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- W2899384299 abstract "This paper develops a conservatism reduction approach for neural-network-based uncertain nonlinear systems to achieve guaranteed cost control. First, a multi-layer neural network model is used to approximate the nonlinearities in dynamic systems, and it is formulated as a linear difference inclusion (LDI) representation. Then, a multi-step ahead Lyapunov function is developed for guaranteed-cost control based on the LDI model. The advantage of such a Lyapunov function is to reduce the conservatism of the linear matrix inequality constraints so that a lower upper bound of the linear quadratic performance index could be expected. Finally, a numerical example is provided to demonstrate the effectiveness of the proposed method." @default.
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- W2899384299 date "2018-08-11" @default.
- W2899384299 modified "2023-09-24" @default.
- W2899384299 title "Conservatism Reduction in Guaranteed Cost Control for a Class of Uncertain Nonlinear Systems" @default.
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- W2899384299 doi "https://doi.org/10.1145/3265639.3265659" @default.
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