• Title/Summary/Keyword: Linearization method

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A Robust Indirect Adaptive Fuzzy State Feedback Regulator Based on Takagi-Sugeno Fuzzy Model

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.12 no.6
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    • pp.554-558
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

Development of an AOA Location Method Using Self-tuning Weighted Least Square (자기동조 가중최소자승법을 이용한 AOA 측위 알고리즘 개발)

  • Lee, Sung-Ho;Kim, Dong-Hyouk;Roh, Gi-Hong;Park, Kyung-Soon;Sung, Tae-Kyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.13 no.7
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    • pp.683-687
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    • 2007
  • In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and Closed-Form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-Form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a Self-Tuning Weighted Least Square AOA algorithm that is a modified version of the conventional Closed-Form solution. In order to estimate the error covariance matrix as a weight, a two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

A NEW SOLUTION METHOD FOR STATE EQUATIONS OF NONLINEAR SYSTEM

  • Zhang, Cheng-Hui;Tan, Cheng-Hui;Cui, Na-Xin
    • Journal of applied mathematics & informatics
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    • v.6 no.1
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    • pp.175-184
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    • 1999
  • Along with the computation and analysis for nonlinear system being more and more involved in the fields such as automation control electronic technique and electrical power system the nonlin-ear theory has become quite a attractive field for academic research. In this paper we derives the solutions for state equation of nonlinear system by using the inverse operator expression of the so-lutions is obtained. An actual computation example is given giving a comparison between IOM and Runge-kutta method. It has been proved by our investigation that IOM has some distinct advantages over usual approximation methods in that it is computationally con-venient rapidly convergent provides accurate solutions not requiring perturbation linearization or the massive computation inherent in discrietization methods such as finite differences. So the IOM pro-vides an effective method for the solution of nonlinear system is of potential application valuable in nonlinear computation.

Error Analysis of Time-Based and Angle-Based Location Methods (시간기반과 각도기반의 측위방식 성능비교 및 오차 특성 분석)

  • Kim Dong-Hyeok;Song Seung-Hun;Sung Tae-Kyung
    • Journal of Institute of Control, Robotics and Systems
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    • v.12 no.10
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    • pp.962-967
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    • 2006
  • Indoor positioning is highlighted recently, and various kinds of indoor positioning systems are under developments. Since positioning systems have their own characteristics, proper positioning scheme should be chosen according to the required specifications. Positioning methods are classified into time-based and angle-based one. This paper presents the error analysis of time-based and angle-based location methods. Because measurements of these methods are nonlinear, linearizations are needed in both cases to estimate the user position. In the linearization, Gauss-Newton method is used in both cases. To analyze the position error, we investigate the error ellipse parameters that include eccentricity, rotation angle, and the size of ellipse. Simulation results show that the major axes of TOA and AOA method lie in different quadrants at most region of workspace, especially where the geometry is poor. When the TOA/AOA hybrid is employed, it is found that the error ellipse is reduced to the intersection of ellipses of TOA and AOA.

Dynamic Control of a Robot with a Free Wheel (바퀴달린 로봇의 동적 제어)

  • 은희창;정동원
    • Journal of the Korean Society for Precision Engineering
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    • v.15 no.3
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    • pp.127-132
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    • 1998
  • Mobile wheeled robots are nonholonomically constrained systems. Generally, it is very difficult to describe the motion of mechanical systems with nonintegrable nonholonomic constraints. An objective of this study is to describe the motion of a robot with a free wheel. The motion of holonomically and/or nonholonomically constrained system can be simply determined by Generalized Inverse Method presented by Udwadia and Kalaba in 1992. Using the method, we describe the exact motion of the robot and determine the constraint force exerted on the robot for satisfying constraints imposed on it. The application illustrates the ease with which the Generalized Inverse Method can be utilized for the purpose of control of nonlinear system without depending on any linearization, maintaining precision tracking motion and explicit determination of control forces of nonholonomically constrained system.

