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- W72726998 abstract "A new PID tuning and controller approach is introduced for Hammerstein systems based on input/output data. A B-spline neural network is used to model the nonlinear static function in the Hammerstein system. The control signal is composed of a PID controller together with a correction term. In order to update the control signal, the multistep ahead predictions of the Hammerstein system based on the B-spline neural networks and the associated Jacobians matrix are calculated using the De Boor algorithms including both the functional and derivative recursions. A numerical example is utilized to demonstrate the efficacy of the proposed approaches." @default.
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- W72726998 date "2012-01-01" @default.
- W72726998 modified "2023-10-18" @default.
- W72726998 title "B-Spline Neural Networks Based PID Controller for Hammerstein Systems" @default.
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- W72726998 doi "https://doi.org/10.1007/978-3-642-31837-5_6" @default.
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