本文關(guān)鍵詞：多鰭機器魚仿生協(xié)調(diào)控制及推進性能研究　出處：《中國科學技術(shù)大學》2017年碩士論文　論文類型：學位論文

  更多相關(guān)文章： 雙尾鰭機器魚 中樞模式發(fā)生器 水動力模型 運動控制 快速推進

【摘要】：魚類運動的研究給機器魚設(shè)計及發(fā)展提供了豐富的靈感來源。魚類的表現(xiàn)能夠提供一系列復雜的運動設(shè)計,涉及到用于產(chǎn)生運動力的多樣性的結(jié)構(gòu)和與水生環(huán)境相互作用的多用途的運動模式。在復雜、不確定的水下環(huán)境中,水下機器魚能出色地完成湖海探測等有著重要應(yīng)用前景的任務(wù)。由于具有機動性強、智能化高、適應(yīng)性強和安全性好等優(yōu)勢,智能機器魚已經(jīng)逐漸成為完成水下任務(wù)的重要工具。神經(jīng)生物學家研究表明,魚類游動所涉及的有節(jié)律的活動是由在脊椎層面的中央模式發(fā)生器所產(chǎn)生的,其本質(zhì)上可以看做是一個非線性振蕩神經(jīng)元產(chǎn)生的強大的網(wǎng)絡(luò),能夠在沒有頂層有節(jié)律的輸入的情況下產(chǎn)生有節(jié)律的輸出。本文設(shè)計了兩款新穎的雙尾鰭機器魚,在保持快速游動的優(yōu)勢之外,大大消除了單尾鰭機器魚在前進時左右搖晃的弊端。第一代機器魚研究重點主要在于用CPG控制網(wǎng)絡(luò)實現(xiàn)其各種機動動作的平滑過渡,而對于第二代雙尾鰭機器魚的重點則在于建立一個可靠高效的水動力學建模。本論文的的主要研究內(nèi)容及成果如下所示:(1)雙尾鰭機器魚的系統(tǒng)設(shè)計。在結(jié)合多矢量推進的胸鰭和雙尾鰭的基礎(chǔ)上,設(shè)計了第一代雙尾鰭機器魚DualFish-Ⅰ,其靠前的胸鰭負責胸鰭前進后退及其他機動動作,而尾鰭則負責快速巡航。與第一代機器魚不同,第二代機器魚DualFish-Ⅱ采用單一大功率Maxon電機控制兩個尾鰭能夠精確同步相向擺動,實驗最高頻率能夠達到6Hz,滿足設(shè)計要求。(2)CPG神經(jīng)控制網(wǎng)絡(luò)的建立。從原始的神經(jīng)元振蕩方程開始,詳細的推導了CPG控制網(wǎng)絡(luò)模型的構(gòu)建,并結(jié)合第一代雙尾鰭機器魚DualFish-I的運動特性,建立了與之相匹配的神經(jīng)控制網(wǎng)絡(luò),最后將獲取的紅外傳感器反饋模擬量轉(zhuǎn)換為距離值,傳遞給CPG控制網(wǎng)絡(luò)中的反饋部分,初步實現(xiàn)機器魚在垂直面的自主避障功能。(3)水動力學建模。以剛性分段理論為基礎(chǔ),結(jié)合無粘性和無壓縮性的準穩(wěn)態(tài)的假設(shè),對剛性和柔性單尾鰭進行了充分的理論建模,初步獲得柔性尾鰭在若干擺動周期內(nèi)的推進力。(4)雙尾鰭機器魚的機動性能及推進性能實驗測試。以雙尾鰭機器魚DualFish-Ⅰ和DualFish-Ⅱ為實驗對象,開展了各種機動性能(前進后退、上浮下潛、翻滾轉(zhuǎn)彎和前后空翻等)測試實驗以及快速推進性能實驗,在選用較小功率的舵機情況下,第一代機器魚具有非常出色的高速特性,使用雙尾鰭擺動推進的最高速度能夠達到0.54 m/s,約1.21BL/s,而用胸鰭推進所達到的最高巡航速度可達0.35m/s,約0.8BL/s。第二代雙尾鰭機器魚具有較高的加速性能,最大加速度約能達到0.7m/s2,同時DualFish-Ⅱ還具有非常好的巡航速度,最高速度能達到0.7m/s,約1.59BL/s;
[Abstract]:The study of fish movement provides a rich source of inspiration for the design and development of robotic fish. The performance of fish can provide a series of complex motion designs, involving the structure of multiple structures for generating exercise force and the multipurpose sports mode of interaction with aquatic environment. In the complex and uncertain underwater environment, the underwater machine fish can accomplish the important application of the lake and sea exploration. Because of its advantages of strong mobility, high intelligence, strong adaptability and good security, intelligent machine fish has gradually become an important tool to accomplish underwater tasks. The research shows that neurobiologist, fish swimming involved rhythmic activity is generated by the central pattern generator in spinal level, its essence can be regarded as a nonlinear oscillation neurons produce a strong network, can output the rhythm in no top rhythmic input case. This paper designs two new type of double tail fin robot fish, which keeps away from the advantages of fast swimming. It greatly eliminates the disadvantages of the single fin fin robot fish swaying in advance. The first generation of robotic fish research focuses on the smooth transition of all kinds of maneuverability by CPG control network. For the second generation of double fin fin robot fish, the key is to establish