Quantized Nonlinear Model Predictive Control for a Building

0448768 - ÚTIA 2016 RIV AU eng C - Konferenční příspěvek (zahraniční konf.)
Pčolka, M. - Žáčeková, E. - Robinett, R. - Čelikovský, Sergej - Šebek, M.
Quantized Nonlinear Model Predictive Control for a Building.
Proceedings of the 2015 IEEE Conference on Control Applications (CCA). Sydney: IEEE, 2015, s. 347-352. ISBN 978-1-4799-7787-1. ISSN 1085-1992.
[IEEE Conference on Control Applications 2015 (CCA 2015). Sydney (AU), 21.09.2015-23.09.2015]
Grant CEP: GA ČR GA13-20433S
Institucionální podpora: RVO:67985556
Klíčová slova: nonlinear model predictive control * building climate control
Kód oboru RIV: BC - Teorie a systémy řízení

In this paper, the task of quantized nonlinear predictive control is addressed. In such case, values of some inputs can be from a continuous interval while for the others, it is required that the optimized values belong to a countable set of discrete values. Instead of very straightforward a posteriori quantization, an alternative algorithm is developed incorporating the quantization aspects directly into the optimization routine. The newly proposed quaNPC algorithm is tested on an example of building temperature control. The results for a broad range of number of quantization steps show that (unlike the naive a posteriori quantization) the quaNPC is able to maintain the control performance close to the performance of the original continuous-valued nonlinear predictive controller and at the same time it significantly decreases the undesirable oscillations of the discrete-valued input.
Trvalý link: http://hdl.handle.net/11104/0250397