• 한국지능시스템학회논문지
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• 제13권5호
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• pp.564-570
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• 2003

본 논문에서는 동력학이 비선형이고, 상태가 불명확하거나 시간에 따라 변화하는 헬리콥터 시스템의 제어를 위해 TSK 퍼지시스템을 이용한 적응 퍼지제어기 설계 방법을 제안한다. 논문에서 제안한 적응 퍼지제어기는 규범모델의 출력을 시스템의 출력이 추종하도록 퍼지제어기 파라미터를 직접 조정하는 규범모델 적응 퍼지제어기이다 또한 Lyapunov 함수를 이용하여 폐루프 시스템의 안정성을 보장하면서 최적인 적응법칙을 유도하였다. 실험실용 모델 헬리콥터 시스템에 대한 실험에서 시스템에 외란이 가해질 때, 제안되고 설계된 적응 퍼지제어기는 적응이 없는 퍼지제어기에 비해 시스템의 상태변화에 성공적인 제어가 실행됨을 보여주었다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• 제3권1호
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• pp.58-65
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• 2003

In this paper, a new model, which is a Takagi-Sugeno fuzzy model, for mobile robot is presented. A controller, consisting of two loops the one of which is the inner state feedback loop designed for stability and the outer loop is a PI controller designed for tracking the reference input, is suggested. Because the robot dynamics is nonlinear, it requires the controller to be insensitive to the nonlinear term. To achieve this objective, the model is developed by well known T-S fuzzy model. The design algorithm of inner state-feedback loop is regional pole-placement. In this paper, regions, for which poles of the inner state feedback loop are lie in, are formulated by LMI's. By solving these LMI's, we can obtain the state feedback gains for T-S fuzzy system. And this paper shows that the PI controller is equivalent to the state feedback and the cost function for reference tracking is equivalent to the LQ(linear quadratic) cost. By using these properties, it is also shown in this paper that the PI controller can be obtained by solving the LQ problem.

• 제어로봇시스템학회논문지
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• 제22권7호
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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.

• 한국조명전기설비학회지:조명전기설비
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• 제9권6호
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• pp.71-77
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• 1995

This paper deals with design method of learning fuzzy controller for control of an unknown nonlinear plant using the self-tuning algorithm of fuzzy inference rules. In this method the fuzzy identification model obtained that the joined identification model of nonlinear part and linear identification model of linear part by fuzzy inference systems. This fuzzy identification model ordered self-tuning by Decent method so as to be servile to nonlinear plant. A the end, designed learning fuzzy controller of fuzzy identification model have learning structure to model reference adaptive system. The simulation results show that th suggested identification and learning control schemes are practically feasible and effective.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1997년도 추계학술대회 논문집 학회본부
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• pp.130-132
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• 1997

This paper proposes a reference model following control system using fuzzy logic controller and genetic algorithm. A fuzzy logic controller is designed such that plant output follows the output generated by a reference model. In this paper, First-order and second-order reference model with no overshoot and fast rise time is designed. Experiment results show the effectiveness of the proposed controller in tracking property and robustness.

• 대한전기학회:학술대회논문집
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• 대한전기학회 1996년도 하계학술대회 논문집 B
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• pp.974-976
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• 1996

In this paper, a reference model following control system using a fuzzy logic controller(FLC) is proposed By using an integrator and a nonlinear hysteresis element, a reference model whose response has no overshoot and fast rise time is designed. A FLC is designed to follow as close as possible to the response of the reference model. The proposed design method is shown that the robustness and the optimal tracking property can be achieved under modeling error, disturbance and parameter perturbations. The effectiveness of the proposed design method is verified through the simulation that compare using the FLC with using a $H_{\infty}$ controller.

• 한국지능시스템학회논문지
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• 제11권8호
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• pp.771-775
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• 2001

본 논문에서는 유도탄 오토파일롯을 제어하기 위해 T-S 퍼지 모델링을 한 다음 병렬분상이론을 적용하여 적응 퍼지 제어기를 설계한다. 추가적으로 제어기의 파라미터는 기준모델과 출력간의 에러, 스테이트, 기준입력 신호를 이용하여 실시간 업데이트되며, 원 플랜트에 대해 regulation 제어가 성공적으로 해결함을 미사일 모델에 적용한 모의 실험 결과로부터 보인다.

• 전자공학회논문지T
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• 제36T권4호
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• pp.60-70
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• 1999

본 논문에서는 FLC의 적응능력에 대한 단점과 제어규칙 도출의 어려움을 극복하기 위하여 모델기준 적응 퍼지제어기(MRAFC)를 제안하였다. MRAFC는 단순퍼지제어기와 플랜트로 구성된 내부 피드백 루프와 단순 퍼지제어기의 제어규칙을 동조시키는 외부 루프로 구성된다. 기준모델은 기준입력에 대해 전체 제어시스템에 요구되는 제어성능을 특성화하고 수량화하는 퍼지제어기 설계기준으로 사용되었다. 그리고 적응 매카니즘은 FLC 제어규칙을 동조하는 역할을 수행한다. 제안한 알고리즘의 성능은 DC 서보 전동기에 대한 실험에 의해 검증되었다.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2004년도 춘계학술대회 논문집 전기기기 및 에너지변환시스템부문
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• pp.143-146
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• 2004

This paper is proposed adaptive fuzzy-neural network(FNN) controller for speed control of induction motor drive. The design of this algorithm based on FNN controller that is implemented using fuzzy control and neural network. A model reference adaptive scheme is proposed in which the adaptation mechanism is executed by fuzzy logic based on the error and change of error measured between the motor speed and output of a reference model. The control performance of the adaptive FNN controller is evaluated by analysis for various operating conditions.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2009년도 제40회 하계학술대회
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• pp.780_781
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• 2009

This paper proposes efficiency optimization control of IPMSM drive using hybrid intelligent controller(HIC). The design of the speed controller based on fuzzy-neural network that is implemented using fuzzy control and neural network. The design of the current based on adaptive fuzzy control using model reference and the estimation of the speed based on neural network using ANN controller. In order to maximize the efficiency in such applications, this paper proposes the optimal control method of the armature current. The optimal current can be decided according to the operating speed and the load conditions. This paper proposes speed control of IPMSM using ALM-FNN, current control of model reference adaptive fuzzy control(MTC) and estimation of speed using ANN controller. The proposed control algorithm is applied to IPMSM drive system controlled HIC, the operating characteristics controlled by efficiency optimization control are examined in detail.