| Budget Amount *help |
¥3,100,000 (Direct Cost: ¥3,100,000)
Fiscal Year 2004: ¥1,700,000 (Direct Cost: ¥1,700,000)
Fiscal Year 2003: ¥1,400,000 (Direct Cost: ¥1,400,000)
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| Research Abstract |
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.
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