基于PMAC引線鍵合軌跡規(guī)劃研究
發(fā)布時間：2018-07-21 11:35
【摘要】：隨著工業(yè)機(jī)器人、汽車、機(jī)械臂行業(yè)的快速發(fā)展和人們對其精度、穩(wěn)定性要求的提高,針對它們的運(yùn)動軌跡研究成為重要的研究課題。學(xué)者們通過不同的方法來研究軌跡規(guī)劃,有的學(xué)者通過提出運(yùn)動軌跡規(guī)劃算法來規(guī)劃軌跡；有的學(xué)者通過將其他領(lǐng)域的控制方法、算法應(yīng)用到軌跡規(guī)劃上；有的學(xué)者從軌跡的基本元素——速度、加速度、位移——的連續(xù)性出發(fā),根據(jù)不同軌跡的工藝要求來擬合；也有的學(xué)者將運(yùn)動分段,用不同的插值方法來擬合等等。本文以平面LED全自動超聲波金絲球焊線機(jī)WB2001為試驗(yàn)平臺,以焊線機(jī)劈刀為研究對象,以引線鍵合軌跡為優(yōu)化目標(biāo),利用PMAC運(yùn)動控制系統(tǒng)中自帶的運(yùn)動軌跡規(guī)劃模式來規(guī)劃軌跡并結(jié)合其PID控制系統(tǒng)進(jìn)一步優(yōu)化、規(guī)劃軌跡。本文從混合模式軌跡規(guī)劃、整段控制參數(shù)和混合模式軌跡優(yōu)化、分段控制參數(shù)和混合模式軌跡規(guī)劃三個角度來規(guī)劃引線鍵合軌跡。混合模式軌跡規(guī)劃將軌跡進(jìn)行分段,在保證位置、速度、加速度連續(xù)基礎(chǔ)上,以跟隨誤差和重復(fù)誤差為試驗(yàn)指標(biāo),以不同控制模式為試驗(yàn)變量,來規(guī)劃軌跡。在規(guī)化過程中,把不同的控制模式數(shù)值化,并結(jié)合正交試驗(yàn)建立不同控制模式與試驗(yàn)指標(biāo)的數(shù)學(xué)模型,用多目標(biāo)遺傳算法獲得規(guī)化目標(biāo)的Pareto最優(yōu)解,從而得到最優(yōu)軌跡規(guī)劃方式,實(shí)現(xiàn)引線鍵后軌跡規(guī)劃。整段控制參數(shù)與混合模式軌跡規(guī)劃是通過試驗(yàn)設(shè)計和響應(yīng)面模型方法來獲取試驗(yàn)數(shù)據(jù),并建模分析來實(shí)現(xiàn)參數(shù)整定。用整段控制參數(shù)設(shè)計正交試驗(yàn),用Design-expert軟件和MATLAB軟件分析計算試驗(yàn)數(shù)據(jù)來優(yōu)化軌跡,和智能方法整定相比,簡單易獲得而且對理論要求較低。分段控制參數(shù)與混合模式軌跡規(guī)劃是利用分段控制參數(shù)與混合模式一起來規(guī)劃軌跡。先把整段運(yùn)動分段處理,對每一段運(yùn)動不同模式、不同控制參數(shù)進(jìn)行試驗(yàn),并建模分析,先找到每段各模式的最優(yōu)控制參數(shù),對比每段中各模式的最優(yōu)控制參數(shù)獲得最優(yōu)控制模式和控制參數(shù)組合,就這樣按順序找出每段最優(yōu)組合,一步一步找出整段的最優(yōu)組合,其中所獲得后段運(yùn)動的控制參數(shù)以前部分運(yùn)動為基礎(chǔ)。軌跡規(guī)劃過程中,將理論方法得到的結(jié)果代入試驗(yàn)平臺進(jìn)行驗(yàn)證,結(jié)果驗(yàn)證了所采用的三種軌跡規(guī)劃方法的正確性、可靠性。
[Abstract]:With the rapid development of industrial robot, automobile and manipulator industry and the improvement of its precision and stability, the research on their motion trajectory has become an important research topic. Some scholars put forward motion trajectory planning algorithm to plan trajectory, some scholars apply the algorithm to trajectory planning by using control methods in other fields, and some scholars study trajectory planning by different methods, some scholars put forward motion trajectory planning algorithm to plan trajectory, and some scholars apply other control methods to trajectory planning. Some scholars start from the continuity of the basic elements of the trajectory-velocity, acceleration, displacement-and fit them according to the technological requirements of different trajectories; others fit the motion segments with different interpolation methods and so on. This paper takes WB2001, an automatic planar LED ultrasonic gold wire ball welding machine, as the test platform, takes the splitter of the wire welding machine as the research object, and takes the lead bond trajectory as the optimization goal. The trajectory planning model of PMAC motion control system is used to plan the trajectory and its pid control system is further optimized to plan the trajectory. In this paper, the lead bond trajectory is planned from three angles: hybrid mode trajectory planning, whole control parameter and mixed mode trajectory optimization, piecewise control parameter and mixed mode trajectory planning. The trajectory of mixed mode trajectory planning is divided into sections. On the basis of continuous position, velocity and acceleration, tracking error and repetition error are taken as test indexes, and different control modes are used as test variables to plan the trajectory. In the process of planning, different control modes are numerically simulated, and mathematical models of different control modes and test indexes are established by orthogonal test. The Pareto optimal solution of the planning target is obtained by using multi-objective genetic algorithm. The optimal trajectory planning method is obtained and the post-lead trajectory planning is realized. The whole control parameter and mixed mode trajectory planning are used to obtain the test data by experimental design and response surface model method, and to realize parameter tuning by modeling and analysis. The orthogonal test is designed with the whole control parameters, and the test data are analyzed and calculated by Design-expert software and MATLAB software to optimize the trajectory. Compared with the intelligent tuning method, it is simple and easy to obtain, and the theoretical requirements are lower. Piecewise control parameters and mixed mode trajectory planning are designed by using piecewise control parameters and mixed modes. First, the whole segment motion is divided into sections, and the different modes and control parameters of each segment are tested, and the optimal control parameters of each model are found out first by modeling and analyzing. By comparing the optimal control parameters of each mode in each section, the optimal control mode and the combination of control parameters are obtained, and the optimal combination of each segment is found in sequence, and the optimal combination of the whole section is found step by step. The obtained control parameters of the posterior motion are based on the previous partial motion. In the course of trajectory planning, the results obtained by the theoretical method are put into the experimental platform to verify the correctness and reliability of the three trajectory planning methods.