Please use this identifier to cite or link to this item:
|Title:||Integral-square-error performance of multiplexed model predictive control|
|Keywords:||Control systems analysis|
semiconductor process modeling
|Source:||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. https://doi.org/10.1109/TII.2011.2106451|
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Dec 6, 2017
WEB OF SCIENCETM
checked on Nov 22, 2017
checked on Dec 17, 2017
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.