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Please use this identifier to cite or link to this item: http://ntour.ntou.edu.tw:8080/ir/handle/987654321/35726

Title: 最佳化演算法結合滑動模式控制於飛機降落系統之應用
Applications of Optimization Algorithms and Sliding Mode Control to Aircraft Landing System
Authors: Shuai-Ting Yu
余帥廷
Contributors: NTOU:Department of Communications Navigation and Control Engineering
國立臺灣海洋大學:通訊與導航工程學系
Keywords: 小腦模型控制器;滑動模式控制;基因演算法;粒子群演算法;渾沌粒子群演算法
CMAC;SMC;GA;PSO;CPSO
Date: 2013
Issue Date: 2013-10-07T02:58:18Z
Abstract: 美國國家運輸安全委員會在1950至2010年間的研究調查指出,平均有28%的飛安意外事件是因天候造成。飛機在起飛以及降落的時候一直都是飛航安全意外事故中最重要的一部分。航機在進場或落地階段,因為在高度不高及速度不快的情況下,一但遇到剪風或亂流等大氣的劇烈變化,會造成飛機航向及下滑軌跡的偏移,嚴重影響飛航安全。現今大部分的飛機上都已安裝有自動降落系統,能夠在正常的飛航環境中安全地幫助飛行器自動降落,並明顯的減輕飛行員的工作負擔。傳統的自動著陸系統所採用的控制理論為增益預定或傳統適應控制的技術,一旦飛行條件或風擾強度超出系統所能適應之範圍,飛行員就必須關閉自動著陸系統改由手動駕駛接管飛機著陸程序。本論文應用小腦模型控制器以及滑動模式控制器於飛機著陸控制,結合基因演算法、粒子群演算法和渾沌粒子群演算法調整滑動模式控制的控制參數,而提出的控器架構不僅可以有效的提升智慧型系統對抗風擾的性能,還可以幫助飛行員引導飛機安全的降落在惡劣的環境下。另外,本論文並利用李亞普諾夫理論去推導出最佳化學習律。本文進一步以TMS320C6713 DSP 開發工具,連結JTAG,利用CCS編譯完成的程式碼載入至DSP的快閃記憶體,實現浮點DSP控制器的即時自動著陸系統。
According to a survey of the National Transportation Safety Board, 28% of aircraft accidents in the years of 1950 to 2010 were weather related. Aircraft takeoff and landing has always been the most important part of aviation safety. In the approach or landing stage, aircraft altitude and speed are low, dramatic changes of atmosphere, such as the wind shear or turbulence, will cause the aircraft off heading and glide path, and seriously affect the flight safety. Nowadays most aircraft have been installed automatic landing system. In the normal environment, aircraft automatic landing system can significantly reduce the pilot's workload. Conventional automatic landing systems are designed by the use of gain scheduling or traditional adaptive control techniques, once the flight conditions or wind disturbance intensity is beyond the limits of the system, the pilot must turn off the automatic landing system and take over the aircraft landing procedures manually. The purpose of this thesis is to apply Cerebellar Model Articulation Controller (CMAC) and Sliding Mode Control (SMC) to aircraft landing control, combined with genetic algorithm (GA), particle swarm optimization (PSO) and chaotic particle swarm optimization (CPSO) which are used to adjust parameters of Sliding Mode Control. The proposed intelligent control scheme not only can effectively improve the intelligent systems to against the wind disturbance, but also can help the pilots guide the aircraft to a safe landing in difficult environment. In addition, Lyapunov theory is utilized to derive the optimal learning rule. The proposed intelligent control scheme can help the pilots guide the aircraft to a safe landing in difficult environment. Furthermore, the TMS320C6713 DSP development tools, links, JTAG, CCS compiled code flash memory are applied to achieve real-time automatic landing system by the floating-point DSP controller.
URI: http://ethesys.lib.ntou.edu.tw/cdrfb3/record/#G0010067007
http://ntour.ntou.edu.tw/handle/987654321/35726
Appears in Collections:[通訊與導航工程學系] 博碩士論文

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