• 제목/요약/키워드: stabilizing robust control

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AC 서보모터에 대한 견실한 외란억제 제어 (Robust Disturbance Suppression Control for AC Servo Motors)

  • 김창환
    • 한국전자통신학회논문지
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    • 제7권4호
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    • pp.839-848
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    • 2012
  • 본 논문에서는 외란토크를 효과적으로 억제할 수 있는 AC 서보모터의 견실제어 방법을 제안한다. 제안된 제어기는 플랜트 모델에 기초한 피드포워드제어기와 안정화 피드백제어기로 구성된다. 피드포워드제어기는 공칭(nominal) 플랜트의 출력이 기준 속도명령을 정확히 추적하도록 설계되며 피드백제어기는 전체 폐루프시스템을 안정화시키는 역할을 한다. 피드백제어기는 임의로 선택될 수 있는 자유함수를 포함하는데 이 자유함수는 외란토크의 영향을 억제하고 제어기가 모델오차에 견실하게(robust) 동작되도록 선택될 수 있다. 컴퓨터 시뮬레이션을 통하여 제안된 제어방식이 기존의 제어방식들에 비해 우수한 제어성능을 가짐을 입증한다.

파라미터 불확실성 시변 시간지연 시스템에 대한 견실 $H^{\infty}$ 제어 (Robust $H^{\infty}$ control for parameter uncertain time-varying systems with time-varying delays in state and control input)

  • 김기태;김종해;박홍배
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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    • pp.113-116
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    • 1997
  • In this paper, we present a robust $H^{\infty}$ controller design method for parameter uncertain time-varying systems with disturbance and that have time-varying delays in both state and control. It is found that the problem shares the same formulation with the $H^{\infty}$ control problem for systems without uncertainty. Through a certain differential Riccati inequality approach, a class of stabilizing continuous controller is proposed. For parameter uncertainties, disturbance and time varying delays, proposed controllers the plant and guarantee an $H^{\infty}$ norm bound constraint on disturbance attenuation for all admissible uncertainties. Finally a numerical example is given to demonstrate the validity of the results.ts.

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큰 상태변수 시간 지연 부정합조건 불확실성 시스템을 위한 강인한 슬라이딩 모드 제어기 (A Robust Sliding Mode Controller for Unmatched Uncertain Severe Sate Time-Delay Systems)

  • 이정훈
    • 전기학회논문지
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    • 제59권10호
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    • pp.1894-1899
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    • 2010
  • This note is concerned with a robust sliding mode control(SMC) for a class of unmatched uncertain system with severe commensurate state time delay. The suggested method is extended to the control of severe state time delay systems with unmatched uncertainties except the matched input matrix uncertainty. A transformed sliding surface is proposed and a stabilizing control input is suggested. The closed loop stability together with the existence condition of the sliding mode on the proposed sliding surface is investigated through one Lemma and two Theorems by using the Lyapunov direct method with the concept of the control Lyapunov function instead of complex Lyapunov-Kravoskii functionals. Through an illustrative example and simulation study, the usefulness of the main results is verified.

Study on The Attitude Stabilization Techniques of Leo Satellites

  • Hwan, Lho-Young;Yong, Jung-Kang
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.56.5-56
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    • 2001
  • In the three axis control of satellite by using reaction wheel and gyro, a reaction wheel produces the control torque by the wheel speed or momentum, and a gyro carries out measuring of the attitude angle and the attitude angular velocity In this study, dynamic modelling of the Low Earth Orbit (LEO) is consisted of the one from the rotational motion of the satellite with the basic rigid body and a flexible body model, and the gyro in addition to the reaction wheel model. The results obtained by the robust controller are compared with those of the PI (Proportional and Integration) controller which is commonly used for the stabilizing satellite.

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Adaptive Receding Horizon $H_{\infty}$ Controller Design for LPV Systems

  • P., PooGyeon;J., SeungCheol
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2000년도 제15차 학술회의논문집
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    • pp.535-535
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    • 2000
  • This paper presents an adaptive receding horizon H$_{\infty}$ controller for the linear parameter varying systems in the deterministic environment, which combines a parameter range estimator and a robust receding horizon H$_{\infty}$ controller using the parameter bounds. Using parameter set inclusion and terminal inequality condition, the closed-loop system stability is guaranteed. It is shown that the stabilizing adaptive receding horizon H$_{\infty}$ controller guarantees the H$_{\infty}$ norm bound.

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Model Identification and Attitude Control Methodology for the Flexible Body of a Satellite

  • Lho, Young-Hwan
    • International Journal of Aeronautical and Space Sciences
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    • 제11권3호
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    • pp.240-245
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    • 2010
  • The controller of a model reference adaptive control monitors the plant's inputs and outputs to acknowledge its characteristics. It then adapts itself to the characteristics it encounters instead of behaving in a fixed manner. An important part of every adaptive scheme is the adaptive law for estimating the unknown parameters on line. A more precise model is required to improve performance and to stabilize a given dynamic system, such as a satellite in which performance varies over time and the coefficients change due to disturbances, etc. After model identification, the robust controller ($H{\infty}$) is designed to stabilize the rigid body and flexible body of a satellite, which can be perturbed due to disturbance. The result obtained by the $H{\infty}$ controller is compared with that of the proportional and integration controller which is commonly used for stabilizing a satellite.