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T-S Fuzzy Model Based Robust Indirect Adaptive State Feedback Control of Flexible Joint Manipulators

  • Hyun, Chang-Ho;Park, Chang-Woo;Park, Mignon
    • Proceedings of the IEEK Conference
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    • 2002.07c
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    • pp.1471-1474
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    • 2002
  • In this paper, we propose a robust indirect adaptive fuzzy state feedback regulator based on Takagi-Sugeno fuzzy model. The proposed adaptive fuzzy regulator is less sensitive to singularity than the conventional one based on the feedback linearization method. Furthermore, the proposed control method is applicable to not only plants with a perfect model but also plants with an imperfect model, which causes uncertainties. We verify the global stability of the proposed method by using Lyapunov method. In order to support the achievement, the application of the proposed adaptive fuzzy regulator to the control of a nonlinear system under the external disturbance is presented and the performance was verified by some simulation result.

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Wheel Slip Control of ABS Using Adaptive Control Method (적응제어 기법을 적용한 ABS의 바퀴 슬립 제어)

  • Choi, Jong-Hwan
    • Journal of the Korean Society of Manufacturing Process Engineers
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    • v.5 no.3
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    • pp.71-79
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    • 2006
  • ABS is a safety device for preventing wheel locking in a sudden baking. Its control methods are classified into three types; deceleration control, wheel slip control and deceleration/acceleration control. The braking force takes the influence of the friction coefficient between road and tire, which in turn depends on the wheel slip as well as road conditions. In this paper, it has been proposed the wheel slip control system to apply the adaptive control method at the ABS. To maintain wheel slip to desired wheel slip, it have been done the linearization and designed the adaptive controller to apply gradient method based on the reference model. It is illustrated by computer simulations that the proposed control system gives good performances and adaptation to parameter variation.

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Development of an AOA Location Method Using Covariance Estimation

  • Lee, Sung-Ho;Roh, Gi-Hong;Sung, Tae-Kyung
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • v.1
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    • pp.485-489
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    • 2006
  • In last decades, several linearization methods for the AOA measurements have been proposed, for example, Gauss-Newton method and closed-form solution. Gauss-Newton method can achieve high accuracy, but the convergence of the iterative process is not always ensured if the initial guess is not accurate enough. Closed-form solution provides a non-iterative solution and it is less computational. It does not suffer from convergence problem, but estimation error is somewhat larger. This paper proposes a self-tuning weighted least square AOA algorithm that is a modified version of the conventional closed-form solution. In order to estimate the error covariance matrix as a weight, two-step estimation technique is used. Simulation results show that the proposed method has smaller positioning error compared to the existing methods.

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Numerical simulation of non-isothermal flow in oil reservoirs using a two-equation model

  • dos Santos Heringer, Juan Diego;de Souza Debossam, Joao Gabriel;de Souza, Grazione;Souto, Helio Pedro Amaral
    • Coupled systems mechanics
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    • v.8 no.2
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    • pp.147-168
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    • 2019
  • This work aims to simulate three-dimensional heavy oil flow in a reservoir with heater-wells. Mass, momentum and energy balances, as well as correlations for rock and fluid properties, are used to obtain non-linear partial differential equations for the fluid pressure and temperature, and for the rock temperature. Heat transfer is simulated using a two-equation model that is more appropriate when fluid and rock have very different thermal properties, and we also perform comparisons between one- and two-equation models. The governing equations are discretized using the Finite Volume Method. For the numerical solution, we apply a linearization and an operator splitting. As a consequence, three algebraic subsystems of linearized equations are solved using the Conjugate Gradient Method. The results obtained show the suitability of the numerical method and the technical feasibility of heating the reservoir with static equipment.

Nonlinear elements position detecting by error matrix method (오차행렬에 의한 비선형 요소 위치 파악에 관한 연구)

  • 변언섭;이상설;박윤식
    • Transactions of the Korean Society of Mechanical Engineers
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    • v.14 no.5
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    • pp.1104-1111
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    • 1990
  • A method to identify nonlinear elements position of a nonlinear system is presented. Nonlinear elements position can be identified by an equivalent error damping and stiffness matrices which are based on the equivalent linearization technique. The procedures of this technique are: (1) Obtain input force and system response. (2) Define error between the actual and linearized restoring forces. (3) Calculate linearized damping and stiffness coefficients to minimize the square error sum. Several examples are tested and found that these methods are very effective not only to locate the nonlinear elements position but also to identify the degree of nonlinearity qualitatively. Nonlinear type can be qualitatively identified by examining the plots of restoring force vs equivalent state values.