• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1998년도 추계학술대회 학술발표 논문집
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• pp.211-217
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• 1998

Many practical control problems for the complex, uncertain or large-scale plants, need to simultaneously achieve a number of objectives, which may conflict or compete with each other. If the conventional optimization methods are applied to solve these control problems, the solution process may be time-consuming and the resulting solution would ofter lose its original meaning of optimality. Nevertheless, the human operators usually performs satisfactory results based on their qualitative and heuristic knowledge. In this paper, we investigate the control strategies of the human operators, and propose a fuzzy model-based multi-objective satisfactory controller. We also apply it to the automatic train operation(ATO) system for the magnetically levitated vehicles(MAGLEV). One of the human operator's strategies is to predict the control result in order to find the meaningful solution. In this paper, Takagi-Sugeno fuzzy model is used to simulated the prediction procedure. Another str tegy is to evaluate the multiple objectives with respect to their own standards. To realize this strategy, we propose the concept of a satisfactory solution and a satisfactory control scheme. The MAGLEV train is a typical example of the uncertain, complex and large-scale plants. Moreover, the ATO system has to satisfy multiple objectives, such as seed pattern tracking, stop gap accuracy, safety and riding comfort. In this paper, the speed pattern tracking controller and the automatic stop controller of the ATO system is designed based on the proposed control scheme. The effectiveness of the ATO system based on the proposed scheme is shown by the experiments with a rotary test bed and a real MAGLEV train.

• 대한전기학회:학술대회논문집
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• 대한전기학회 2001년도 하계학술대회 논문집 D
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• pp.1964-1966
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• 2001

Active Noise control(ANC) is rapidly becoming the most effective way to reduce noises that can otherwise be very difficult and expensive to control. This research presents ANFIS (Adaptive Network Fuzzy Inference System) controller for adaptively noise cancelling in a duct. ANC system generates secondary control sound pressure with same amplitude and with opposite phase as noise to be eliminated. ANFIS controller is trained to optimize its parameters for adaptively cancelling noise. That is ANFIS train its parameters by gradient descent and LSE method so called hybrid method. This paper present ANFIS in active noise control which provides an improvement convergence speed and limitation of linearity condition. It can model nonlinear functions of arbitrary complexity and ANFIS can construct an input-ouput mapping based on both human knowledge in the form of Takagi and Sugeno's fuzzy if-then rules and stipulated input-output data pairs. This paper also shows that the proposed ANFIS active noise control system successfully cancelled noise.

• 한국항해항만학회지
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• 제32권6호
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• pp.459-464
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• 2008

본 논문은 파라미터 변화나 외란이 존재하는 환경에서 컨테이너 크레인의 트롤리 위치와 컨테이너의 흔들림을 효과적으로 제어할 수 있는 모델기반 퍼지제어기를 제안한다. 이를 위해 우선 파라미터 변화에 대응할 수 있는 모델링 기법인 T-S 퍼지모델을 구현하고, 소속함수의 파라미터를 실수코딩 유전알고리즘(RCGA)으로 조정하는 문제를 다룬다. 다음으로 퍼지모델의 각 서브시스템에 대해 LQ 제어기 법을 사용하여 서브제어기를 설계하고, 이렇게 설계된 서브제어기를 ROGA로 조정된 퍼지모델의 소속함수로 퍼지결합하여 제안하는 모델기반 퍼지제어기를 구성한다. 시뮬레이션을 통해 RCGA로 조정된 소속함수를 사용하는 퍼지모델은 컨테이너 크레인의 비선형 모델의 출력에 잘 추종하였고, 모델기반 퍼지제어기도 파라미터 변화와 외란이 존재하는 환경에서 강인한 제어를 수행하고 있음을 확인하였다.

• Journal of Power Electronics
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• 제14권3호
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• pp.444-457
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• 2014

This paper presents the design and realization of a digital PV simulator with a Push-Pull Forward (PPF) circuit based on the principle of modular hardware and configurable software. A PPF circuit is chosen as the main circuit to restrain the magnetic biasing of the core for a DC-DC converter and to reduce the spike of the turn-off voltage across every switch. Control and I/O interface based on a personal computer (PC) and multifunction data acquisition card, can conveniently achieve the data acquisition and configuration of the control algorithm and interface due to the abundant software resources of computers. In addition, the control program developed in Matlab/Simulink can conveniently construct and adjust both the models and parameters. It can also run in real-time under the external mode of Simulink by loading the modules of the Real-Time Windows Target. The mathematic models of the Push-Pull Forward circuit and the digital PV simulator are established in this paper by the state-space averaging method. The pole-zero cancellation technique is employed and then its controller parameters are systematically designed based on the performance analysis of the root loci of the closed current loop with $k_i$ and $R_L$ as variables. A fuzzy PI controller based on the Takagi-Sugeno fuzzy model is applied to regulate the controller parameters self-adaptively according to the change of $R_L$ and the operating point of the PV simulator to match the controller parameters with $R_L$. The stationary and dynamic performances of the PV simulator are tested by experiments, and the experimental results show that the PV simulator has the merits of a wide effective working range, high steady-state accuracy and good dynamic performances.