Please use this identifier to cite or link to this item:
Title: Integral-square-error performance of multiplexed model predictive control
Authors: Ling, K.V.
Ho, W.K. 
Feng, Y.
Wu, B.
Keywords: Control systems analysis
performance evaluation
predictive control
semiconductor process modeling
Issue Date: May-2011
Citation: Ling, K.V., Ho, W.K., Feng, Y., Wu, B. (2011-05). Integral-square-error performance of multiplexed model predictive control. IEEE Transactions on Industrial Informatics 7 (2) : 196-203. ScholarBank@NUS Repository.
Abstract: It is well-known that faster sampling increases computational load but gives better performance. Multiplexed Model Predictive Control (MMPC) has been proposed recently. Its motivation was to reduce real-time computational load. The reduction in computational load can be used gainfully to increase sampling rate and improve performance. Hence, in this paper, we derive a formula to compute the Integral-Square-Error (ISE) performance of a MMPC controlled system. Given the plant and disturbance models, the ISE formula derived allows one to investigate how the ISE changes with control design parameters, such as the sampling interval and control weighting. This enables one to select, for example, a suitable sampling interval for the MMPC design to achieve the desired ISE performance. In addition, we validated the ISE formula on a multizone semiconductor manufacturing thermal process. © 2011 IEEE.
Source Title: IEEE Transactions on Industrial Informatics
ISSN: 15513203
DOI: 10.1109/TII.2011.2106451
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.


checked on Jun 8, 2021


checked on Jun 8, 2021

Page view(s)

checked on Jun 10, 2021

Google ScholarTM



Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.