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.
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 and Applied Science > Electronics and Computer Science > Comms, Signal Processing & Control
|Date Deposited:||24 Jul 2012 10:39|
|Last Modified:||24 Jul 2012 10:40|
|Contributors:||Hong, Xia (Author)
Iplikci, S. (Author)
Chen, Sheng (Author)
Warwick, kevin (Author)
|Further Information:||Google Scholar|
|ISI Citation Count:||0|
|RDF:||RDF+N-Triples, RDF+N3, RDF+XML, Browse.|
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