a reliable and efficient hydrodynamic modeling. The main contents and results of this paper are as follows: (1) the system design of double caudal fin machine fish. On the basis of the vectored thruster pectoral fins and double tail fin on the design of the first generation of twin skeg robotic fish DualFish- 1, the front of the pectoral fin of pectoral fin and other responsible for forward and backward maneuver, and the tail is responsible for fast cruise. Unlike the first generation of robotic fish, the second generation of robot fish DualFish- II uses a single high power Maxon motor to control two caudal fin, which can synchronize accurately and swing. The highest frequency of experiment can reach 6Hz, which meets the design requirements. (2) the establishment of CPG neural control network. From the beginning of neuronal oscillations of the original equations, detailed derivation of the CPG construction control network model, and combined with the motion characteristics of the first generation of twin skeg robotic fish DualFish-I, built to match the neural network control, infrared sensor will obtain the final feedback analog to the distance value passed to the feedback part of CPG control network in the initial implementation of fish robot autonomous obstacle avoidance function in vertical plane. (3) hydrodynamic modeling. Based on rigid segmentation theory, combined with the assumption of quasi steady state without viscosity and non compressibility, a rigid and flexible single fin fin is fully modeled, and the propulsion force of flexible tail fin in some swing periods is preliminarily obtained. (4) experimental test on the maneuverability and propelling performance of the double caudal fin machine fish. The double tail fin machine fish DualFish- I and DualFish- II as the experimental object, to carry out a variety of motor performance (forward and backward, up and down, tumbling and turning backflips etc.) test and the rapid advance of performance test in the steering gear with small power under the situation, the first generation of robotic fish with excellent characteristics of high speed, using the highest speed double caudal fin propulsion can reach 0.54 m/s, about 1.21BL/s, the maximum cruising speed of up to 0.35m/s and pectoral fin reached about 0.8BL/s. Accelerate the performance of the second generation of twin skeg robotic fish is high, the maximum acceleration can reach about 0.7m/s2, while DualFish- II also has a very good cruise speed, can reach a maximum speed of 0.7m/s, about 1.59BL/s;
【學位授予單位】：中國科學技術(shù)大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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相關(guān)期刊論文 前3條

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3 George V.Lauder;Peter G.A.Madden;;Learning from Fish: Kinematics and Experimental Hydrodynamics for Roboticists[J];International Journal of Automation and Computing;2006年04期

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本文編號：1343872