By Topic

Gain-scheduled smith proportional-integral derivative controllers for linear parameter varying first-order plus time-varying delay systems

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $33
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Y. Bolea ; Autom. Control Dept., Tech. Univ. of Catalonia (UPC), Barcelona, Spain ; V. Puig ; J. Blesa

Practical control problems often deal with parameter-varying uncertain systems that can be described by a first-order-plus-delay (FOPD) model. In this paper, a new approach to design gain-scheduled robust linear parameter varying (LPV) propotional-intergral derivative controllers with pole placement constraints through linear matrix inequalities (LMI) regions is proposed. The controller structure includes a Smith Predictor (SP) to deal with the delays. System parameter variations are measured online and used to schedule the controller and the SP. Although the known part of the delay is compensated with the -delay scheduling- SP, the proposed approach allows to consider uncertainty in the delay estimation. This uncertainty is taken into account in the controller design as an unstructured dynamic uncertainty. Finally, two applications are used to assess the proposed methodology: a simulated artificial example and a simulated physical system based on an open canal system used for irrigation purposes. Both applications are represented by FOPD models with large and variable delays as well as parameters that depend on the operating conditions.

Published in:

IET Control Theory & Applications  (Volume:5 ,  Issue: 18 )