• Title/Summary/Keyword: cart inverted pendulum

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LMI Design of Multi-Objective$ Η_2/Η_\infty$Controllers for an Inverted Pendulum on the Cart Using Polytope Models (폴리토프 모델을 이용한 도립진자의 다목적$ Η_2/Η_\infty$ 제어기의 LMI 설계)

  • 이상철
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.1
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    • pp.6-13
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    • 2002
  • This paper deals with the linear matrix inequality (LMI) design procedures for multi-objective Η$_2$$_{\infty}$ controllers with pole-placement constraints for an inverted pendulum system modeled as convex polytopes to ensure the stabilizing regulator and tracking performances. Polytopic models with multiple linear time-invariant models linearized at some operating points are derived to design controllers overcoming the conservativeness such as a controller may have when it is designed for a model linearized at a single operating point. Multi-objective controllers are designed for polytopic models by the LMT design technique with convex algorithms. It is observed that the inverted pendulum controlled by any controller designed for each polytopic model is stabilizingly restored to the vertical angle position for initial values of larger tilt anlges.

Desing of a Controller for Rod Balancing System

  • Kim, Sang-Gyu;An, Jung-Hun;Hong, Sung-Hun;Kang, Mun-Sung
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.66.4-66
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    • 2001
  • In this paper we have fabricated the two-dimensional Rod Balancing System which expands conventional one-dimensional inverted pendulum control system and designed its controller. The X-axis cart and Y-axis bar of the Rod Balancing System, which is composed of X-Y table, are actuated through timing belt by each of two geared DC motors, and the rod mounted on a X-axis cart can be brought to the desired position and maintained in a vertical position by motor-control. For the control of the Rod Balancing System, we used a fuzzy logic controller that is an approach to systems control when the exact mathematical model of the plant is unknown or the mathematical model is too complex to understand.

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Indirect Adaptive Fuzzy Observer Design

  • Yang, Jong-Kun;Hyun, Chang-Ho;Kim, Jae-Hun;Kim, Eun-Tai;Park, Mi-Gnon
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 2004.10a
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    • pp.192-196
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

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Indirect Adaptive Fuzzy Observer Design

  • Yang, Jong-Kun;Hyun, Chang-Ho;Kim, Jae-Hun;Kim, Eun-Tai;Park, Mignon
    • Journal of the Korean Institute of Intelligent Systems
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    • v.14 no.7
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    • pp.927-933
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

Design of T-S Fuzzy Model based Adaptive Fuzzy Observer and Controller

  • Ahn, Chang-Hwan
    • Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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    • v.23 no.11
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    • pp.9-21
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    • 2009
  • This paper proposes the alternative observer and controller design scheme based on T-S fuzzy model. Nonlinear systems are represented by fuzzy models since fuzzy logic systems are universal approximators. In order to estimate the unmeasurable states of a given unknown nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. The proposed controller is based on a simple output feedback method. Therefore, it solves the singularity problem, without any additional algorithm, which occurs in the inverse dynamics based on the feedback linearization method. The adaptive fuzzy scheme estimates the parameters and the feedback gain comprising the fuzzy model representing the observation system. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observer and controller, they are applied to an inverted pendulum on a cart.

T-S Fuzzy Model Based Indirect Adaptive Fuzzy Observer Design

  • Hyun Chang-Ho;Kim You-Keun;Kim Euntai;Park Mignon
    • Proceedings of the IEEK Conference
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    • summer
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    • pp.348-353
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    • 2004
  • This paper proposes an alternative observation scheme, T-S fuzzy model based indirect adaptive fuzzy observer. Nonlinear systems arc represented by fuzzy models since fuzzy logic systems arc universal approximators. In order to estimate the unmeasurable states of a given nonlinear system, T-S fuzzy modeling method is applied to get the dynamics of an observation system. T-S fuzzy system uses the linear combination of the input state variables and the modeling applications of them to various kinds of nonlinear systems can be found. The adaptive fuzzy scheme estimates the parameters comprising the fuzzy model representing the observation system. The proposed indirect adaptive fuzzy observer based on T-S fuzzy model can cope with not only unknown states but also unknown parameters. In the process of deriving adaptive law, the Lyapunov theory and Lipchitz condition are used. To show the performance of the proposed observation method, it is applied to an inverted pendulum on a cart.

