夜視型自主式群組校園巡邏機器人之研究--子計畫二：基於Petri net理論之群組夜間巡邏機器人之分散式系統

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dc.contributor國立臺灣師範大學電機工程學系zh_tw
dc.contributor.author王偉彥zh_tw
dc.contributor.author黃義盛zh_tw
dc.date.accessioned2014-10-30T09:28:26Z
dc.date.available2014-10-30T09:28:26Z
dc.date.issued2012-07-31zh_TW
dc.description.abstract本計畫中，我們針對某一類主動式移動機器人系統，提出了一個使用混合式直接/間接適應性派屈模糊類神經網路之線上路徑追蹤控制器設計。此新穎的方法包含控制目的的決定、近似器的架構、系統動態的模組化、線上控制演算法的發展與系統穩定性的分析。根據模型資訊與控制資訊的重要性，我們使用一個權重因子去結合直接型與間接型的適應性派屈模糊類神經網路控制器。因此，控制器的設計方法在設計的過程中將更加有彈性。此外，我們使用李普諾夫理論去確認整個系統的穩定性。模擬的結果驗證了我們所提出的方法可以達到適合的追蹤效能。zh_tw
dc.description.abstractIn this project, we proposed a path-tracking controller design for a class of autonomous mobile robot system using hybrid direct/indirect adaptive Petri-fuzzy-neural network. This novel approach consists of control objectives determination, approximator configuration design, system dynamics modeling, online control algorithm development, and system stability analysis. According to the importance and viability of plant knowledge and control knowledge, a weighting factor is utilized to sum together the direct and indirect adaptive FNN controllers. Therefore, the controller design methodology is more flexible during the design process. Moreover, the stability of the whole system can be verified by using Lyapunov theory. Simulation results illustrate that the proposed method can achieve favorable tracking performance.en_US
dc.identifierntnulib_tp_E0604_04_003zh_TW
dc.identifier.urihttp://rportal.lib.ntnu.edu.tw/handle/20.500.12235/32074
dc.languagechizh_TW
dc.publisher行政院國家科學委員會zh_tw
dc.relation〈行政院國家科學委員會專題研究計畫，NSC100-2221-E-003-007〉zh_tw
dc.subject.other派屈模糊類神經網路zh_tw
dc.subject.other主動式移動機器人zh_tw
dc.subject.other路徑追蹤控制zh_tw
dc.subject.otherPetri-fuzzy-neural networken_US
dc.subject.otherautonomous mobile roboten_US
dc.subject.otherpath-tracking controlen_US
dc.title夜視型自主式群組校園巡邏機器人之研究--子計畫二：基於Petri net理論之群組夜間巡邏機器人之分散式系統zh_tw

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