Hybrid Model Predictive Control Based on Wireless Sensor Feedback: an experimental study
2007 (English)In: Proceedings of the 46th IEEE Conference on Decision and Control, New Orleans, Louisiana, USA., 2007, 5062-5067 p.Conference paper (Refereed)
This paper presents the design and the experimental validation of model predictive control (MPC) of a hybrid dynamical process based on measurements collected by a wireless sensor network. The proposed setup is the prototype of an industrial application in which a remote station controls the process via wireless network links. The experimental platform is a laboratory process consisting of four infrared lamps, controlled in pairs by two on/off switches, and of a transport belt, where moving parts equipped with wireless sensors are heated by the lamps. By approximating the stationary heat spatial distribution as a piecewise affine function of the position along the belt, the resulting plant model is a hybrid dynamical system. The control architecture is based on the reference governor approach: the process is actuated by a local controller, while a hybrid MPC algorithm running on a remote base station sends optimal belt velocity set-points and lamp on/off commands over a network link exploiting the information received through the wireless network. A discrete-time hybrid model of the process is used for the hybrid MPC algorithm and for the state estimator.
Place, publisher, year, edition, pages
New Orleans, Louisiana, USA., 2007. 5062-5067 p.
IdentifiersURN: urn:nbn:se:kth:diva-58487ScopusID: 2-s2.0-62749205480OAI: oai:DiVA.org:kth-58487DiVA: diva2:473150
46th IEEE Conference on Decision and Control, 12-14 Dec 2007
QC 201201122012-01-052012-01-052012-01-16Bibliographically approved