This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based sampling techniques. The proposed control scheme preserves all well-known individual advantages of GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an important reduction of actuation load meanwhile the control system performance is maintained within an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish a tradeoff between control performance and the number of actuations. The performance of the proposed control algorithm is first verified for a first-order plus delay process and afterwards it is evaluated by using a case study based on the greenhouse temperature control problem.
Description
ScienceDirect.com - Computers & Chemical Engineering - A practical approach for Generalized Predictive Control within an event-based framework
%0 Journal Article
%1 Pawlowski201252
%A Pawlowski, A.
%A Guzmánn, J.L.
%A Normey-Rico, J.E.
%A Berenguel, M.
%D 2012
%J Computers & Chemical Engineering
%K event_driven send_on_delta
%N 0
%P 52 - 66
%R 10.1016/j.compchemeng.2012.03.003
%T A practical approach for Generalized Predictive Control within an event-based framework
%U http://www.sciencedirect.com/science/article/pii/S0098135412000816
%V 41
%X This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based sampling techniques. The proposed control scheme preserves all well-known individual advantages of GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an important reduction of actuation load meanwhile the control system performance is maintained within an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish a tradeoff between control performance and the number of actuations. The performance of the proposed control algorithm is first verified for a first-order plus delay process and afterwards it is evaluated by using a case study based on the greenhouse temperature control problem.
@article{Pawlowski201252,
abstract = {This work presents a combination of the Generalized Predictive Control (GPC) algorithm with event-based sampling techniques. The proposed control scheme preserves all well-known individual advantages of GPC and event-based sampling algorithms, respectively. The main benefits of this combination are an important reduction of actuation load meanwhile the control system performance is maintained within an acceptable level. Guidelines for a tuning procedure are given and tested for a wide set of industrial process models. Furthermore, the resulting algorithm is simple to be implemented and allows to establish a tradeoff between control performance and the number of actuations. The performance of the proposed control algorithm is first verified for a first-order plus delay process and afterwards it is evaluated by using a case study based on the greenhouse temperature control problem.},
added-at = {2012-05-25T14:41:24.000+0200},
author = {Pawlowski, A. and Guzmánn, J.L. and Normey-Rico, J.E. and Berenguel, M.},
biburl = {https://www.bibsonomy.org/bibtex/2a7620f027881214e1cc9549c3086dee8/romeroj},
description = {ScienceDirect.com - Computers & Chemical Engineering - A practical approach for Generalized Predictive Control within an event-based framework},
doi = {10.1016/j.compchemeng.2012.03.003},
interhash = {fa62ec5208f0ac258fdff1fe62f0d20a},
intrahash = {a7620f027881214e1cc9549c3086dee8},
issn = {0098-1354},
journal = {Computers & Chemical Engineering},
keywords = {event_driven send_on_delta},
number = 0,
pages = {52 - 66},
timestamp = {2012-05-25T14:41:25.000+0200},
title = {A practical approach for Generalized Predictive Control within an event-based framework},
url = {http://www.sciencedirect.com/science/article/pii/S0098135412000816},
volume = 41,
year = 2012
}