本文選題：自適應(yīng)控制 + 遙操作��； 參考：《昆明理工大學(xué)》2017年碩士論文

【摘要】：近年來,由于人口紅利流失,中國(guó)積極主導(dǎo)經(jīng)濟(jì)發(fā)展轉(zhuǎn)型,境內(nèi)勞力密集的低端制造業(yè)正逐漸轉(zhuǎn)型為技術(shù)密集的高端制造業(yè),因此高度自動(dòng)化的需求水漲船高,帶動(dòng)工業(yè)機(jī)器人研發(fā)水平快速成長(zhǎng)。隨著機(jī)器人產(chǎn)業(yè)的不斷發(fā)展,人們對(duì)機(jī)器人的性能需求也越來越高,研究機(jī)器人的控制問題已經(jīng)成為解決機(jī)器人軌跡精度不精確的有效方法并逐漸成為研究熱點(diǎn)。本課題對(duì)機(jī)器人的運(yùn)動(dòng)控制算法進(jìn)行了深入研究,分別將自適應(yīng)控制策略和未知輸入觀測(cè)器應(yīng)用于機(jī)器人這種典型的非線性系統(tǒng)上,針對(duì)不同應(yīng)用場(chǎng)景分別提出了三種控制策略:(1)單機(jī)械臂的魯棒自適應(yīng)控制。通過引入濾波變換和在自適應(yīng)律中引入泄漏項(xiàng),提出了保證參數(shù)估計(jì)的機(jī)械臂魯棒自適應(yīng)控制方法。分析證明了該算法可以實(shí)現(xiàn)參數(shù)誤差和追蹤誤差的同時(shí)收斂,且具有較強(qiáng)的魯棒性。(2)雙邊遙操作系統(tǒng)的魯棒自適應(yīng)控制。將所提出的單機(jī)械臂自適應(yīng)控制方法拓展到雙邊遙操作系統(tǒng),提出了保證參數(shù)估計(jì)的雙邊遙操作機(jī)械臂魯棒自適應(yīng)控制算法。分析證明所提控制策略可以保證系統(tǒng)在通訊延遲的情況下實(shí)現(xiàn)參數(shù)誤差收斂以及主從狀態(tài)跟隨。(3)基于未知輸入觀測(cè)器的機(jī)械臂運(yùn)動(dòng)控制。通過引入濾波變換,設(shè)計(jì)未知輸入觀測(cè)器觀測(cè)外部干擾及未建模動(dòng)態(tài),并將觀測(cè)出來的估計(jì)值作為控制器前饋預(yù)補(bǔ)償干擾及未建模動(dòng)態(tài)造成的影響。該控制方法的控制設(shè)計(jì)及調(diào)參十分簡(jiǎn)單使用,并且能有效抵抗外部干擾,具有較強(qiáng)的魯棒性。在完成上述理論研究的同時(shí),本課題還進(jìn)行了仿真分析,通過與傳統(tǒng)控制方法比較驗(yàn)證了所提算法的優(yōu)勢(shì)。最后,本課題以自行研制的SCARA(Selective Compliance Assembly Robot Arm選擇順應(yīng)性裝配機(jī)械臂)機(jī)器人為研究對(duì)象,應(yīng)用所提出的控制算法對(duì)其進(jìn)行實(shí)驗(yàn)。實(shí)驗(yàn)結(jié)果驗(yàn)證了所提算法在實(shí)際工程應(yīng)用中的有效性。
[Abstract]:In recent years, as a result of the loss of the population dividend, China has actively led the transformation of economic development, and the labor-intensive low-end manufacturing industry in China is gradually transforming into a technology-intensive high-end manufacturing industry. As a result, the demand for high automation is rising. Drive industrial robot R & D level to grow rapidly. With the development of robot industry, the demand for robot performance is becoming higher and higher. The research on robot control has become an effective method to solve the inaccurate trajectory accuracy of robot and has gradually become a research hotspot. In this paper, the motion control algorithm of the robot is deeply studied, and the adaptive control strategy and the unknown input observer are applied to the typical nonlinear system of the robot. For different application scenarios, robust adaptive control of single manipulator with three control strategies: 1) is proposed. By introducing the filter transform and the leakage term into the adaptive law, a robust adaptive control method for the manipulator is proposed, which guarantees the estimation of the parameters. It is proved that the proposed algorithm can converge at the same time as the parameter error and the tracking error, and has strong robustness. 2) robust adaptive control of the bilateral teleoperation system. The proposed adaptive control method for single manipulator is extended to the bilateral teleoperation system, and a robust adaptive control algorithm for the two-sided telemanipulator is proposed to guarantee parameter estimation. It is proved that the proposed control strategy can guarantee the convergence of the parameter error and the master-slave state following. 3) the manipulator motion control based on the unknown input observer can be guaranteed by the proposed control strategy. The unknown input observer is designed to observe the external disturbance and the unmodeled dynamic by introducing the filter transform, and the estimated values are taken as the influence of the feedforward disturbance and the unmodeled dynamic of the controller. The control design and parameter adjustment of the control method are very simple to use, and can effectively resist external interference, and have strong robustness. At the same time, the simulation analysis is carried out, and the advantages of the proposed algorithm are verified by comparing with the traditional control methods. Finally, the self-developed SCARA(Selective Compliance Assembly Robot Arm (SCARA(Selective Compliance Assembly Robot Arm) robot is used as the research object, and the proposed control algorithm is used to test the robot. Experimental results verify the effectiveness of the proposed algorithm in practical engineering applications.
【學(xué)位授予單位】：昆明理工大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類號(hào)】：TP242

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