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论文编号:ZD787 论文字数:21874,页数:56,有开题报告,文献综述,外文翻译
摘 要
机器人的控制问题无论在理论界还是工程界多年来一直备受人们关注。众所周知,机器人是一个十分复杂的多输入多输出非线性系统,它具有时变、强耦和非线性的动力学特点,对其进行控制也是十分复杂的,我们必须面对机器人大量不确定性因素的存在。在机器人的各种控制算法中,基予模型的计算力矩控制方法是十分有效的,其操作性也是很强的。然而,这种控制算法必须面临两大难题,第一,必须实现对机器人动力学模型的快速计算;第二,必须事先精确计算机器人的动力学模型,因为计算力矩算法在模型未知的情况下鲁棒性较差。但在实际中,即使获得一个较为理想的机器人动力学模型也是很困难的,何况在操作过程中机器人动力学模型的各个参数可能发生变化,同时还受到环境干扰和负载变化等许多不确定性因素的影响。
本论文以具有完整动力学模型的机器人系统,即不确定性机器人系统为研究对象,在现有的文献基础上,重点探讨基于计算力矩算法的补偿控制策略。
本文首先介绍了机器人的发展概论和机器人控制理论概况,然后对计算力矩控制算法的基本思想和主要特点作详细的阐述,紧接着探讨了基于计算力矩结构的不确定机器人的补偿控制算法。基本思想都是将不确定性机器人系统分解成标称系统和不确定系统:对于标称系统,采用计算力矩控制;对于不确定系统,采用机器人系统的回归矩阵或集中不确定性上界的包络函数,设计不同的补偿控制器,补偿控制器的输入与机器人的输入相叠加作为整个机器人系统的输入,使得机器人闭环系统能够实现全局一致最后有界、渐进稳定和指数稳定。并对二自由度串联机器人进行了MATLAB仿真,利用S-Function编写程序,证明了其有效性和可行性。
关键词 不确定机器人;计算力矩控制;鲁棒控制;机器人动力学;MATLAB/imulion;S-Function函数
Abstract
The control problems of robotic manipulators have received great attention in theoretical research and engineering for many years. It is well known that the robotic manipulator is a very complicated MIMO nonlinear system with time-varying strong-coupling and nonlinear dynamic characteristics, so the control for such a system is quite difficult, we have to face a lot of uncertainties. The model-based scheme popularly known as Computed Torque Control (CTC) is effective and its performance is excellent in various control strategies for robotic manipulator. However, the requirements for successfully implementing CTC are fast computation and perfect knowledge of dynamic model.. because CTC is not robust enough in uncertain model. In practice, unfortunately, it is impossible to obtain a prefect, or even reasonably accurate dynamic model of a robotic manipulator. Furthermore, the parameters of dynamics model of robotic manipulators may also be subject to change when the manipulator goes about its task. Meanwhile, the system can be influenced by uncertainties such as external disturbance and payload change.
In this dissertation, the system of robotic manipulator with entire dynamic model namely, the robotic system with uncertainties is regarded as controlled plant and the various compensation schemes based CTC are developed on base of references available.
The dissertation gives a brief description about the developing situation and control theory of robot firstly, and then the underlying idea and characteristic of CTC are introduced in detail. Subsequently discussed control strategies with compensation control structure which are based on CTC are proposed. The overall idea is that the system of robotic manipulators is decomposed as two parts: one is nominal system with perfect knowledge of dynamic model and the other is system with uncertainties. CTC is used to control nominal system. For uncertainties system, we utilize the regress of robotic system or bounding function on uncertainties to design different compensation controllers. The inputs of the two parts control the robotic systems together. These proposed control algorithms ensure Global Universe Ultimate Boundness Stability, Global Asymptotic Stability and Global Exponential Stability of the whole robotic system. The simulation results are presented for the same 2-DOF serial robotic manipulator in MATLAB, Use s-Function compiled programs, which validate the effectiveness and feasibility of the proposed schemes.
Keywords robotic manipulators with uncertainties; computed torque control; robust adaptive control; Robotic kinematics; MATLAB/ Simulation; S-Function
目 录
摘 要 I
Abstract II
第1章 绪论 1
1.1 研究背景及意义 1
1.1.1机器人发展简史与自动控制 2
1.1.2本课题研究的意义 3
1.2 机器人鲁棒控制方法概述 4
1.2.1鲁棒控制方法 4
1.2.2反馈线性化控制 5
1.2.3变结构控制方法 5
1.3 本章小结 6
第2章 预备知识 7
2.1 数学知识 7
2.2 仿真知识 9
2.2.1仿真的概念 9
2.2.2 MATLAB语言简介 10
2.3 机器人的数学模型 10
2.4 机器人仿真模型的建立 12
2.5 本章小结 14
第3章 机器人的位姿描述 15
3.1 位姿描述 15
3.1.1平行移动 15
3.1.2旋转 17
3.1.3齐次变换 18
3.2 运动学正向问题 19
3.3 运动学逆向问题 21
3.4 雅可比矩阵 23
3.5 本章小结 27
第四章 机器人的动力学模型 28
4.1 利用牛顿定律建立机器人动力学模型 28
4.1.1机器人平动的动力学模型 28
4.1.2机器人转动的动力学模型 30
4.2 利用拉格朗日方程建立机器人动力学模型 31
4.3 二自由度机器人的动力学模型 32
4.4 本章小结 36
第五章 应用计算机力矩结构的控制策略 37
5.1 计算力矩的基本思想 37
5.2 仅对标称模型的计算力矩控制 38
5.2.1仿真结果 38
5.3 计算力矩的补偿控制结构 39
5.3.1不确定性约束参数已知 41
5.3.2不确定性约束参数未知 45
5.4 本章小结 47
结论 48
参考文献 49
致谢 51
附录1 52
附录2 56
附录3 61
附录4 70