DocumentCode
631850
Title
PID gain scheduling by parametric model predictive control
Author
Nguyen, Minh H.-T ; Kok Kiong Tan ; Chek Sing Teo
Author_Institution
SIMTech-NUS Joint Lab. (Precision Motion Syst.), Nat. Univ. of Singapore, Singapore, Singapore
fYear
2013
fDate
9-12 July 2013
Firstpage
944
Lastpage
948
Abstract
This paper considers the problem of augmenting the PID structure with the MPC functionality of constraint handling and optimization. Firstly, we review the MPC framework which can be built from a model and a linear feedback gain. This linear gain can be any preexisting multi-loop PID design in the unconstrained case, or based on the two stabilizing PI/PID design for multivariable systems we introduce here. The resulting controller is a feedforward PID mapping, a straightforward form without the need of tuning PID to fit an optimal input. Secondly, the parametric solution of MPC further suggests a PID network implementation by utilizing gain scheduling schemes available in industry.
Keywords
control system synthesis; multivariable systems; optimisation; predictive control; stability; three-term control; MPC framework; PID gain scheduling scheme; constraint handling; feedforward PID mapping; linear feedback gain; multi-loop PID design; multivariable systems; optimization; parametric model predictive control; Feedforward neural networks; Optimal control; Output feedback; PD control; Predictive control; Robustness; Steady-state;
fLanguage
English
Publisher
ieee
Conference_Titel
Advanced Intelligent Mechatronics (AIM), 2013 IEEE/ASME International Conference on
Conference_Location
Wollongong, NSW
ISSN
2159-6247
Print_ISBN
978-1-4673-5319-9
Type
conf
DOI
10.1109/AIM.2013.6584215
Filename
6584215
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