• Title/Summary/Keyword: Sugeno model

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Design of the Optimal Controller for Takagi-Sugeno Fuzzy Systems and Its Application to Spacecraft control (Takagi-Sugeno 퍼지시스템에 대한 최적 제어기 설계 및 우주 비행체의 자세 제어 응용)

  • Park, Yeon-Muk;Tak, Min-Je
    • Journal of Institute of Control, Robotics and Systems
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    • v.7 no.7
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    • pp.589-596
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    • 2001
  • In this paper, a new design methodology for the optimal control of nonlinear systems described by the TS(Takagi-Sugeno) fuzzy model is proposed. First, a new theorem concerning the optimal stabilizing control of a general nonlinear dynamic system is proposed. Next, based on the proposed theorem and the inverse optimal approach, an optimal controller synthesis procedure for a TS fuzzy system is given, Also, it is shown that the optimal controller can be found by solving a linear matrix inequality problem. Finally, the proposed method is applied to the attitude control of a rigid spacecraft to demonstrate its validity.

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Observer-Based Output-feedback Sampled-Data Controlling the Singularly Perturbed Takagi-Sugeno Fuzzy Model (특이섭동 타카기 수게노 퍼지모델의 관측기기반 - 출력궤환 샘플치제어)

  • Kang, Hyoung Bin;Moon, Ji Hyun;Lee, Ho Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.9
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    • pp.679-685
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    • 2016
  • This paper addresses an observer-based output-feedback sampled-data controller design problem for nonlinear systems in Takagi-Sugeno (T-S) form including singular perturbations. The design condition is represented in terms of linear matrix inequalities. The separation principle is also investigated.

LMI-Based Design of Fuzzy Controllers for Takagi-Sugeno Fuzzy Systems

  • Kim, Jinsung;Park, Jooyoung;Park, Daihee
    • Proceedings of the Korean Institute of Intelligent Systems Conference
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    • 1998.06a
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    • pp.326-330
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    • 1998
  • There have been several recent studies concerning the stability of fuzzy control systems and the synthesis of stabilizing fuzzy controller. This paper reports on a related study of the TS(Takagi-Sugeno) fuzzy systems, and it is shown that the controller synthesis problems for the nonlinear systems described by the TS fuzzy model can be reduced to convex problems involving LMIs(Linear matrix inequalities). After classifying the TS fuzzy systems into two families based on how diverse their input matrices are, different controller synthesis procedure is given for each of these families. A numerical example is presented to illustrate the synthesis procedures developed in this paper.

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Robust ℋ Sampled-Data Control for Takagi-Sugeno Fuzzy Model with Singular Perturbation (특이섭동 타카기-수게노 퍼지모델의 강인 ℋ 샘플치 제어)

  • Kang, Hyoung Bin;Moon, Ji Hyun;Lee, Ho Jae
    • The Transactions of The Korean Institute of Electrical Engineers
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    • v.65 no.9
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    • pp.1524-1530
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    • 2016
  • This paper deals with a robust $H_{\infty}$ sampled-data controller design problem for nonlinear systems in Takagi-Sugeno fuzzy form with singular perturbation. The employed controller takes a state-feedback form. The design condition is represented in terms of linear matrix inequalities. A numerical examples is included to show the effectiveness of the theoretical development.

Evolutionary design of Takagi-Sugeno type fuzzy model for nonlinear system identification and time series

  • Kim, Min-Soeng;Lee, Ju-Jang
    • 제어로봇시스템학회:학술대회논문집
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    • 2001.10a
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    • pp.93.1-93
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    • 2001
  • An evolutionary approach for the design of Fuzzy Logic Systems(FLSs) is proposed. Membership functions(MFs) in Takagi-Sugeno type fuzzy logic system is optimized through evolutionary process. Output singleton values are obtained through pseudo-inverse method. The proposed technique is unique for that, to prevent overfilling phenomenon, limited-level RBF membership functions are used and the new fitness function is invented. To show the effectiveness of the proposed method, some simulations results on model identification are given.

