本文關鍵詞：六自由度并聯(lián)機器人的運動控制與研究　出處：《新疆大學》2017年碩士論文　論文類型：學位論文

  更多相關文章： 并聯(lián)機構 位置正反解 極端學習機 軌跡規(guī)劃 魯棒自適應控制策略

【摘要】：并聯(lián)機構相對于串聯(lián)機構來說,它是一種全新的結構,其優(yōu)勢在于具有很大的剛度,非常高的精度,很強的承載能力,容易實現(xiàn)控制等等。在結構和性能上與應用廣泛的串聯(lián)機構形成對偶關系,在應用上形成互補關系,大大擴展了機器人的應用范圍。并聯(lián)機構是一個復雜系統(tǒng),其具有多自由度、多輸入和多輸出、非線性程度較高、多參數(shù)、強耦合的特點,還有很多問題還需要進一步的研究和完善。本文詳細介紹了六自由度(Six Degrees of Freedom,6-DOF)并聯(lián)機構的運動學,即對并聯(lián)機構的位置進行正反解計算,分析平臺運動的速度和加速度。利用位置反解求得大量的輸入輸出數(shù)據(jù)組,把這些數(shù)據(jù)組作為極端學習機的網絡訓練樣本,應用極端學習機算法求解位置正解,實現(xiàn)并聯(lián)機構輸入位移與輸出位姿的非線性映射,進而可求解出與輸入位移對應的輸出位姿,并采用Matlab軟件對極端學習機方法進行仿真驗證。在運動學分析的基礎上,運用牛頓—歐拉法,對并聯(lián)機構建立動力學模型。在Matlab/SimMechanics中建立6-DOF并聯(lián)平臺的機械模型,使其與Simulink緊密組合在一起,構造出并聯(lián)機構仿真控制系統(tǒng)。對并聯(lián)機構的上平臺進行了軌跡規(guī)劃,設計出六自由度并聯(lián)機構控制系統(tǒng)總體方案。采用比例微分(Proportion Derivative,PD)控制器,引入魯棒自適應控制策略,耦合成魯棒自適應PD控制算法,并將其應用于Stewart并聯(lián)機器人單缸伺服系統(tǒng)。利用Matlab/Simulink模塊建立并聯(lián)機構聯(lián)合控制系統(tǒng),用魯棒自適應PD控制算法對其運動控制進行仿真實驗。仿真結果表明魯棒自適應PD控制算法對Stewart并聯(lián)機器人單缸伺服系統(tǒng)的參數(shù)變化具有自適應性,對于外界干擾具有很強的魯棒穩(wěn)定性,能對系統(tǒng)軌跡進行穩(wěn)定跟蹤,實現(xiàn)高效驅動,有效地提高系統(tǒng)運動的穩(wěn)定性。
[Abstract]:Parallel mechanism is a new structure relative to series mechanism. Its advantage lies in its great rigidity, high accuracy, strong carrying capacity, easy realization of control and so on. The dual relationship is formed in the structure and performance with the widely used series mechanism, and the complementary relationship is formed in the application, which greatly expands the scope of the application of the robot. Parallel mechanism is a complex system. It has many degrees of freedom, multi input and multi output, high nonlinearity, multi parameter and strong coupling. There are still many problems to be further studied and perfected. In this paper, the kinematics of Six Degrees of Freedom (6-DOF) parallel mechanism is introduced in detail, that is, the forward and backward solution of the position of the parallel mechanism is calculated, and the speed and acceleration of the platform motion are analyzed. The solution is obtained by a large number of input and output data set by position, put these data as extreme learning machine network training samples, application of extreme learning machine algorithm for solving the position of positive solutions, nonlinear mapping implementation of parallel mechanism the input displacement and output pose, and output pose can be calculated with the corresponding input displacement, and the use of Matlab the software of extreme learning machine method for simulation. On the basis of kinematics analysis, using the Newton Euler method, establish the dynamic model of the parallel mechanism. The mechanical model of 6-DOF parallel platform is set up in Matlab/SimMechanics, so that it is closely combined with Simulink, and the simulation control system of parallel mechanism is constructed. The trajectory planning of the upper platform of the parallel mechanism is carried out, and the overall scheme of the six degree of freedom parallel mechanism control system is designed. The Proportion Derivative (PD) controller is introduced to introduce the robust adaptive control strategy, and the robust adaptive PD control algorithm is coupled. It is applied to the single cylinder servo system of the Stewart parallel robot. The joint control system of parallel mechanism is established by using Matlab/Simulink module, and the simulation experiment of motion control is carried out by the robust adaptive PD control algorithm. The simulation results show that the adaptive algorithm parameters of Stewart parallel manipulator cylinder servo system of robust adaptive control for PD, has strong robustness to external disturbance, the system trajectory stability tracking, achieve efficient driving, effectively improve the stability of the system movement.
【學位授予單位】：新疆大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：TP242

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