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.


PDF (Manuscript)
Download (224Kb)


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 > Southampton Wireless Group
ePrint ID: 341401
Accepted Date and Publication Date:
July 2012Delivered
July 2012Made publicly available
Date Deposited: 24 Jul 2012 10:39
Last Modified: 31 Mar 2016 14:31
Further Information:Google Scholar
URI: http://eprints.soton.ac.uk/id/eprint/341401

Actions (login required)

View Item View Item

Downloads from ePrints over the past year. Other digital versions may also be available to download e.g. from the publisher's website.

View more statistics