【摘要】：在遙操作系統(tǒng)中,由于遠(yuǎn)距離或?qū)嵤┯邢薜臄?shù)據(jù)傳輸,會(huì)導(dǎo)致大量的時(shí)延,并且,通常時(shí)延的反饋信號(hào)會(huì)產(chǎn)生主機(jī)器人和從機(jī)器人之間的位置和力跟蹤誤差,從而影響系統(tǒng)的整體穩(wěn)定性。同時(shí),遙操作系統(tǒng)存在系統(tǒng)模型不確定項(xiàng),如:時(shí)延、系統(tǒng)動(dòng)力學(xué)參數(shù)不確定項(xiàng)、未知的外部干擾、以及未知的主、從機(jī)器人各關(guān)節(jié)的內(nèi)部摩擦等,這會(huì)也會(huì)大大的降低遙操作系統(tǒng)的透明性,甚至引起系統(tǒng)不穩(wěn)定。針對(duì)上述問(wèn)題。本文在有固定時(shí)延條件下,基于自適應(yīng)控制和神經(jīng)網(wǎng)絡(luò)其他智能控制方法,以有效地改善系統(tǒng)動(dòng)態(tài)的跟蹤性能、穩(wěn)定性和透明性為目標(biāo),本文采用位置誤差(Position Error Based,PEB)遙操作控制結(jié)構(gòu),設(shè)計(jì)了多個(gè)時(shí)延力反饋遙操作系統(tǒng)雙邊控制器。本文的主要研究?jī)?nèi)容可以總結(jié)為:(1)針對(duì)遙操作系統(tǒng)具有動(dòng)力學(xué)參數(shù)不確定性和時(shí)延的問(wèn)題,本文采用了一種基于PEB控制結(jié)構(gòu)的自適應(yīng)控制方法,與傳統(tǒng)的自適應(yīng)雙邊控制器算法,該方法對(duì)動(dòng)力學(xué)參數(shù)不確定值的估計(jì)更加接近真實(shí)值,且具有更好的系統(tǒng)跟蹤性能。(2)考慮遙操作系統(tǒng)存在未知的外部干擾、主-從機(jī)器人機(jī)械內(nèi)部摩擦,以及時(shí)延,基于Lypunov直接法設(shè)計(jì)了一種基于模型逼近的神經(jīng)網(wǎng)絡(luò)自適應(yīng)控制方法,并融入到PEB遙操作控制結(jié)構(gòu)中。仿真實(shí)驗(yàn)結(jié)果表明該方法能夠有效地應(yīng)用到具有未知外部干擾和機(jī)器人各個(gè)關(guān)節(jié)內(nèi)部摩擦的復(fù)雜的遙操作系統(tǒng)模型上,并具有良好的跟蹤性能。(3)為了使遙操作系統(tǒng)更具有實(shí)際意義,有必要對(duì)遙操作系統(tǒng)跟蹤誤差收斂時(shí)間進(jìn)行有效控制,在PEB遙操作控制結(jié)構(gòu)中,基于終端滑�？刂婆c自適應(yīng)控制,設(shè)計(jì)了一種連續(xù)有限時(shí)間收斂的自適應(yīng)終端滑模雙邊控制方法,解決了這一問(wèn)題。仿真實(shí)驗(yàn)結(jié)果表明該方法確實(shí)在收斂時(shí)間上得到了提高,但是與前一個(gè)方法相比,跟蹤誤差精度略有降低。(4)成功將本文所設(shè)計(jì)的研究方法應(yīng)用于主、從機(jī)器人都為兩自由度兩連桿機(jī)械臂,存在固定通信通道時(shí)延的遙操作系統(tǒng)仿真平臺(tái)上,實(shí)驗(yàn)結(jié)果說(shuō)明本文所設(shè)計(jì)的方法的具有良好的實(shí)際控制性能。
[Abstract]:In teleoperation systems, long distance or limited data transmission can lead to a large number of delays, and the feedback signals of delay usually produce position and force tracking errors between the master robot and slave robot. Thus, the overall stability of the system is affected. At the same time, there are uncertainties in the system model, such as time delay, uncertain dynamic parameters of the system, unknown external interference, and internal friction of the joints of the unknown master and slave robot, etc. This will also greatly reduce the transparency of the remote operating system, and even lead to system instability. In response to the above problems. In this paper, based on adaptive control and other intelligent control methods based on neural network, the dynamic tracking performance, stability and transparency of the system are effectively improved under the condition of fixed delay. The position error (Position Error Based, is adopted in this paper. PEB) telecontrol control structure and design several bilateral controllers of delay force feedback teleoperation system. The main research contents of this paper can be summarized as follows: (1) aiming at the problem of dynamic parameter uncertainty and delay in remote operating system, an adaptive control method based on PEB control structure is adopted in this paper. Compared with the traditional adaptive two-sided controller algorithm, the estimation of the uncertain dynamic parameters is closer to the real value, and it has better tracking performance. (2) considering the unknown external interference in the remote operating system, Based on the Lypunov direct method, a neural network adaptive control method based on model approximation is designed for the internal friction and delay of the master-slave robot, and it is integrated into the PEB teleoperation control structure. The simulation results show that the proposed method can be effectively applied to the complex remote operating system model with unknown external interference and internal friction of each joint of the robot. And has good tracking performance. (3) in order to make the remote operating system more practical significance, it is necessary to effectively control the tracking error convergence time of the remote operating system, in the PEB teleoperation control structure, Based on terminal sliding mode control and adaptive control, a continuous finite time convergent adaptive terminal sliding mode bilateral control method is designed to solve this problem. The simulation results show that the convergence time of the proposed method is improved, but the tracking error accuracy is slightly lower than the previous one. (4) the proposed method is successfully applied to the main method. The robot is a two-link manipulator with two degrees of freedom and there is a fixed communication channel delay on the remote operating system simulation platform. The experimental results show that the method designed in this paper has good practical control performance.
【學(xué)位授予單位】：電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2017
【分類(lèi)號(hào)】：TP242

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