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검색결과 1,144건 처리시간 0.035초

Toward Establishment of Japan-Korea Long-Term Forest Hydrological Research Network

  • Otsuki, Kyoichi;Ogawa, Shigeru;Kume, Atsushi;Kumagai, Tomo'omi
    • 한국수자원학회:학술대회논문집
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    • 한국수자원학회 2002년도 학술발표회 논문집(I)
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    • pp.51-58
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    • 2002

  • In this paper, the status of forest and forestry together with the trend of forest hydrology in Japan are firstly overviewed for the mutual understanding between the Japan Society of Hydrology and Water Resources (JSHWR) and the Korean Water Resources Association (KWRA). Then, Long-Term Ecological Research recently introduced in Asia is briefly explained, and the establishment of Japan-Korea Long-Term Forest Hydrological Research Network is proposed.

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A Simple Robust Tracking Controller for Robot Manipulators Using Joint Position Measurements Contaminated by Noises

  • Wada, Makoto;Oya, Masahiro;Sagara, Shinichi;Kobayashi, Toshihiro
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 2001년도 ICCAS
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    • pp.147.2-147
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    • 2001

  • In this paper we develop a new robust trajectory tracking control scheme without using joint velocity. The proposed controller doesn´t employ adaptation, Therefore, the construction of the controller becomed very simple. Moreover, by using numerical simulation, we make sure the effectiveness of the proposed controller in the presence of quantization errors.

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An Optimization Method Wsing Simulated Annealing for Universal Learning Network

  • Murata, Junichi;Tajiri, Akihito;Hirasawa, Kotaro;Ohbayashi, Masanao
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.183-186
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    • 1995

  • A method is presented for optimization of Universal Learning Networks (ULN), where, together with gradient method, Simulated Annealing (SA) is employed to elude local minima. The effectiveness of the method is shown by its application to control of a crane system.

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Neural network structure design using genetic algorithm

  • Murata, Junichi;Tanaka, Kei;Koga, Masaru;Hirasawa, Kotaro
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1995년도 Proceedings of the Korea Automation Control Conference, 10th (KACC); Seoul, Korea; 23-25 Oct. 1995
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    • pp.187-190
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    • 1995

  • A method is proposed which searches for optimal structures of Neural Networks (NN) using Genetic Algorithm (GA). The purpose of the method lies in not only finding an optimal NN structure but also leading us to the goal of self-organized control system that acquires its structure and its functionality by itself depending on its environment.

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Control of a magnetic levitation system via feedback error learning

  • Hao, Shuang-Hui;Yang, Zi-Jiang;Tsuji, Teruo
    • 제어로봇시스템학회:학술대회논문집
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    • 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국제학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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    • pp.345-350
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    • 1993

  • This paper presents an on-line feedback error learning control algorithm for a magnetic levitation system. It will be shown that even in the case of abrupt changes of the system parameters and disturbanes, the control performance is still very satisfactory.

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