate the battery. One of the PD controller controls the elevator angle to assist the LQR controller, and the other controls the rudder angle to adjust the direction of the underwater glider. A reduced order Luenberger observer is adopted to estimates the center of gravity of the glider and the buoyancy mass that are essential but cannot be measured. Mathematical simulation using Matlab proved the validity of the proposed controller to obtain better performance than conventional LQR only controller under the influence of sea current.

Design of an LQR Controller Considering Pole's Moving-Range (근의 이동범위를 고려한 LQR 제어기 설계)

  • Park, Min-Ho;Hong, Suk-Kyo;Lee, Sang-Hyuk
    • Journal of Institute of Control, Robotics and Systems
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    • v.11 no.10
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    • pp.864-869
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    • 2005
  • This paper proposes a new method for LQR controller design. It is unsystematic and difficult to design an LQR controller by trial and error. The proposed method is capable of systematically calculating weighting matrices for desired pole(s) by the pole's moving-range in S-plane and the relational equation between closed-loop pole(s) and weighting matrices. This will provide much-needed functionality to apply LQR controller. The example shows the feasibility of the proposed method.

Performance of LQR and H$_2$ Controller for an Experimentally-Identified Structure with AMD (AMD가 설치된 실험모델에 대한 LQR과 H$_2$제어기의 설계 및 성능비교)

  • 민경원;이승준;주석준;김홍진;박민규
    • Proceedings of the Computational Structural Engineering Institute Conference
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    • 2003.04a
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    • pp.461-470
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    • 2003
  • This paper discusses a time domain controller, LQR, and a frequency domain controller, H₂, for optimal control of civil structures under seismic loads. Numerical simulations are performed on a three-story structure with Active Mass Driver (AMD), which is experimentally identified. Control effectiveness of each controller for the suppression of third floor acceleration responses is investigated when the similar maximum control force is used. Simulation results indicate that LQR is effective for acceleration response reduction while H₂ controller is efficient for utilizing control force.

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An Optimal Tuning of PI-PD Controller Via LQR (LQR을 사용한 최적 PI-PD제어기 동조)

  • Kang, Keun-Hyoung;Suh, Byung-Suhl
    • Proceedings of the KIEE Conference
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    • 2005.05a
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    • pp.109-112
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    • 2005
  • This paper presents an optimal and robust PI-PD controller design method for the second-order systems both with dead time and without dead time to satisfy the design specifications in the time domain via LQR design technique. The optimal tuning method of PI-PD controller are also developed by setpoint weighting and neural networks. It is shown that the simulation results show significantly improved performance by proposed method.

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Alleviating the Tower Mechanical Load of Multi-MW Wind Turbines with LQR Control

  • Nam, Yoonsu;Kien, Pham Trung;La, Yo-Han
    • Journal of Power Electronics
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    • v.13 no.6
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    • pp.1024-1031
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    • 2013
  • This paper addresses linear quadratic regulation (LQR) for variable speed variable pitch wind turbines. Because of the inherent nonlinearity of wind turbines, a set of operating conditions is identified and then a LQR controller is designed for each of the operating points. The feedback controller gains are then interpolated linearly to get a control law for the entire operating region. In addition, the aerodynamic torque and effective wind speed are estimated online to get the gain-scheduling variable for implementing the controller. The potential of this method is verified through simulation with the help of MATLAB/Simulink and GH Bladed. The performance and mechanical load when using LQR are also compared with those obtained when using a PI controller.

The Study on Position Control of Nonlinear System Using Wavelet Neural Network Controller (웨이블렛 신경회로망 제어기를 이용한 비선형 시스템의 위치 제어에 관한 연구)

  • Lee, Jae-Hyun
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.12 no.12
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    • pp.2365-2370
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    • 2008
  • In this paper, applications of wavelet neural network controller to position control of nonlinear system are considered. Wavelet neural network is used in the objectives which improve the efficiency of LQR controllers. It is possible to make unstable nonlinear systems stable by using LQR(Linear Quadratic Regulator) technique. And, in order to be adapted to disturbance effectively in this system it uses wavelet neural network controller. Applying this method to the position control of nonlinear system, its usefulness is verified from the results of experiment.