DocumentCode
2136536
Title
Adaptive Unified Predictive Control applied to first-order-plus-dead-time processes to eliminate unknown class of deterministic disturbance
Author
Lin, Shu-Kai ; Lee, An-Chen
Author_Institution
Dept. of Mech. Eng., Nat. Chiao-Tung Univ., Hsinchu, Taiwan
fYear
2011
fDate
11-15 April 2011
Firstpage
149
Lastpage
156
Abstract
A novel Adaptive Unified Predictive Control method (Adaptive-UPC) is proposed and applied to the first-order-plus-dead-time (FOPDT) process models with model uncertainties under unknown deterministic disturbances. Based on Indirect Self-tuning Regulator, this new control structure is constructed by combining UPC controller, Recursive Least-Squares Estimation with forgetting factor (RLS with forgetting factor) and Variable Regression Estimation (VRE). The simulation results show that the method can be effectively applied to first-order-plus-dead-time (FOPDT) process models with uncertain process parameters (gain, time constant and dead-time) and unknown deterministic disturbance.
Keywords
adaptive control; least squares approximations; predictive control; recursive estimation; regression analysis; self-adjusting systems; uncertain systems; adaptive unified predictive control method; deterministic disturbance elimination; first-order-plus-dead-time process model; indirect self-tuning regulator; recursive least-squares estimation; variable regression estimation; First order plus dead time process; Model uncertainty; RLS with forgetting factor; Unified predictive control; Unknown disturbance; VRE;
fLanguage
English
Publisher
ieee
Conference_Titel
Computational Intelligence in Control and Automation (CICA), 2011 IEEE Symposium on
Conference_Location
Paris
Print_ISBN
978-1-4244-9902-1
Type
conf
DOI
10.1109/CICA.2011.5945741
Filename
5945741
Link To Document