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全方位移动机械手运动控制方法的研究
Alternative TitleResearch on Motion Control of Omnidirectional Mobile Manipulator Systems
徐冬
Subtype工学博士
Thesis Advisor易建强
2008-05-29
Degree Grantor中国科学院研究生院
Place of Conferral中国科学院自动化研究所
Degree Discipline控制理论与控制工程
Keyword全方位移动机械手 冗余驱动 运动控制 不确定性 轨迹跟踪 Omnidirectional Mobile Manipulator Redundantly-actuated Motion Control Uncertainty Trajectory Tracking
Abstract全方位移动机械手,其全方位移动平台不受非完整约束,具有平面运动所需的3个自由度,运动性能优于受非完整约束的移动平台(比较典型的差分驱动的移动平台),因而其运动控制问题的研究具有重要的理论意义和实用价值。本文以全方位移动机械手系统为背景,结合国家自然科学基金项目“移动机械手的协调运动规划与控制”等,对其运动控制问题展开研究。 首先,对移动机械手系统及其控制问题进行了介绍,综述了国内外对移动机械手系统的研究进展,并阐述了选题背景和论文主要内容。 其次,结合实验室的全方位移动机械手系统,分析了系统的体系结构,然后建立了轮式全方位移动机械手的运动学模型,并在其基础上进行了运动学控制的仿真研究。 第三,根据系统的运动学模型,使用Lagrange方法建立了系统集成动力学模型,并进行轨迹跟踪控制问题研究。此外,针对全方位移动机械手移动平台冗余驱动的特性,运用牛顿-欧拉方法建立了一种分体动力学模型,并提出一种系统位姿镇定和内力同时控制的方法,实现了内力与位姿的协同控制。 第四,针对动力学系统不确定性,利用系统动力学特性,提出一种基于动力学模型固定上界的简单滑模轨迹跟踪控制器。该算法用于轮式全方位移动机械手系统,实现了协调控制。 第五,由于基于动力学模型固定上界的滑模轨迹跟踪控制器的保守性,提出一种考虑系统不确定性的参数自适应鲁棒控制算法,保证了闭环系统所有状态的渐近跟踪,实现了系统的协调运动控制。 第六,假设系统的不确定性可分成系统结构不确定性和未知的外部干扰两部分,提出两种基于神经网络非线性映射能力和自学习能力的自适应神经网络控制方法:传统自适应神经网络控制方法和自适应神经网络滑模控制方法。分离式神经网络结构用来逼近整个系统的结构不确定性,滑模控制用来保证系统的鲁棒性,仿真结果显示该自适应神经网络滑模控制方法具有良好的动态特性。 最后,对取得的研究成果进行了总结,并展望了需要进一步研究的工作。
Other AbstractOmnidirectional mobile manipulator, which omnidirectional mobile platform has total three DOF in the motion plane, is not affected by nonholonomic constraints. Consequently, the motion performance of omnidirectional mobile platform is much better than the differential-driven mobile platform, which is restricted by the nonholonomic constraint. Therefore, motion control of omnidirectional mobile manipulator systems is challengeable in both theory and application. In this dissertation, motion control problems of mobile manipulator are studied extensively with the support of project of National Science and Foundation of China “Coordinated Motion Planning and Control of Mobile Manipulator”.Firstly, mobile manipulator systems, as well as their control problems are introduced. The research status of control of mobile manipulator systems is comprehensively surveyed. Then background and main work of this dissertation are proposed.Secondly, according to the actual omnidirectional mobile manipulator in the lab, the system configuration is elaborated. Then, the kinematics of the omnidirectional mobile manipulator system is derived and the simulation research work based on the kinematics is performed.Thirdly, based on the kinematics, we use Lagrange method to construct the integrated dynamic model and address the trajectory tracking control problem. In addition, for the redundantedly-actuated property of the ominidirectional mobile platform, we use Newton-Euler method to construct the separate dynamic model. Then the regular motion and internal force synchronously control scheme is proposed and the coordinated control of force and posture is realized.Fourthly, for the dynamics uncertainties of the omnidirctional mobile manipulator system, a sliding mode control scheme based on the fixed large upper boundedness of the system dynamics is proposed for trajectory tracking. The performances of the proposed method are verified on mobile manipulator systems.Fifthly, since the fixed large upper boundedness sliding mode controller has the conservative characteristic, a robust parameter adapting control method, which consider the system with uncertainties, is proposed. This control method guarantees the closed-loop system asymptotical stability and realizes the system coordinated control.Sixthly, it is assumed that system uncertainties can be divided into two subsystems: structure uncertainties and external disturbances. Two control methods based on nonlinear mapping ability and self-learning ability of neural network are proposed: one is conventional adaptive neural network control method; another is adaptive neural network sliding mode control method. A partitioned neural network structure is applied to approximate the whole system structure uncertainties and the sliding mode control is used to guarantee the robustness.Finally, the obtained results are summarized and future work is addressed.
shelfnumXWLW1211
Other Identifier200518014628029
Language中文
Document Type学位论文
Identifierhttp://ir.ia.ac.cn/handle/173211/6088
Collection毕业生_博士学位论文
Recommended Citation
GB/T 7714
徐冬. 全方位移动机械手运动控制方法的研究[D]. 中国科学院自动化研究所. 中国科学院研究生院,2008.
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