Distributed model predictive control algorithm based on event-trigger

2017 ◽  
Author(s):  
Minghao Chen ◽  
Yuanlong Liu ◽  
Jun Zhao ◽  
Zuhua Xu
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Distributed Model ◽  
Distributed Model Predictive Control ◽  
Event Trigger ◽  
Model Predictive Control Algorithm

scholarly journals Reference Tracking using a Non-Cooperative Distributed Model Predictive Control Algorithm

2016 ◽  
Vol 49 (7) ◽  
pp. 1079-1084 ◽  
Author(s):  
Anca Maxim ◽  
Clara M. Ionescu ◽  
Constantin F. Caruntu ◽  
Corneliu Lazar ◽  
Robin De Keyser
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Control Algorithm ◽  
Distributed Model ◽  
Reference Tracking ◽  
Distributed Model Predictive Control ◽  
Model Predictive Control Algorithm

scholarly journals Improved Distributed Model Predictive Control with Control Planning Set

2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Wei Chen
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
System Performance ◽  
Control Algorithm ◽  
Distributed Model ◽  
Distributed Model Predictive Control ◽  
Exchange Information ◽  
Predictive Controller ◽  
Model Predictive Control Algorithm ◽  
The Stability

We focus on distributed model predictive control algorithm. Each distributed model predictive controller communicates with the others in order to compute the control sequence. But there are not enough communication resources to exchange information between the subsystems because of the limited communication network. This paper presents an improved distributed model predictive control scheme with control planning set. Control planning set algorithm approximates the future control sequences by designed planning set, which can reduce the exchange information among the controllers and can also decrease the distributed MPC controller calculation demand without degrading the whole system performance much. The stability and system performance analysis for distributed model predictive control are given. Simulations of the four-tank control problem and multirobot multitarget tracking problem are illustrated to verify the effectiveness of the proposed control algorithm.

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