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A parallel fixed‐point predictive controller
Author(s) -
Kadlec J.,
Gaston F. M. F.,
Irwin G. W.
Publication year - 1997
Publication title -
international journal of adaptive control and signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.73
H-Index - 66
eISSN - 1099-1115
pISSN - 0890-6327
DOI - 10.1002/(sici)1099-1115(199708)11:5<415::aid-acs416>3.0.co;2-j
Subject(s) - normalization (sociology) , a priori and a posteriori , computer science , control theory (sociology) , model predictive control , very large scale integration , controller (irrigation) , fixed point , regularization (linguistics) , control engineering , mathematics , artificial intelligence , embedded system , engineering , control (management) , mathematical analysis , philosophy , epistemology , sociology , anthropology , agronomy , biology
A parallel fixed‐point implementation of a general predictive controller is derived. It is based on the concepts of predictive control outlined by Chisci, Zappa and Mosca. These controllers use parallel identification arrays as the basic building blocks. In this paper the largest part of the standard information filter array is replaced with a similar array which uses normalized data suitable for fixed‐point VLSI implementation. The normalization ensures that all the data are within the range [−1, 1]. The controller includes an effective regularization scheme which allows a priori information about the plant and the controller to be included and kept permanently present in the identification scheme. Users can select the level of the influence of this a priori information on the controller adaptation relative to the effect of the measured data. The resultant architecture is suitable for fixed‐point VLSI or DSP application aiming for low power and minimal complexity or maximal speed. © 1997 John Wiley & Sons, Ltd.