A CLASS OF ASYMPTOTICALLY STABILIZING STATE FEEDBACK FOR UNCERTAIN NONLINEAR SYSTEMS

  • Hashimoto, Yuuki;Wu, Hansheng;Mizukami, Koichi
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.271-274
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    • 1995
  • This paper is concerned with the problem of robust stabilization of uncertain single-input and single-output nonlinear systems. Based on the input/output linearization approach for nonlinear state feedback synthesis in conjunction with Lyapunov methods, a stabilizing state feedback controller is proposed. Compared with the controllers reported in the control literature, instead of uniform ultimate boudedness, the controller proposed in this paper can guarantee uniform asymptotic stability of nonlinear systems in the presence of uncertainties. The required information about uncertain dynamics in the system is only that the uncertainties are bounded in Euclidean norm by known functions of the system state.

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상태변수 종속 불확실성이 포함된 다입력 비선형 계통에 대한 전역 안정성이 보장되는 견실한 적응 퍼지 제어기 설계 (A design of a robust adaptive fuzzy controller globally stabilizing the multi-input nonlinear system with state-dependent uncertainty)

  • 박영환;박귀태
    • 제어로봇시스템학회논문지
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    • 제2권4호
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    • pp.297-305
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    • 1996
  • In this paper a novel robust adaptive fuzzy controller for the nonlinear system with state-dependent uncertainty is proposed. The conventional adaptive fuzzy controller determines the function of state variable bounding the state-dependent uncertain term in the system dynamics on the local state space by off-line calculation. Whereas the proposed method determines that function by the fuzzy inference so that it guarantees the stability of the closed loop system globally on the whole state space. In addition, the method is applicable to the multi-input system. We applied the proposed method to the Burn Control of the Tokamak fusion reactor whose dynamics contains the state-dependent uncertainty and proved the effectiveness of the scheme by using the simulation results.

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A Novel Stabilizing Control for Neural Nonlinear Systems with Time Delays by State and Dynamic Output Feedback

  • Liu, Mei-Qin;Wang, Hui-Fang
    • International Journal of Control, Automation, and Systems
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    • 제6권1호
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    • pp.24-34
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    • 2008
  • A novel neural network model, termed the standard neural network model (SNNM), similar to the nominal model in linear robust control theory, is suggested to facilitate the synthesis of controllers for delayed (or non-delayed) nonlinear systems composed of neural networks. The model is composed of a linear dynamic system and a bounded static delayed (or non-delayed) nonlinear operator. Based on the global asymptotic stability analysis of SNNMs, Static state-feedback controller and dynamic output feedback controller are designed for the SNNMs to stabilize the closed-loop systems, respectively. The control design equations are shown to be a set of linear matrix inequalities (LMIs) which can be easily solved by various convex optimization algorithms to determine the control signals. Most neural-network-based nonlinear systems with time delays or without time delays can be transformed into the SNNMs for controller synthesis in a unified way. Two application examples are given where the SNNMs are employed to synthesize the feedback stabilizing controllers for an SISO nonlinear system modeled by the neural network, and for a chaotic neural network, respectively. Through these examples, it is demonstrated that the SNNM not only makes controller synthesis of neural-network-based systems much easier, but also provides a new approach to the synthesis of the controllers for the other type of nonlinear systems.

Robust Controller Design for Parametrically Uncertain System

  • Tipsuwanporn, V.;Piyarat, W.;Witheephanich, K.;Gulpanich, S.;Paraken, Y.
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1999년도 제14차 학술회의논문집
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    • pp.92-95
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    • 1999
  • The design problem of the control system is the ability to synthesize controller that achieve robust stability and robust performance. The paper explains the Finite Inclusions Theorem (FIT) by the procedure namely FIT synthesis. It is developed for synthesizing robustly stabilizing controller for parametrically uncertain system. The fundamental problem in the study of parametrically uncertain system is to determine whether or not all the polynomials in a given family of characteristic polynomials is Hurwitz i.e., all their roots lie in the open left-half plane. By FIT it can prove a polynomial is Hurwitz from only approximate knowledge of the polynomial's phase at finitely many points along the imaginary axis. An example shows the simplicity of using the FIT synthesis to directly search for robust controller of parametrically uncertain system by way of solving a sequence of systems of linear inequalities. The systems of inequalities are solved via the projection method which is an elegantly simple technique fur solving (finite or infinite) systems of convex inequalities in an arbitrary Hilbert space. Results from example show that the controller synthesized by FIT synthesis is better than by H$\sub$$\infty$/ synthesis with parametrically uncertain system as well as satisfied the objectives for a considerably larger range of uncertainty.

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