机械手自适应模糊控制方法研究

发布时间：2018-05-10 16:03

本文选题：机械手 + 轨迹跟踪　；参考：《西南石油大学》2017年硕士论文

【摘要】：随着科学技术的飞速前进,机械手技术的发展逐渐成为工业控制领域内研究最为热门的学科,并不断向其它领域渗透。机械手系统的核心是控制系统,机械手的智能控制研究近年来得到诸多学者的高度重视,如何能使机械手更高速度和更高精度的为人类服务,从而代替人做许多复杂的、环境恶劣的、单调重复的工作是目前最需要解决的问题。随着科技的发展,人们对机械手的要求不仅仅是能够实现点对点的跟踪、一般直线跟踪和复杂的曲线跟踪,而是能够实现对任意指定路径高精度的跟踪。然而机械手系统受到许多不确定性因素的影响,如负载变化、随机扰动等外界因素和模型自身不确定性因素的影响,这些因素使得很难获得机械手系统准确的数学模型,很大程度上加大了机械手获得高精度轨迹跟踪控制方法的难度。因此本文就机械手轨迹跟踪控制方法展开深入的研究,目的是通过设计合理的控制器使机械手达到高精度轨迹跟踪控制的目的,使机械手的执行末端能够按照用户设定的期望路径,完成用户指定的工作流程。该论文的主要研究工作如下:1.本文首先分析了机械手运动学的理论知识,通过对刚体位姿的描述、坐标的转换,建立了机械手的运动学方程;然后通过拉格朗日函数的理论知识,推导了机械手的动力学模型;最后运用S函数对双关节机械手系统的动力学模型进行了编程,为后序仿真实验验证做好了充分的准备。2.其次分析了模糊系统的理论知识,并针对双关节机械手系统,完成了常规模糊控制系统的设计,并利用仿真实验分析出所设计的控制器的控制效果,通过仿真实验可知所设计的模糊控制器具有良好鲁棒性和不依赖对象精确数学模型的优点,但不足之处是存在控制精度较低的问题。3.在分析对比了常规模糊控制器对机械手轨迹跟踪控制的效果,设计出了两种新的自适应模糊控制算法,针对具有不确定性因素的MIMO系统,设计了具有模糊系统误差逼近特性的自适应模糊控制方案来提高机械手轨迹跟踪精度。而当机械手受到外界较大扰动等不确定性因素时,常规的模糊自适应控制方案对机械手的轨迹跟踪控制效果不太理想的情况,设计基于模糊补偿的机械手自适应模糊控制器来减少不确定性因素的影响,改善控制精度。本章所设计的控制算法均采用Lyapunov稳定性算法验证所设计的控制系统的稳定性,最后通过仿真实验研究,分析讨论了机械手在不同控制算法的控制下所能达到的轨迹跟踪效果,从而证明了所设计的控制算法的有效性。最后分析总结了本文的工作重点和取得的研究成果,并提出了不足和对下一步更深入的研究计划进行了展望。
[Abstract]:With the rapid development of science and technology, the development of manipulator technology has gradually become the hottest subject in the field of industrial control, and continues to infiltrate into other fields. The core of the manipulator system is the control system. In recent years, the intelligent control research of the manipulator has been paid great attention by many scholars. How to make the manipulator serve the human with higher speed and precision, so as to do a lot of complex things instead of the human being. The most important problem to be solved at present is the harsh environment and monotonous and repetitive work. With the development of science and technology, the requirement of manipulator is not only to achieve point-to-point tracking, general line tracking and complex curve tracking, but also to track any given path with high accuracy. However, manipulator system is affected by many uncertain factors, such as load change, random disturbance and so on. These factors make it difficult to obtain accurate mathematical model of manipulator system. To a great extent, it is more difficult for the manipulator to obtain high precision trajectory tracking control method. In this paper, the trajectory tracking control method of manipulator is studied in depth. The purpose of this paper is to design a reasonable controller to make the manipulator achieve the purpose of high precision trajectory tracking control. The end of the manipulator can complete the user-specified workflow according to the desired path set by the user. The main research work of this thesis is as follows: 1. In this paper, the kinematics theory of manipulator is analyzed, and the kinematics equation of manipulator is established by describing the position of rigid body and transforming coordinates, and then through the theoretical knowledge of Lagrange function. The dynamics model of the manipulator is deduced, and the dynamic model of the two-joint manipulator system is programmed by using S function, which is fully prepared for the post-sequence simulation experiment. Secondly, the theoretical knowledge of the fuzzy system is analyzed, and the design of the conventional fuzzy control system is completed for the dual-joint manipulator system, and the control effect of the designed controller is analyzed by the simulation experiment. The simulation results show that the fuzzy controller has the advantages of good robustness and no dependence on the precise mathematical model of the object, but the disadvantage is that the control accuracy is low. In this paper, the effect of conventional fuzzy controller on trajectory tracking control of manipulator is analyzed and compared. Two new adaptive fuzzy control algorithms are designed for MIMO system with uncertain factors. An adaptive fuzzy control scheme with the characteristic of fuzzy system error approximation is designed to improve the tracking accuracy of manipulator. However, when the manipulator is subjected to some uncertain factors, such as outside disturbance, the conventional fuzzy adaptive control scheme is not ideal for the trajectory tracking control of the manipulator. An adaptive fuzzy controller for manipulator based on fuzzy compensation is designed to reduce the influence of uncertain factors and improve the control precision. All the control algorithms designed in this chapter use Lyapunov stability algorithm to verify the stability of the designed control system. Finally, the trajectory tracking effect of manipulator under the control of different control algorithms is analyzed and discussed through simulation experiments. Thus, the effectiveness of the proposed control algorithm is proved. Finally, the emphasis and research results of this paper are analyzed and summarized, and the deficiency and the prospect of further research plan are put forward.
【学位授予单位】：西南石油大学
【学位级别】：硕士
【学位授予年份】：2017
【分类号】：TP241

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