Title :
Indirect iterative learning control: Application on artificial pancreatic β-cell
Author :
Wang, Youqing ; Doyle, Francis J., III
Author_Institution :
Dept. of Chem. Eng., Univ. of California, Santa Barbara, CA, USA
Abstract :
Most existing iterative learning control (ILC) algorithms work in direct pattern; while indirect ILC is an open problem. In this paper, model predictive control (MPC) is chosen as the local controller for processes and ILC is used to update the setpoint for MPC; this novel combination belongs to indirect ILC and is named ILC-based MPC in this paper. Indirect ILC has revealed some advantages compared to direct ILC. The proposed algorithm is validated in artificial pancreatic beta-cell and the simulation results verify the effectiveness and excellence of this method.
Keywords :
adaptive control; iterative methods; learning systems; medical control systems; predictive control; ILC-based MPC; artificial pancreatic beta-cell; direct pattern; indirect iterative learning control; model predictive control; Cardiac disease; Control systems; Diabetes; Insulin; Iterative algorithms; Pancreas; Predictive control; Predictive models; Sugar; Three-term control; glucose control; indirect pattern; iterative learning control; model predictive control;
Conference_Titel :
Control and Decision Conference, 2009. CCDC '09. Chinese
Conference_Location :
Guilin
Print_ISBN :
978-1-4244-2722-2
Electronic_ISBN :
978-1-4244-2723-9
DOI :
10.1109/CCDC.2009.5192271
