How good is quantized model predictive control with horizon one?

Title: How good is quantized model predictive control with horizon one?
Creator: Müller, Claus; Quevedo, Daniel E.; Goodwin, Graham C.
Relation: IEEE Transactions on Automatic Control Vol. 56, Issue 11, p. 2623-2638
Publisher Link: http://dx.doi.org/10.1109/TAC.2011.2122610
Publisher: Institute of Electrical and Electronics Engineers (IEEE)
Resource Type: journal article
Date: 2011
Description: Model Predictive Control is increasingly being used in areas where decision variables are constrained to finite or countably infinite sets. Well known fields include Power Electronics, Signal Processing, and Telecommunications. Typically, the applications utilize high speed sampling and, thus, there is an incentive to reduce computational burden. One way of achieving this is to use small optimization horizons. This raises the question as to the optimality and performance of control laws with short horizons. In this paper, we give necessary and sufficient conditions for horizon one quantized model predictive control to be equivalent to the use of larger horizons. We also explore situations where horizon one is near optimal.
Subject: optimality; predictive control; quantization
Identifier: http://hdl.handle.net/1959.13/921848
Identifier: uon:9417
Identifier: ISSN:0018-9286
Language: eng
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