本文選題：機(jī)器人 + 機(jī)械手臂�。� 參考：《中國(guó)計(jì)量學(xué)院》2015年碩士論文

【摘要】：機(jī)器人不僅要有較高的控制精度,還需要具備碰撞感知能力和柔順性。用氣動(dòng)肌肉驅(qū)動(dòng)的機(jī)器人具有質(zhì)量輕、柔順性和仿生性好等優(yōu)點(diǎn),應(yīng)用前景廣泛。但是氣動(dòng)肌肉具有很多復(fù)雜特性,對(duì)氣動(dòng)肌肉建模、控制以及在其表面安裝傳感器困難。本文主要研究了兩個(gè)問題：一是根據(jù)氣動(dòng)肌肉兩端的差壓信號(hào)感知?dú)鈩?dòng)肌肉徑向碰撞；二是研究氣動(dòng)肌肉關(guān)節(jié)的控制算法。建立了氣動(dòng)肌肉特性測(cè)試平臺(tái),設(shè)計(jì)單自由度氣動(dòng)肌肉關(guān)節(jié),測(cè)試了氣動(dòng)肌肉和關(guān)節(jié)特性。采用二階高斯函數(shù)和三階傅立葉函數(shù)對(duì)原始曲線和遲滯性曲線擬合,得到氣動(dòng)肌肉長(zhǎng)度-氣壓模型；測(cè)試結(jié)果表明氣動(dòng)肌肉及其驅(qū)動(dòng)的關(guān)節(jié)具有很強(qiáng)的非線性和遲滯性,而且會(huì)隨著氣壓、負(fù)載變化而變化。提出根據(jù)氣動(dòng)肌肉兩端差壓信號(hào)感知?dú)鈩?dòng)肌肉徑向碰撞(沖擊)的方法,并與軸向沖擊區(qū)分；基于流體阻抗法,建立了軸、徑向沖擊差壓信號(hào)模型。搭建實(shí)驗(yàn)平臺(tái)和數(shù)據(jù)采集系統(tǒng),通過實(shí)驗(yàn)研究了負(fù)載、沖擊作用、內(nèi)部氣壓、碰撞位置對(duì)差壓信號(hào)的影響；實(shí)驗(yàn)結(jié)果表明相同條件下徑向沖擊作用產(chǎn)生的差壓信號(hào)幅值大于軸向,軸向相頻曲線變化雜亂,徑向相頻曲線有周期性變化規(guī)律。四種因素會(huì)改變差壓信號(hào)的幅值,但不會(huì)改變相頻曲線的變化規(guī)律。采用自相關(guān)函數(shù)法提取相頻曲線的周期性特征,實(shí)現(xiàn)了軸、徑向沖擊區(qū)分。設(shè)計(jì)了改進(jìn)的神經(jīng)元PID控制算法,用Sigmoid函數(shù)定義神經(jīng)元PID控制算法的增益系數(shù),提高了控制算法的自適應(yīng)性,并在參數(shù)學(xué)習(xí)過程中添加衰減因子來提高參數(shù)學(xué)習(xí)的收斂速度。針對(duì)氣動(dòng)肌肉充、放氣過程中表現(xiàn)出來的遲滯性,設(shè)計(jì)了雙層結(jié)構(gòu)的MFA-DSCMAC (Model Free Adaptive-Double Structure Cerebellar Model Articulation Controller)控制算法,對(duì)充、放氣過程分別進(jìn)行學(xué)習(xí),從而有效地補(bǔ)償了遲滯性；設(shè)計(jì)誤差可信度評(píng)估函數(shù)來調(diào)整學(xué)習(xí)率,抑制突發(fā)干擾對(duì)神經(jīng)網(wǎng)絡(luò)學(xué)習(xí)的破壞。搭建了一個(gè)五自由度機(jī)械手臂,基于工控機(jī)和C++軟件建立控制系統(tǒng),采用串聯(lián)的關(guān)節(jié)控制算法控制機(jī)械手臂完成倒水作業(yè)。
[Abstract]:The robot should not only have high control precision, but also have collision sensing ability and flexibility.The robot driven by pneumatic muscle has many advantages, such as light weight, flexibility and good bionics.But pneumatic muscle has many complex characteristics, it is difficult to model, control and install sensors on the surface of pneumatic muscle.This paper mainly studies two problems: one is to perceive radial collision of pneumatic muscle according to the differential pressure signal at both ends of pneumatic muscle; the other is to study the control algorithm of pneumatic muscle joint.The pneumatic muscle characteristic test platform is established, and the single degree of freedom pneumatic muscle joint is designed, and the pneumatic muscle and joint characteristics are tested.By using the second-order Gao Si function and the third-order Fourier function to fit the original curve and the hysteresis curve, the length pressure model of the pneumatic muscle is obtained, and the test results show that the pneumatic muscle and its actuated joints have strong nonlinearity and hysteresis.And it changes with the pressure and the load.A method for sensing radial impact (shock) of pneumatic muscle based on differential pressure signals at both ends of pneumatic muscle is proposed, which is distinguished from axial impact, and a model of differential pressure signal for axial and radial impact is established based on fluid impedance method.The experiment platform and data acquisition system are built, and the effects of load, impact, internal pressure and collision position on differential pressure signal are studied experimentally.The experimental results show that the amplitude of differential pressure signal produced by radial shock is larger than that of axial direction, the axial phase frequency curve is chaotic, and the radial phase frequency curve has periodic variation rule.Four factors will change the amplitude of differential pressure signal, but will not change the law of phase frequency curve.The periodic characteristic of phase frequency curve is extracted by autocorrelation function method.The improved neural PID control algorithm is designed, and the gain coefficient of the neural PID control algorithm is defined by Sigmoid function, which improves the self-adaptability of the control algorithm, and the attenuation factor is added in the process of parameter learning to improve the convergence rate of the parameter learning.Aiming at the hysteresis in the process of pneumatic muscle filling and exhalation, a double-layer MFA-DSCMAC model Free Adaptive-Double Structure Cerebellar Model Articulation controller is designed, which can be used to study the process of filling and discharging respectively, thus compensating the hysteresis effectively.The error reliability evaluation function is designed to adjust the learning rate and to suppress the damage to the learning of neural network caused by burst interference.A control system based on industrial computer and C software is set up for a five-degree-of-freedom manipulator, and a series joint control algorithm is used to control the robot arm to complete the operation of pouring water.
【學(xué)位授予單位】：中國(guó)計(jì)量學(xué)院
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2015
【分類號(hào)】：TH138;TP242

【相似文獻(xiàn)】

相關(guān)期刊論文 前10條

1 王月權(quán);;精煉系統(tǒng)差壓泵的應(yīng)用[J];小氮肥;2009年02期

2 方立德;盧慶華;李小亭;張計(jì)科;何青;張W，

本文編號(hào)：1761432