Hong, Xia, Iplikci, S., Chen, Sheng and Warwick, kevin
B-spline neural networks based PID controller for Hammerstein systems.
In, 8th International Conference Intelligent Computing, Huangshan Shi, CN,
25 - 29 Jul 2012.
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 multi-step 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.
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