B-spline neural networks based PID controller for Hammerstein systems

Hong, Xia, Iplikci, S., Chen, Sheng and Warwick, kevin (2012) B-spline neural networks based PID controller for Hammerstein systems. In, 8th International Conference Intelligent Computing, Huangshan Shi, CN, 25 - 29 Jul 2012. 12pp.


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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.

Item Type: Conference or Workshop Item (Paper)
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions: Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control
ePrint ID: 341401
Date Deposited: 24 Jul 2012 10:39
Last Modified: 27 Mar 2014 20:24
Further Information:Google Scholar
ISI Citation Count:0
URI: http://eprints.soton.ac.uk/id/eprint/341401

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