QFT Parameter-Scheduling control design for linear Time-Varying systems based on RBF networks |
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Authors: | Email author" target="_blank">Jae?Weon?ChoiEmail author Wan-Suk?Yoo Suk?Lee Ki?Hong?Im Jin?Young?Choi |
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Affiliation: | (1) School of Mechanical Engineering and Research Institute of Mechanical Technology, Pusan National University, 609-735 Pusan, Korea;(2) School of Electrical Engineering and Computer Science, Seoul National University, 151-742 Seoul, Korea |
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Abstract: | For most of linear time-varying (LTV) systems, it is difficult to design time-varying controllers in analytic way. Accordingly,
by approximating LTV systems as uncertain linear time-invariant, control design approaches such as robust control have been
applied to the resulting uncertain LTI systems. In particular, a robust control method such as quantitative feedback theory
(QFT) has an advantage of guaranteeing the frozen-time stability and the performance specification against plant parameter
uncertainties. However, if these methods are applied to the approximated linear time-invariant (LTI) plants with large uncertainty,
the resulting control law becomes complicated and also may not become ineffective with faster dynamic behavior. In this paper,
as a method to enhance the fast dynamic performance of LTV systems with bounded time-varying parameters, the approximated
uncertainty of time-varying parameters are reduced by the proposed QFT parameter-scheduling control design based on radial
basis function (RBF) networks. |
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Keywords: | QFT (Quantitative Feedback Theory) Linear Time-Varying System Parameter Scheduling RBF (Radial Basis Function) Network |
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