• Title/Summary/Keyword: Uncertainties, Disturbances

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Robust Motion Controller Design for Flexible XY Positioning Systems (유연한 XY 위치결정 시스템을 위한 강인 동작 제어기 설계)

  • 김봉근;박상덕;정완균;염영일
    • Journal of Institute of Control, Robotics and Systems
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    • v.9 no.1
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    • pp.82-89
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    • 2003
  • A robust motion control method is proposed fur the point-to-point position control of a XY positioning system which consists of a base cart, elastic ben and moving mass. The horizontal motion controller consists of the feedforward controller to suppress the single mode vibration of the elastic beam and the feedback controller to get the high-accuracy positioning performance of the base cart. Input preshaping vibration suppression method based on system modeling with analytic frequency equation is proposed and integrated into the robust internal-loop compensator(RIC) to increase the robustness of the whole closed-loop system The vertical motion controller is proposed based on the dual RIC structure. Through experiments, it is shown that the proposed method can stabilize the system and suppress the vibration in the presence of uncertainties and disturbances.

Robust Predictive Feedback Control for Constrained Systems

  • Giovanini, Leonardo;Grimble, Michael
    • International Journal of Control, Automation, and Systems
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    • v.2 no.4
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    • pp.407-422
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    • 2004
  • A new method for the design of predictive controllers for SISO systems is presented. The proposed technique allows uncertainties and constraints to be concluded in the design of the control law. The goal is to design, at each sample instant, a predictive feedback control law that minimizes a performance measure and guarantees of constraints are satisfied for a set of models that describes the system to be controlled. The predictive controller consists of a finite horizon parametric-optimization problem with an additional constraint over the manipulated variable behavior. This is an end-constraint based approach that ensures the exponential stability of the closed-loop system. The inclusion of this additional constraint, in the on-line optimization algorithm, enables robust stability properties to be demonstrated for the closed-loop system. This is the case even though constraints and disturbances are present. Finally, simulation results are presented using a nonlinear continuous stirred tank reactor model.

Robust Tracking Control of a Flexible Joint Robot System using a CMAC Neural Network Disturbance Observer (CMAC 신경망 외란관측기를 이용한 유연관절 로봇의 강인 추적제어)

  • 김은태
    • Journal of the Institute of Electronics Engineers of Korea SC
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    • v.40 no.5
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    • pp.299-307
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    • 2003
  • The local structure of CMAC neural networks (NN) results in better and faster controllers for nonlinear dynamical systems. In this paper, we propose a CMAC NN-based disturbance observer and its corresponding controller for a flexible joint robot. The CMAC NN-based disturbance observer compensates for the parametric uncertainties and the external disturbances throughout the entire mechanical system. Finally, a simulation result is given to demonstrate the effectiveness of proposed design method's robust tracking performance.

A Design of PID Controller Using Loop Shaping Method of QFT (QFT의 루프형성법을 이용한 PID 제어기 설계)

  • Kim Ju-Sik;Lee Sang-Hyuk
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.52 no.7
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    • pp.379-384
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    • 2003
  • QFT(Quantitative Feedback Theory) is a very practical design technique that emphasizes the use of feedback for achieving the desired system performance tolerances in despite of plant uncertainties and disturbances. The loop shaping procedure of the QFT method is employed to design the robust controller, until the desired bounds are satisfied. This paper presents a method to estimate the Pm parameters using the loop shaping of the QFT. The proposed method identifies the parameter vector of PID controller from a linear system that develops from rearranging the two dimensional input matrices and output vectors obtained from the QFT bounds. The feasibilities of the suggested algorithm are illustrated with an example.

A Study on the Effectiveness of ILQ Algorithm in Active Structural Control (건축 구조물의 능동 제진에 있어 ILQ 제어 알고리즘의 유용성에 관한 연구)

  • Lee, Jin-Ho;Hwang, I-Cheol
    • Proceedings of the KSME Conference
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    • 2001.06b
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    • pp.140-145
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    • 2001
  • Various control algorithms are available to suppress the vibration of a system subjected to disturbances. LQ algorithm is simple and easy to implement the hardwares, but it lacks robustness for uncertainties and often causes difficulty in determining the weighting matrices. This study focuses on the effectiveness ILQ(Inverse Linear Quadratic optimal control) algorithm as the alternative to LQ applied to control the vibration of a building under the seismic excitation. The building is of moment resisting steel frames and assumed to behave within the elastic range. The brief overview of LQ and ILQ algorithms is introduced, and the displacement responses of the structure using ILQ algorithm are compared with those obtained from LQ control. The magnitude of control forces are also determined and compared for both LQ and ILQ algorithm.

