• 제목/요약/키워드: Model Uncertainties

검색결과 1,294건 처리시간 0.03초

A Robust Input Modification Approach for High Tracking Control Performance of Flexible Joint Robot

  • Park, Min-Kyu;Lee, Sang-Hun;Hur, Jong-Sung;Yim, Jong-Guk;Park, Jong-Hyeon
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.1249-1253
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    • 2004
  • A robust input modification approach to the control of flexible joint robot is presented. In our previous study, we developed an observer based state feedback control for the suppression of residual vibration of a robot. The control was very effective in suppressing the inherent vibration of a flexible joint robot. However it did not meet high performance requirements under high speed motion and model uncertainties. As a solution of the problem, we present an input modification method with robustness against parametric uncertainties. The main idea of the proposed input modification method is to generate a modified reference position command for fast and accurate motion of the robot. Using this proposed method we can reduce the servo delay and settling time by about 60% and substantially improve the path accuracy.

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Design of Controller for Affine Takagi-Sugeno Fuzzy System with Parametric Uncertainties via BMI

  • Lee, Sang-In;Joo, Young-Hoon;Park, Jin-Bae
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2004년도 ICCAS
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    • pp.658-662
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    • 2004
  • This paper develops a stability analysis and controller synthesis methodology for a continuous-time affine Takagi-Sugeno (T-S) fuzzy systems with parametric uncertainties. Affine T-S fuzzy system can be an advantage because it may be able to approximate nonlinear functions to high accuracy with fewer rules than the homogeneous T-S fuzzy systems with linear consequents only. The analysis is based on Lyapunov functions that are continuous and piecewise quadratic. The search for a piecewise quadratic Lyapunov function can be represented in terms of bilinear matrix inequalities (BMIs). A simulation example is given to illustrate the application of the proposed method.

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An Extended Robust $H_{\infty}$ Filter for Nonlinear Constrained Uncertain System

  • Seo, Jae-Won;Yu, Myeong-Jong;Park, Chan-Gook;Lee, Jang-Gyu
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2003년도 ICCAS
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    • pp.565-569
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    • 2003
  • In this paper, a robust filter is proposed to effectively estimate the system states in the case where system model uncertainties as well as disturbances are present. The proposed robust filter is constructed based on the linear approximation methods for a general nonlinear uncertain system with an integral quadratic constraint. We also derive the important characteristic of the proposed filter, a modified $H_{\infty}$ performance index. Analysis results show that the proposed filter has robustness against disturbances, such as process and measurement noises, and against parameter uncertainties. Simulation results show that the proposed filter effectively improves the performance.

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Robust 제어기를 이용한 발전 여자 시스템 전력 안정도 개선 (PSS Improvement of Generator Excitation System using Robust Controller)

  • 홍현문;최재호;류홍우
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 A
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    • pp.364-367
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    • 1996
  • This paper deals with the design and evaluation of the robust controller for generator excitation system to improve the steady state and transient stabilities. The nonlinear characteristics of the system is treated as model uncertainties, and then the robust control techniques are introduced into the PSS design to take into account these uncertainties at the controller design stage. The performance of the designed controller is examined by extensive non-linear time domain simulation. It is shown that the performance of the robust controller is superior to that of the conventional PSS in all cases studied.

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A Robust Sensorless Vector Control System for Induction Motors

  • Huh Sung-Hoe;Choy Ick;Park Gwi-Tae
    • 전력전자학회:학술대회논문집
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    • 전력전자학회 2001년도 Proceedings ICPE 01 2001 International Conference on Power Electronics
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    • pp.443-447
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    • 2001
  • In this paper, a robust sensorless vector control system for induction motors with a speed estimator and an uncertainty observer is presented. At first, the proposed speed estimator is based on the MRAS(Mode Reference Adaptive System) scheme and constructed with a simple fuzzy logic(FL) approach. The structure of the proposed FL estimator is very simple. The input of the FL is the rotor flux error difference between reference and adjustable model, and the output is the estimated incremental rotor speed Secondly, the unmodeled uncertainties such as parametric uncertainties and external load disturbances are modeled by a radial basis function network(RBFN). In the overal speed control system, the control inputs are composed with a norminal control input and a compensated control input, which are from RBFN observer output and the modeling error of the RBFN, repectively. The compensated control input is derived from Lyapunov unction approach. The simulation results are presented to show the validity of the proposed system.

