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Adaptive Control Theory for Nonlinear Parameterized Systems and Its Application to Micro-Mechanical System

非线性参数化系统自适应控制理论及其在微机械系统中的应用

基本信息

批准号：
15560389
负责人：
NARIKIYO Tatsuo
金额：
$ 1.98万
依托单位：
Toyota Technological Institute
依托单位国家：
日本
项目类别：
Grant-in-Aid for Scientific Research (C)
财政年份：
2003
资助国家：
日本
起止时间：
2003 至 2004
项目状态：
已结题

项目摘要

Purpose of this study is to search an adaptation mechanism for a more general class of practical systems whose uncertain quantities cannot be expressed linearly with respect to unknown parameters. In this study, a novel adaptive control technique is proposed, which is applicable to any NP systems under Lipschitzian structure. This idea enables the design of adaptive controllers, which can compensate effectively for NP uncertainties in the sense that it guarantees both global boundedness of the closed-loop system signals and tracking error within any prescribed accuracies. The structures of the resulting controllers are simple since they are designed based on the information of the upper bounds for the nonlinear functions, not the functions at all. An important feature of the proposed technique is that the compactness of parametric sets is not required. Therefore, the designed adaptive controls gain a great amount of computation reduced. Also, a very broad class of nonlinearly parameterized adaptive control problems such as Lipschitzian parameterization, multiplicative parameterization, fractional parameterization or their combinations can be solved by the proposed approach.A general framework of adaptive control to compensate for parametrrc uncertainties of robot manipulators is constructed. The goal is to verify how the proposed adaptive control technique actually works with practical dynamic systems. In practical robot manipulators, NP uncertainties are common. A typical example is the Stribeck effect of frictional forces at joints of the manipulators. Such an effect results in undesired tracking errors, especially at the low-velocity tracking task. However, in the literature of robot control, there is still no result addressing the adaptive control problem for NP uncertainties of robot manipulators in a general manner.

本研究的目的是寻找一个适应机制，更一般的一类实际系统的不确定量不能表示线性关于未知参数。本文提出了一种新的自适应控制方法，它适用于任何具有Lipschitz结构的NP系统。这种思想使得自适应控制器的设计，它可以有效地补偿NP不确定性的意义上，它保证了闭环系统信号的全局有界性和跟踪误差在任何规定的精度。所得到的控制器的结构是简单的，因为它们是基于非线性函数的上界的信息来设计的，而不是在所有的功能。所提出的技术的一个重要特点是，参数集的紧凑性是不需要的。因此，所设计的自适应控制器大大减少了计算量。同时，该方法还可以解决一类非常广泛的非线性参数化自适应控制问题，如Lipschitzian参数化、乘法参数化、分数参数化或它们的组合，从而构建了机器人参数不确定性自适应控制的一般框架.我们的目标是验证所提出的自适应控制技术实际上是如何与实际的动态系统。在实际的机器人操作器中，NP不确定性很常见。一个典型的例子是在机械手关节处的摩擦力的Stribeck效应。这种效应导致不期望的跟踪误差，特别是在低速跟踪任务中。然而，在机器人控制的文献中，仍然没有结果解决NP不确定性的机器人操作器的自适应控制问题的一般方式。