Please use this identifier to cite or link to this item: https://doi.org/10.1145/2350716.2350742
Title: Implementation of model predictive control with modified minimal model on low-power RISC microcontrollers
Authors: Nguyen, B.P. 
Ho, Y.
Wu, Z.
Chui, C.-K. 
Keywords: Embedded system
Glucose regulation
Minimal model
Model predictive control
Issue Date: 2012
Source: Nguyen, B.P.,Ho, Y.,Wu, Z.,Chui, C.-K. (2012). Implementation of model predictive control with modified minimal model on low-power RISC microcontrollers. ACM International Conference Proceeding Series : 165-171. ScholarBank@NUS Repository. https://doi.org/10.1145/2350716.2350742
Abstract: Due to the ability of modeling multivariable systems and handling constraints in the control framework, model predictive control (MPC) has received a lot of interest from both academic and industrial communities. Although it is an established control technique, implementing MPC on small-scale devices is a challenge since we need to handle complicated issues of the control framework using limited computational power and hardware resources. This paper presents our implementation of MPC with constraints on the Texas Instruments MSP430 16-bit microcontroller platform. The MPC operational constraints which are supported in our design include rate of change, amplitude and output constraints, while the associated optimization problem is solved using a primal-dual interior-point algorithm based on predicator-corrector method. Our implementation is demonstrated in a prototype of a real-time closeloop blood glucose regulation system using a modification of the minimal model. Experimental results show that our system is able to achieve desired diabetes management, and the chosen microprocessor is capable of performing the MPC algorithm accurately with high energy-efficiency and in realtime. Copyright © 2012 ACM.
Source Title: ACM International Conference Proceeding Series
URI: http://scholarbank.nus.edu.sg/handle/10635/51607
ISBN: 9781450312325
DOI: 10.1145/2350716.2350742
Appears in Collections:Staff Publications

Show full item record
Files in This Item:
There are no files associated with this item.

Page view(s)

33
checked on Feb 16, 2018

Google ScholarTM

Check

Altmetric


Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.