• 제목/요약/키워드: nonlinear uncertain system

검색결과 248건 처리시간 0.028초

이산 비선형 시스템에 대한 확장 유한 임펄스 응답 필터 (An Extended Finite Impulse Response Filter for Discrete-time Nonlinear Systems)

  • 한세경;권보규;한수희
    • 제어로봇시스템학회논문지
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    • 제21권1호
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    • pp.34-39
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    • 2015
  • In this paper, a finite impulse response (FIR) filter is proposed for discrete-time nonlinear systems. The proposed filter is designed by combining the estimate of the perturbation state and nominal state. The perturbation state is estimated by adapting the optimal time-varying FIR filter for the linearized perturbation model and the nominal state is directly obtained from the nonlinear nominal trajectory model. Since the FIR structured estimators use the finite horizon information on the most recent time interval, the proposed extended FIR filter satisfies the bounded input/bounded output (BIBO) stability, which can't be obtained from infinite impulse response (IIR) estimators. Thus, it can be expected that the proposed extended FIR filter is more robust than IIR structured estimators such as an extended Kalman filter for the round-of errors and the uncertainties from unknown initial states and uncertain system model parameters. The simulation results show that the proposed filter has better performance than the extended Kalman filter (EKF) in both robustness and fast convergency.

비선형 마찰력이 있는 시스템의 강인한 적응제어기법 (Adaptive Robust Control of Mechanical Systems with Uncertain Nonlinear Dynamic Friction)

  • 이태봉;양현석;김병한
    • 한국산학기술학회논문지
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    • 제12권11호
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    • pp.5194-5201
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    • 2011
  • 본 논문에서는 부분적으로 알고 있는 비선형 마찰력이 있는 2차 기계시스템에 대한 강인한 적응제어 기법을 제시한다. 제시하는 적응제어 방법은 잡음이나 모델링 에러가 없는 경우에는 위치 및 속도 추적 오차는 점근적으로 영으로 수렴함을 보장하며, 잡음이나 모델링 에러가 있는 경우에는 그동안 발표된 다른 논문의 결과와 달리 디자인 변수를 적절하게 선택하면 위치 및 속도 추적 오차를 원하는 범위까지 줄일 수 있음을 보였으며 이는 시뮬레이션 결과를 통해 입증하였다.

불확실한 pure-feedback 비선형 계통에 대한 출력 궤환 적응 신경망 제어기 (Adaptive Output-feedback Neural Control of uncertain pure-feedback nonlinear systems)

  • 박장현;김성환;장영학;유영재
    • 한국지능시스템학회논문지
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    • 제23권6호
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    • pp.494-499
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    • 2013
  • 본 논문은 불확실한 연속시 단일입력 단일출력 pure-feedback 비선형 계통에 대해서 참고문헌 [15]에서 제안된 상태변수 궤환 적응 신경망 제어 알고리듬을 바탕으로 출력만이 측정 가능한 계통에 적용할 수 있는 출력 궤환 제어기를 제시한다. 고려하는 계통에 대한 출력 궤환 적응 신경망 제어기는 이 분야에서 아직까지 어느 문헌에서도 다루지 않은 주제이다. 제안된 출력 궤환 제어기는 백스테핑을 회피하여 상대적으로 간결한 제어 규칙과 단 하나의 신경망만이 사용된다는 [15]의 장점을 그대로 계승하며 적용되는 비선형 계통의 범주를 더 넓힌다는 의미를 가진다.

비적응 모델 보상법에 의한 강성로보트의 강인한 동작제어 (Robust Motion Control of Robotic Manipulators with Nonadaptive Model-based Compensation)

  • ;유삼상
    • Journal of Advanced Marine Engineering and Technology
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    • 제18권4호
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    • pp.102-111
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    • 1994
  • This article deals with the problem of designing a robust algorithm for the motion control of robot manipulator whose nonlinear dynamics contain various uncertainties. To ensure high performance of control system, a model-based feedforward compensation with continuous robust control has been developed. The control structure based on the deterministic approach consists of two parts : the nominal control law is first introduced to stabilize the system without uncertainties, then a robust nonlinear control law is adopted to compensate for both the resulting errors(or structured uncertainties) and unstructured uncertainties. The uncertainties assumed in this study are bounded by polynomials in the Euclidean norms of system states with known bounding coefficients. The presented control scheme is relatively simple as well as computationally efficient. With a feasible class of desired trajectories, the proposed control law provides sufficient criteria which guarantee that all possible responses of the closed-loop system are uniformly ultimately bounded in the presence of uncertainties. Therefore, the control algorithm proposed is shown to be robust with respect to the involved uncertainties.

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신경회로망을 이용한 무인헬리콥터의 적응출력피드백제어 (Adaptive Output Feedback Control of Unmanned Helicopter Using Neural Networks)

  • 박범진;홍창호;석진영
    • 한국항공우주학회지
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    • 제35권11호
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    • pp.990-998
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    • 2007
  • 불확실한 비선형 다중입출력 시스템에 대해서 신경회로망을 이용한 적응출력피드백제어기법이 제안되었다. 역변환 기반의 제어입력으로부터 불확실한 비선형성을 분리하기 위해 변형된 운동 역변환 모델(Modified Dynamic Inversion Model, MDIM)이 도입되었다. MDIM은 근사된 운동 역변환 모델과 역변환 모델 오차로 구성되었고 한 개의 신경회로망이 MDIM을 보상하는데 적용되었다. 여기서 신경회로망의 출력은 필터링된 근사오차 기반의 제어기를 증대시킨다. 추적성능과 종국적 유계성(ultimate boundedness)을 보장하기 위해 리야프노프의 직접방법(Lyapunov's direct method)으로부터 유도된 온라인 가중치 적응법칙이 이용되었다. 수치적 시뮬레이션을 통해 본 논문의 타당성을 검증하였다.