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비중앙 집중식 강성 적응 제어법을 통한 산업용 로봇 궤도추적제어 (Robust Decentralized Adaptive Controller for Trajectory Tracking Control of Uncertain Robotic Manipulators)

  • 유삼상
    • 수산해양기술연구
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    • 제30권4호
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    • pp.329-340
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    • 1994
  • This paper presents a dynamic compensation methodology for robust trajectory tracking control of uncertain robot manipulators. To improve tracking performance of the system, a full model-based feedforward compensation with continuous VS-type robust control is developed in this paper(i.e,. robust decentralized adaptive control scheme). Since possible bounds of uncertainties are unknown, the adaptive bounds of the robust control is used to directly estimate the uncertainty bounds(instead of estimating manipulator parameters as in centralized adaptive control0. The global stability and robustness issues of the proposed control algorithm have been investigated extensively and rigorously via a Lyapunov method. The presented control algorithm guarantees that all system responses are uniformly ultimately bounded. Thus, it is shown that the control system is evaluated to be highly robust with respect to significant uncertainties.

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적응 백스테핑과 MRAS를 이용한 유도전동기 제어 (Induction Motor Control Using Adaptive Backstepping and MRAS)

  • 이선영;박기광;양해원
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 2008년도 학술대회 논문집 정보 및 제어부문
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    • pp.77-78
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    • 2008
  • This paper presents to control speed of induction motors with uncertainties. We use an adaptive backstepping controller with fuzzy neural networks(FNNs) and model reference adaptive system(MRAS) at Indirect vector control method. The adaptive backstepping controller using FNNs can control speed of induction motors even we have a minimum of information. And this controller can be used to approximate most of uncertainties which are derived from unknown motor parameters, load torque such as disturbances. MRAS estimates to rotor resistance and also can find optimal flux to minimize power losses of Induction motor. Indirect vector PI current controller is used to keep rotor flux constant without measuring or estimating the rotor flux. Simulation and experiment results are verified the effectiveness of this proposed approach.

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Power System Oscillations Damping by Robust Decentralized DFIG Wind Turbines

  • Surinkaew, Tossaporn;Ngamroo, Issarachai
    • Journal of Electrical Engineering and Technology
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    • 제10권2호
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    • pp.487-495
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    • 2015
  • This paper proposes a new robust decentralized power oscillation dampers (POD) design of doubly-fed induction generator (DFIG) wind turbine for damping of low frequency electromechanical oscillations in an interconnected power system. The POD structure is based on the practical $2^{nd}$-order lead/lag compensator with single input. Without exact mathematical model, the inverse output multiplicative perturbation is applied to represent system uncertainties such as system parameters variation, various loading conditions etc. The parameters optimization of decentralized PODs is carried out so that the stabilizing performance and robust stability margin against system uncertainties are guaranteed. The improved firefly algorithm is applied to tune the optimal POD parameters automatically. Simulation study in two-area four-machine interconnected system shows that the proposed robust POD is much superior to the conventional POD in terms of stabilizing effect and robustness.

A Robust Control with a Neural Network Structure for Uncertain Robot Manipulator

  • Han, Myoung-Chul
    • Journal of Mechanical Science and Technology
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    • 제18권11호
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    • pp.1916-1922
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    • 2004
  • A robust position control with the bound function of neural network structure is proposed for uncertain robot manipulators. The uncertain factors come from imperfect knowledge of system parameters, payload change, friction, external disturbance, and etc. Therefore, uncertainties are often nonlinear and time-varying. The neural network structure presents the bound function and does not need the concave property of the bound function. The robust approach is to solve this problem as uncertainties are included in a model and the controller can achieve the desired properties in spite of the imperfect modeling. Simulation is performed to validate this law for four-axis SCARA type robot manipulator.

모터 각도를 이용한 유연 관절 머니퓰레이터의 강인한 위치 추종 제어기 설계 (Design of a Robust Position Tracking Controller for Flexible Joint Manipulator Using Motor Angle)

  • 이상명;김인혁;손영익
    • 전기학회논문지
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    • 제63권9호
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    • pp.1245-1247
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    • 2014
  • This paper presents a robust position tracking controller for motor-driven flexible joint manipulators using only the motor angle measurement. The control problem is not easy because the link position is hard to estimate in the presence of parameter uncertainties. The proposed controller consists of a feedback linearization controller (FLC) and two proportional-integral observers (PIOs) that estimate both system states including the link position and an equivalent disturbance for compensating the parameter uncertainties. Comparative computer simulations are conducted to demonstrate the effectiveness of the proposed control algorithm.