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Sliding Mode Control with Disturbance Observer for An Active Magnetic Bearing System (능동자기베어링계에서 외란관측기를 갖는 슬라이딩모드 제어)

  • Kang, Min-Sig
    • Proceedings of the KSME Conference
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    • 2004.04a
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    • pp.846-851
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    • 2004
  • In this paper, a sliding mode control based on disturbance observer is proposed to attenuate disturbance responses in an active magnetic bearing system, which is subject to base motion. An algorithm for exactly decoupling the disturbance estimation dynamics from the sliding mode dynamics is developed. It is also shown that the proposed method preserves the robustness of the sliding mode and asymtotically achieves zero regulation error, in the presence of external disturbances and parametric uncertainties. The proposed control is applied to a 2-DOF active magnetic bearing system subject to base motion. The feasibility of the proposed technique is illustrated, and the results of an experimental demonstration are shown.

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Stochastic Design Approach for the Guidance and Control System of an Automatic Landing Vehicle

  • Minami, Yoshinori;Miyazawa, Yoshikazu;Shimada, Yuzo
    • 제어로봇시스템학회:학술대회논문집
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    • 1998.10a
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    • pp.41-46
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    • 1998
  • In this paper, a stochastic approach based on a Monte Carlo simulation method for the design of a guidance and control (G & C) system of an automatic landing flight experiment (ALFLEX) vehicle is presented. The aim of this study is to design a G & C system robust against uncertainties in the vehicular dynamics. In this study, uncertain parameters and disturbances are treated as random variables in the Monte Carlo simulation. Then, some controller gains in the G & C system are tuned to satisfy conditions concerning the states at touchdown. The proposed method was applied to the ALFLEX vehicle. The simulation results shored the effectiveness of the present approach.

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Teleoperation Controller Design for an Underwater Manipulator Using an $H_{\infty}$ Control Scheme Based on Disturbance Observer (외란관측기를 바탕으로 $H_{\infty}$제어 방법을 이용한 수중 로봇 팔의 원격조종 제어기 설계)

  • Ryu, Jee-Hwan;Kwon, Dong-Soo;Lee, Pan-Moon;Hong, Seok-Won
    • Journal of Institute of Control, Robotics and Systems
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    • v.6 no.7
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    • pp.578-585
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    • 2000
  • This paper presents a robust and systematic bilateral controller design method for a teleoperation of an underwater manipulator. Disturbance observer is used as a local controller of the master and underwater slave manipulator to set up the teleoperation system as a nominal model by compensating coupled nonlinear terms model uncertainties and external disturbances in the water. Using the linearized master/slave model a $H_{\infty}$ optimal control scheme is applied to systematically construct a force reflecting bilateral controller.

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Fuzzy Logic Application to a Two-wheel Mobile Robot for Balancing Control Performance

  • Kim, Hyun-Wook;Jung, Seul
    • International Journal of Fuzzy Logic and Intelligent Systems
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    • v.12 no.2
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    • pp.154-161
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    • 2012
  • This article presents experimental studies of fuzzy logic application to control a two-wheel mobile robot(TWMR) system. The TWMR system is composed of two systems, an inverted pendulum system and a mobile robot system. Although linear controllers can stabilize the TWMR, fuzzy controllers are expected to have robustness to uncertainties so that the resulting performances are expected to be better. Nominal fuzzy rules are used to control balance and position of TWMR. Fuzzy logic is embedded on a DSP chip to control the TWMR. Balancing performances of the PID controller and the fuzzy controller under disturbances are compared through extensive experimental studies.

Adaptive Neural Network Control for Robot Manipulators

  • Lee, Min-Jung;Choi, Young-Kiu
    • KIEE International Transaction on Systems and Control
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    • v.12D no.1
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    • pp.43-50
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    • 2002
  • In the recent years neural networks have fulfilled the promise of providing model-free learning controllers for nonlinear systems; however, it is very difficult to guarantee the stability and robustness of neural network control systems. This paper proposes an adaptive neural network control for robot manipulators based on the radial basis function netwo.k (RBFN). The RBFN is a branch of the neural networks and is mathematically tractable. So we adopt the RBFN to approximate nonlinear robot dynamics. The RBFN generates control input signals based on the Lyapunov stability that is often used in the conventional control schemes. The saturation function is also chosen as an auxiliary controller to guarantee the stability and robustness of the control system under the external disturbances and modeling uncertainties.

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