Robust Stabilization of Uncertain Nonlinear Systems via Fuzzy Modeling and Numerical Optimization Programming

  • Lee Jongbae;Park Chang-Woo;Sung Ha-Gyeong;Lim Joonhong
    • International Journal of Control, Automation, and Systems
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    • 제3권2호
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    • pp.225-235
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    • 2005
  • This paper presents the robust stability analysis and design methodology of the fuzzy feedback linearization control systems. Uncertainty and disturbances with known bounds are assumed to be included in the Takagi-Sugeno (TS) fuzzy models representing the nonlinear plants. $L_2$ robust stability of the closed system is analyzed by casting the systems into the diagonal norm bounded linear differential inclusions (DNLDI) formulation. Based on the linear matrix inequality (LMI) optimization programming, a numerical method for finding the maximum stable ranges of the fuzzy feedback linearization control gains is also proposed. To verify the effectiveness of the proposed scheme, the robust stability analysis and control design examples are given.

Hopfield 신경망의 파라미터 추정을 이용한 간접 적응 가변구조제어 (Indirect Adaptive Sliding Mode Control Using Parameter Estimation of Hopfield Network)

  • 함재훈;박태건;이기상
    • 대한전기학회:학술대회논문집
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    • 대한전기학회 1996년도 하계학술대회 논문집 B
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    • pp.1037-1041
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    • 1996
  • Input-output linearization technique in nonlinear control does not guarantee the robustness in the presence of parameter uncertainty or unmodeled dynamics, etc. However, it has been used as an important preliminary step in achieving additional control objectives, for instance, robustness to parameter uncertainty and disturbance attenuation. An indirect adaptive control scheme based on input-output linearization is proposed in this paper. The scheme consists of a Hopfield network for process parameter identification and an adaptive sliding mode controller based on input-output linearization, which steers the system response into a desired configuration. A numerical example is presented for the trajectory tracking of uncertain nonlinear dynamic systems with slowly time-varying parameters.

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A Neural Network Adaptive Controller for Autonomous Diving Control of an Autonomous Underwater Vehicle

  • Li, Ji-Hong;Lee, Pan-Mook;Jun, Bong-Huan
    • International Journal of Control, Automation, and Systems
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    • 제2권3호
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    • pp.374-383
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    • 2004
  • This paper presents a neural network adaptive controller for autonomous diving control of an autonomous underwater vehicle (AUV) using adaptive backstepping method. In general, the dynamics of underwater robotics vehicles (URVs) are highly nonlinear and the hydrodynamic coefficients of vehicles are difficult to be accurately determined a priori because of variations of these coefficients with different operating conditions. In this paper, the smooth unknown dynamics of a vehicle is approximated by a neural network, and the remaining unstructured uncertainties, such as disturbances and unmodeled dynamics, are assumed to be unbounded, although they still satisfy certain growth conditions characterized by 'bounding functions' composed of known functions multiplied by unknown constants. Under certain relaxed assumptions pertaining to the control gain functions, the proposed control scheme can guarantee that all the signals in the closed-loop system satisfy to be uniformly ultimately bounded (UUB). Simulation studies are included to illustrate the effectiveness of the proposed control scheme, and some practical features of the control laws are also discussed.

Modified RHKF Filter for Improved DR/GPS Navigation against Uncertain Model Dynamics

  • Cho, Seong-Yun;Lee, Hyung-Keun
    • ETRI Journal
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    • 제34권3호
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    • pp.379-387
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    • 2012
  • In this paper, an error compensation technique for a dead reckoning (DR) system using a magnetic compass module is proposed. The magnetic compass-based azimuth may include a bias that varies with location due to the surrounding magnetic sources. In this paper, the DR system is integrated with a Global Positioning System (GPS) receiver using a finite impulse response (FIR) filter to reduce errors. This filter can estimate the varying bias more effectively than the conventional Kalman filter, which has an infinite impulse response structure. Moreover, the conventional receding horizon Kalman FIR (RHKF) filter is modified for application in nonlinear systems and to compensate the drawbacks of the RHKF filter. The modified RHKF filter is a novel RHKF filter scheme for nonlinear dynamics. The inverse covariance form of the linearized Kalman filter is combined with a receding horizon FIR strategy. This filter is then combined with an extended Kalman filter to enhance the convergence characteristics of the FIR filter. Also, the receding interval is extended to reduce the computational burden. The performance of the proposed DR/GPS integrated system using the modified RHKF filter is evaluated through simulation.

Uncertainty Modeling and Robust Control for LCL Resonant Inductive Power Transfer System

  • Dai, Xin;Zou, Yang;Sun, Yue
    • Journal of Power Electronics
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    • 제13권5호
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    • pp.814-828
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    • 2013
  • The LCL resonant inductive power transfer (IPT) system is increasingly used because of its harmonic filtering capabilities, high efficiency at light load, and unity power factor feature. However, the modeling and controller design of this system become extremely difficult because of parameter uncertainty, high-order property, and switching nonlinear property. This paper proposes a frequency and load uncertainty modeling method for the LCL resonant IPT system. By using the linear fractional transformation method, we detach the uncertain part from the system model. A robust control structure with weighting functions is introduced, and a control method using structured singular values is used to enhance the system performance of perturbation rejection and reference tracking. Analysis of the controller performance is provided. The simulation and experimental results verify the robust control method and analysis results. The control method not only guarantees system stability but also improves performance under perturbation.