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Design of T-S Fuzzy-Model-Based Controller for Control of Autonomous Underwater Vehicles (무인 잠수정의 심도 제어를 위한 T-S 퍼지 모델 기반 제어기 설계)

  • Jun, Sung-Woo;Kim, Do-Wan;Lee, Ho-Jae
    • Journal of the Korean Institute of Intelligent Systems
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    • v.21 no.3
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    • pp.302-306
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    • 2011
  • This paper presents Takagi-Sugeno (T-S) fuzzy-model-based controller for depth control of autonomous underwater vehicles(AUVs). Through sector nonlinearity methodology, The nonlinear AUV is represented by T-S fuzzy model. By using the Lyapunov function, the design condition of controller is derived to guarantee the performance of depth control in the format of linear matrix inequality (LMI). An example is provided to illustrate the effectiveness of the proposed methodology.

An Indirect Model Reference Adaptive Fuzzy Control for SISO Takagi-Sugeno Model

  • Cho, Young-Wan;Park, Chang-Woo;Lee, Ki-Chul;Park, Mignon
    • Transactions on Control, Automation and Systems Engineering
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    • v.3 no.1
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    • pp.32-42
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    • 2001
  • In this paper, a parameter estimator is developed for the plant model whose structure is represented by the Takagi-Sugeno model. The essential idea behind the on-line estimation is the comparison of the measured stated with the state of an estimation model whose structure is the same as that of the parameterized model. Based on the parameter estimation scheme, and indirect Model Reference Adaptive Fuzzy control(MRAFC) scheme is proposed to provide asymptotic tracking of a reference signal for the systems with uncertain for slowly time-varying parameters. The developed control law and adaptive law guarantee the boundedness of all signals in the closed-loop systems. In addition, the plant state tracks the state of the reference model asymptotically with time for any bounded reference input signal.

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Fuzzy Formation Controlling Phugoid Model-Based Multi-Agent Systems (장주기모델로 구성된 다개체시스템의 퍼지 군집제어)

  • Moon, Ji Hyun;Lee, Jaejun;Lee, Ho Jae
    • Journal of Institute of Control, Robotics and Systems
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    • v.22 no.7
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    • pp.508-512
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    • 2016
  • This paper discusses a Takagi-Sugeno (T-S) fuzzy controller design problem for a phugoid model-based multi-agent system. The error between the state of a phugoid model and a reference is defined to construct a multi-agent system model. A T-S fuzzy model of the multi-agent system is built by introducing a nonlinear controller. A fuzzy controller is then designed to stabilize the T-S fuzzy model, where the synthesis condition is represented in terms of linear matrix inequalities.

Fuzzy Variable Structure Control of Wheel-Driven Inverted Pendulum (바퀴구동 도립진자에 대한 퍼지 가변구조제어)

  • Yoo Byung-Kook
    • Journal of the Institute of Convergence Signal Processing
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    • v.5 no.4
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    • pp.301-307
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    • 2004
  • This paper suggests a fuzzy variable structure control scheme for Takagi-Sugeno(T-S) fuzzy model and presents the attitude control of the wheel-driven inverted pendulum(WDIP) based on the proposed control algorithm. The proposed controller is designed based on the T-S fuzzy modeling of nonlinear system and the unification of gain matrices in linear subsystems that constitute the overall fuzzy model. The uncertainties generated in the gain matrix unifying procedure can be interpreted as the input disturbances of the conventional variable structure control. These unifying disturbances can be resolved by using the robustness property of the conventional variable structure system. Design example for wheel-driven inverted pendulum demonstrates the utility and validity of the proposed control scheme.

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T-S Fuzzy Model-based Waypoints-Tracking Control of Underwater Vehicles (무인잠수정의 T-S 퍼지 모델기반 경로점 유도제어)

  • Kim, Do-Wan;Lee, Ho-Jae;Sur, Joo-No
    • Journal of Institute of Control, Robotics and Systems
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    • v.17 no.6
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    • pp.526-530
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    • 2011
  • This paper presents a new fuzzy model-based design approach for waypoints-tracking control of nonlinear underwater vehicles (UUVs) on a horizontal plane. The waypoints-tracking control problem is converted into the stabilization one for the error model between the given nonlinear UUV and the waypoints. By using the sector nonlinearity, the error model is modeled in Takagi-Sugeno's form. We then derive stabilization conditions for the error model in the format of linear matrix inequality. A numerical simulation is provided to illustrate the effectiveness of the proposed methodology.