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The Design of Loop-shaping Two-degree-of-freedom H_{\infty} Digital Controller for Sampled-data System (샘플치 시스템의 루프정형 2자유도 H_{\infty}디지털 제어기 설계)

  • Lee, Sang-Cheol;Park, Jong-U;Jo, Do-Hyeon;Lee, Jong-Yong;Lee, Sang-Hyo
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.49 no.9
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    • pp.495-503
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    • 2000
  • In this paper we propose a design procedure of loop-shaping two-degree-of-freedom H$\infty$ digital controller for sampled-data system. We extend the continuous time loop-shaping two-degree-of-freedom H$\infty$ control problem to sampled-data system. The configuration of generalized plant is modified for sampled-data system. And then using continuous lifting we obtain the digital controller. In the final stage of loop-shaping procedure the problem of absorbing weighting functions is discussed. We summarize this study to the design procedure and illustrate the application for an inverted pendulum on the cart.

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SA-selection-based Genetic Algorithm for the Design of Fuzzy Controller

  • Han Chang-Wook;Park Jung-Il
    • International Journal of Control, Automation, and Systems
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    • v.3 no.2
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    • pp.236-243
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    • 2005
  • This paper presents a new stochastic approach for solving combinatorial optimization problems by using a new selection method, i.e. SA-selection, in genetic algorithm (GA). This approach combines GA with simulated annealing (SA) to improve the performance of GA. GA and SA have complementary strengths and weaknesses. While GA explores the search space by means of population of search points, it suffers from poor convergence properties. SA, by contrast, has good convergence properties, but it cannot explore the search space by means of population. However, SA does employ a completely local selection strategy where the current candidate and the new modification are evaluated and compared. To verify the effectiveness of the proposed method, the optimization of a fuzzy controller for balancing an inverted pendulum on a cart is considered.

An Improved Method to Construct T-S Fuzzy Model

  • Min, Hyung-Gi;Jeung, Eun-Tae;Kwon, Sung-Ha
    • 제어로봇시스템학회:학술대회논문집
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    • 2003.10a
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    • pp.2264-2269
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    • 2003
  • This paper presents an improved method that constructs an equivalent T-S fuzzy model for nonlinear systems expressed by nonlinear differential equations including terms of power series. The method in this paper has fewer numbers of the rules than the previous methods as well as exactly expresses nonlinear systems. Moreover, this method can get wider feasible area satisfying the stability conditions than the previous methods. We show the improvement of modeling by comparing the proposed method with two previous methods through an inverted pendulum on a cart.

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Study on the T-S Fuzzy Modeling in Cart-Type Inverted Pendulum System (바퀴형 역진자 시스템의 T-S Fuzzy Modeling에 관한 연구)

  • Lee, Seung-Taek;Lee, Dong-Kwang;Kwak, Gun-Pyong;Park, Seung-Kyu
    • Proceedings of the KIEE Conference
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    • 2011.07a
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    • pp.1858-1859
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    • 2011
  • 제어를 할 때 비선형 시스템을 선형화 하는 것이 중요하다. 선형화를 하기위해는 퍼지 모델을 사용하는데 그 중 바퀴형 역진자 시스템은 비선형 시스템의 파라미터 값을 모두 알아도 T-S퍼지를 기반으로 하여 선형제어를 사용하는데 어려움이 있다. 그래서 Identification을 함으로써 바퀴형 역진자 시스템을 좀 더 편리하게 T-S 퍼지 모델로 만들 수 있다.

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