本文選題：陀螺儀　切入點(diǎn)：BP神經(jīng)網(wǎng)絡(luò)　出處：《中北大學(xué)》2017年碩士論文

【摘要】：在四旋翼無人機(jī)控制系統(tǒng)中,姿態(tài)傳感器起到了測量相關(guān)參數(shù)的作用,然后將參數(shù)反饋到控制系統(tǒng)中進(jìn)行姿態(tài)解算,實(shí)現(xiàn)無人機(jī)的姿態(tài)控制。姿態(tài)傳感器作為飛控系統(tǒng)的重要組成部分,它的狀態(tài)將關(guān)系到無人機(jī)的穩(wěn)定飛行,所以對(duì)姿態(tài)傳感器的故障診斷是非常有意義的。本文主要研究工作如下:本文通過比較現(xiàn)有各種故障診斷技術(shù)的優(yōu)勢(shì)與缺陷,并考慮到四旋翼飛行器飛控系統(tǒng)的特性,將BP神經(jīng)網(wǎng)絡(luò)診斷方法應(yīng)用于四旋翼飛行器飛控系統(tǒng)并針對(duì)BP神經(jīng)網(wǎng)絡(luò)的收斂速度慢、精度低等缺點(diǎn),采用遺傳算法進(jìn)行改進(jìn)。將陀螺儀三個(gè)角度輸出作為估計(jì)參數(shù),建立了翻滾角觀測器、俯仰角觀測器和偏航角觀測器,在線估計(jì)陀螺儀輸出。對(duì)于故障類型辨別的問題,本文將故障數(shù)據(jù)與傳感器實(shí)測數(shù)據(jù)進(jìn)行一元線性回歸分析,能夠成功辨別恒增益與恒偏差故障。并提出了雙閾值檢測方法,以提高故障檢測的準(zhǔn)確率。使用的不同訓(xùn)練算法與隱層節(jié)點(diǎn)對(duì)BP神經(jīng)網(wǎng)絡(luò)進(jìn)行訓(xùn)練,以選取最優(yōu)訓(xùn)練算法與隱層節(jié)點(diǎn)數(shù);同時(shí)對(duì)GA-BP網(wǎng)絡(luò)性能進(jìn)行仿真,數(shù)據(jù)表明GA-BP網(wǎng)絡(luò)在收斂速率和精度方面有了明顯提升。在MATLAB仿真平臺(tái)下,進(jìn)行故障檢測和辨別仿真,結(jié)果表明,本文所使用的方法不僅能夠準(zhǔn)確的預(yù)測陀螺儀的輸出,而且雙閾值檢測故障法也能較為準(zhǔn)確的檢測到故障注入點(diǎn),并對(duì)其進(jìn)行標(biāo)記,并且一元線性回歸法也能準(zhǔn)確的辨別故障類型。
[Abstract]:In the four-rotor UAV control system, the attitude sensor acts as a measure of related parameters, and then the parameters are fed back to the control system for attitude calculation. As an important part of flight control system, attitude sensor will affect the steady flight of UAV. So it is very meaningful to fault diagnosis of attitude sensor. The main research work of this paper is as follows: this paper compares the advantages and disadvantages of various fault diagnosis technologies, and takes into account the characteristics of flight control system of four-rotor aircraft. The BP neural network diagnosis method is applied to the flight control system of four-rotor aircraft. The genetic algorithm is used to improve the BP neural network because of its slow convergence speed and low precision. The output of three angles of the gyroscope is taken as the estimation parameter. The roll angle observer, pitch angle observer and yaw angle observer are established to estimate the gyroscope output online. The method of double threshold detection is proposed to improve the accuracy of fault detection. Different training algorithms and hidden layer nodes are used to train BP neural network. In order to select the optimal training algorithm and the number of hidden layer nodes, at the same time, the performance of GA-BP network is simulated. The data show that the convergence rate and precision of GA-BP network have been improved obviously. Under the MATLAB simulation platform, fault detection and discrimination simulation are carried out. The results show that the method used in this paper can not only accurately predict the output of gyroscope, but also detect the fault injection point accurately and mark it. And the linear regression method can also accurately identify the type of fault.
【學(xué)位授予單位】：中北大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：V267;TP183

【參考文獻(xiàn)】

相關(guān)期刊論文 前10條

1 姜曉東;任力;劉銘;李彥;陳平;;基于BP神經(jīng)網(wǎng)絡(luò)的小電流接地故障選線方法[J];山東理工大學(xué)學(xué)報(bào)(自然科學(xué)版);2017年01期

2 蔡志端;王玉龍;王玉玲;荀倩;;基于改進(jìn)型滑模觀測器的逆變器開路故障診斷[J];制造業(yè)自動(dòng)化;2015年19期

3 劉毅娟;雷鳴;何e，

本文編號(hào)：1675595