.png){kind=icon}
.png){kind=icon}
Return
Global Coordinated Distributed Predictive Control Algorithm Based on System Dynamic Decomposition Index
.png){kind=icon}
OA
AI
DOI：10.1109/ACCESS.2019.2948292.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Distributed model predictive control algorithms have been widely used in the field of process control of large system. However, there is no effective way to deal with subsystem decomposition and subsystem coordination strategies. This paper proposes a global coordinated distributed predictive control algorithm based on system dynamic decomposition index to solve this problem. Firstly, the dynamic partial least squares algorithm is adopted to decompose the large system into individual subsystems. In the decomposition process a correlation index matrix is constructed, which is simultaneously applied to weight the interaction of subsystems in the control strategy design of each subsystem. By this way the control coordination among subsystems is based on the true interaction rather than blindness. Finally, the proposed algorithm was applied to the chemical process of Shell Heavy Oil Fractionator to verify its effectiveness and feasibility.
Keywords:
Heuristic algorithms
Indexes
Prediction algorithms
Correlation
Predictive control
Input variables
Coordination strategy
dynamic partial least squares
model predictive control
system decomposition
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.