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
Link To Document :
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