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN312.8
[Abstract]:With the rapid development of industrial robot, automobile and manipulator industry and the improvement of its precision and stability, the research on their motion trajectory has become an important research topic. Some scholars put forward motion trajectory planning algorithm to plan trajectory, some scholars apply the algorithm to trajectory planning by using control methods in other fields, and some scholars study trajectory planning by different methods, some scholars put forward motion trajectory planning algorithm to plan trajectory, and some scholars apply other control methods to trajectory planning. Some scholars start from the continuity of the basic elements of the trajectory-velocity, acceleration, displacement-and fit them according to the technological requirements of different trajectories; others fit the motion segments with different interpolation methods and so on. This paper takes WB2001, an automatic planar LED ultrasonic gold wire ball welding machine, as the test platform, takes the splitter of the wire welding machine as the research object, and takes the lead bond trajectory as the optimization goal. The trajectory planning model of PMAC motion control system is used to plan the trajectory and its pid control system is further optimized to plan the trajectory. In this paper, the lead bond trajectory is planned from three angles: hybrid mode trajectory planning, whole control parameter and mixed mode trajectory optimization, piecewise control parameter and mixed mode trajectory planning. The trajectory of mixed mode trajectory planning is divided into sections. On the basis of continuous position, velocity and acceleration, tracking error and repetition error are taken as test indexes, and different control modes are used as test variables to plan the trajectory. In the process of planning, different control modes are numerically simulated, and mathematical models of different control modes and test indexes are established by orthogonal test. The Pareto optimal solution of the planning target is obtained by using multi-objective genetic algorithm. The optimal trajectory planning method is obtained and the post-lead trajectory planning is realized. The whole control parameter and mixed mode trajectory planning are used to obtain the test data by experimental design and response surface model method, and to realize parameter tuning by modeling and analysis. The orthogonal test is designed with the whole control parameters, and the test data are analyzed and calculated by Design-expert software and MATLAB software to optimize the trajectory. Compared with the intelligent tuning method, it is simple and easy to obtain, and the theoretical requirements are lower. Piecewise control parameters and mixed mode trajectory planning are designed by using piecewise control parameters and mixed modes. First, the whole segment motion is divided into sections, and the different modes and control parameters of each segment are tested, and the optimal control parameters of each model are found out first by modeling and analyzing. By comparing the optimal control parameters of each mode in each section, the optimal control mode and the combination of control parameters are obtained, and the optimal combination of each segment is found in sequence, and the optimal combination of the whole section is found step by step. The obtained control parameters of the posterior motion are based on the previous partial motion. In the course of trajectory planning, the results obtained by the theoretical method are put into the experimental platform to verify the correctness and reliability of the three trajectory planning methods.
【學(xué)位授予單位】：廣東工業(yè)大學(xué)
【學(xué)位級別】：碩士
【學(xué)位授予年份】：2015
【分類號】：TN312.8
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