By Topic

Constrained distributed model predictive control strategy based on agent coordination

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$33 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

3 Author(s)
Yang Danxuan ; Key Laboratory of Advanced Control and Optimization for Chemical Processes of Ministry of Education, East China University of Science and Technology, Shanghai 200237 ; Wang Mengling ; Shi Hongbo

In this paper, a distributed model predictive control (DMPC) strategy is proposed based on agent coordination, in which subsystems couple through the inputs. At first, the initial feasible solution of each agent can be achieved by solving local optimization problems in which the state constraints of neighbor subsystems are considered at each sampling time. And then the global optimal solution can be obtained through agent coordination. In the negotiating process, the innovative global optimization objective is determined for the sake of reducing iteration time and improving the convergence speed efficiently. Finally, the accuracy and efficiency of the proposed scheme is put to test through simulation.

Published in:

Control Conference (CCC), 2012 31st Chinese

Date of Conference:

25-27 July 2012