PUMA机器人轨迹跟踪控制算法仿真研究

发布时间：2018-04-27 20:31

本文选题：工业机器人 + 轨迹跟踪　；参考：《深圳大学》2017年硕士论文

【摘要】：随着现代工业发展速度越来越快,人们格外地重视如何进一步提高工业生产的效率,所以对工业机器人的控制性能提出了更高的要求。由于工业机器人本身的强非线性和耦合特性,使得在工业机器人控制中存在着很多问题,机器人的轨迹跟踪控制则是众多问题中的一个重点。轨迹跟踪控制的主要目的就是通过给定各关节的驱动力矩,使得机器人的位置、速度等状态变量跟踪给定的理想轨迹[1]。本文从工业机器人响应速度和跟踪精度两个方面,对工业机器人的轨迹跟踪控制算法进行研究。本文首先分析了工业机器人的轨迹跟踪控制在国内外的研究现状。随后分析了六自由度机器人的运动学与动力学问题,然后通过拉格朗日方法建立了机器人的动力学方程并分析动力学方程的推导过程,最后对方程进行数值化简并仿真验证。接着分析常规的轨迹跟踪控制算法(如PD-重力补偿控制、计算力矩法、滑膜变结构控制等),根据性能要求提出快速变结构算法和模糊变结构算法。前者是通过对变结构控制的趋近律进行优化来改善控制效果,后者先利用变结构控制的特性弥补参数不确定性所带来的影响,在这个基础上再利用模糊规则来调节趋近律参数,以削弱变结构控制所带来的抖振现象。然后利用SOLIDWORKS建立工业机器人的虚拟样机模型,再导入到ADAMS进行约束与驱动的添加,将虚拟样机模型模块化后导出到MATLAB中使虚拟样机模型转化为MATLAB中的一个模块,从而实现MATLAB与ADAMS的连接,随后在MATLAB中搭建工业机器人控制算法的仿真模型,并进行两者的联合仿真。最后以PUMA机器人为控制对象,设计了相应的轨迹跟踪算法程序,利用联合仿真实验对比来验证所提两种算法的可行性。
[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.
【学位授予单位】：深圳大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP242

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