本文選題：工業(yè)機器人 + 軌跡跟蹤�。� 參考：《深圳大學(xué)》2017年碩士論文

【摘要】：隨著現(xiàn)代工業(yè)發(fā)展速度越來越快,人們格外地重視如何進一步提高工業(yè)生產(chǎn)的效率,所以對工業(yè)機器人的控制性能提出了更高的要求。由于工業(yè)機器人本身的強非線性和耦合特性,使得在工業(yè)機器人控制中存在著很多問題,機器人的軌跡跟蹤控制則是眾多問題中的一個重點。軌跡跟蹤控制的主要目的就是通過給定各關(guān)節(jié)的驅(qū)動力矩,使得機器人的位置、速度等狀態(tài)變量跟蹤給定的理想軌跡[1]。本文從工業(yè)機器人響應(yīng)速度和跟蹤精度兩個方面,對工業(yè)機器人的軌跡跟蹤控制算法進行研究。本文首先分析了工業(yè)機器人的軌跡跟蹤控制在國內(nèi)外的研究現(xiàn)狀。隨后分析了六自由度機器人的運動學(xué)與動力學(xué)問題,然后通過拉格朗日方法建立了機器人的動力學(xué)方程并分析動力學(xué)方程的推導(dǎo)過程,最后對方程進行數(shù)值化簡并仿真驗證。接著分析常規(guī)的軌跡跟蹤控制算法(如PD-重力補償控制、計算力矩法、滑膜變結(jié)構(gòu)控制等),根據(jù)性能要求提出快速變結(jié)構(gòu)算法和模糊變結(jié)構(gòu)算法。前者是通過對變結(jié)構(gòu)控制的趨近律進行優(yōu)化來改善控制效果,后者先利用變結(jié)構(gòu)控制的特性彌補參數(shù)不確定性所帶來的影響,在這個基礎(chǔ)上再利用模糊規(guī)則來調(diào)節(jié)趨近律參數(shù),以削弱變結(jié)構(gòu)控制所帶來的抖振現(xiàn)象。然后利用SOLIDWORKS建立工業(yè)機器人的虛擬樣機模型,再導(dǎo)入到ADAMS進行約束與驅(qū)動的添加,將虛擬樣機模型模塊化后導(dǎo)出到MATLAB中使虛擬樣機模型轉(zhuǎn)化為MATLAB中的一個模塊,從而實現(xiàn)MATLAB與ADAMS的連接,隨后在MATLAB中搭建工業(yè)機器人控制算法的仿真模型,并進行兩者的聯(lián)合仿真。最后以PUMA機器人為控制對象,設(shè)計了相應(yīng)的軌跡跟蹤算法程序,利用聯(lián)合仿真實驗對比來驗證所提兩種算法的可行性。
[Abstract]:With the rapid development of modern industry, people attach great importance to how to further improve the efficiency of industrial production. Due to the strong nonlinear and coupling characteristics of industrial robot, there are many problems in industrial robot control, and the trajectory tracking control of robot is one of the most important problems. The main purpose of trajectory tracking control is to track the given ideal trajectory with the state variables such as the position and velocity of the robot through the given driving torque of each joint. In this paper, the trajectory tracking control algorithm of industrial robot is studied from two aspects: response speed and tracking accuracy. In this paper, firstly, the research status of industrial robot trajectory tracking control at home and abroad is analyzed. Then the kinematics and dynamics of the six-degree-of-freedom robot are analyzed. Then the dynamic equation of the robot is established by Lagrangian method and the derivation process of the dynamic equation is analyzed. Finally the equations are simplified numerically and verified by simulation. Then the conventional trajectory tracking control algorithms, such as PD-gravity compensation control, moment calculation method, synovial variable structure control and so on, are analyzed. The fast variable structure algorithm and fuzzy variable structure algorithm are proposed according to the performance requirements. The former improves the control effect by optimizing the approach law of variable structure control, the latter uses the characteristics of variable structure control to compensate for the influence of parameter uncertainty, and then adjusts the parameters of approach law by using fuzzy rules. In order to weaken the chattering phenomenon caused by variable structure control. Then the virtual prototype model of industrial robot is established by using SOLIDWORKS, then imported into ADAMS to add constraints and drivers, and then the virtual prototype model is modularized and exported to MATLAB to transform the virtual prototype model into a module in MATLAB. In order to realize the connection between MATLAB and ADAMS, the simulation model of industrial robot control algorithm is built in MATLAB, and the joint simulation between the two is carried out. Finally, taking PUMA robot as the control object, the corresponding trajectory tracking algorithm program is designed, and the feasibility of the two algorithms is verified by the comparison of joint simulation experiments.
【學(xué)位授予單位】：深圳大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2017
【分類號】：TP242

【參考文獻(xiàn)】

相關(guān)期刊論文 前4條

1 翟敬梅;康博;唐會華;;工業(yè)機器人軌跡跟蹤的自適應(yīng)模糊變結(jié)構(gòu)算法[J];華南理工大學(xué)學(xué)報(自然科學(xué)版);2012年12期

2 席雷平;陳自力;齊曉慧;;具有抖振抑制特性的機械臂快速滑模變結(jié)構(gòu)控制[J];電機與控制學(xué)報;2012年07期

3 曹文祥;馮雪梅;;工業(yè)機器人研究現(xiàn)狀及發(fā)展趨勢[J];機械制造;2011年02期

4 曾華森;謝存禧;吳向壘;張鐵;;6自由度噴涂機器人的運動學(xué)分析與仿真[J];微計算機信息;2008年26期

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本文編號：1812216