scholarly journals Distributed Model Predictive Control of Steam/Water Loop in Large Scale Ships

Processes ◽  
2019 ◽  
Vol 7 (7) ◽  
pp. 442 ◽  
Author(s):  
Shiquan Zhao ◽  
Anca Maxim ◽  
Sheng Liu ◽  
Robin De Keyser ◽  
Clara Ionescu
Keyword(s):  
Control System ◽  
Model Predictive Control ◽  
Predictive Control ◽  
Power Plants ◽  
Large Scale ◽  
Distributed Model ◽  
Distributed Model Predictive Control ◽  
Steam Power Plants ◽  
Great Reliability ◽  
The Stability

In modern steam power plants, the ever-increasing complexity requires great reliability and flexibility of the control system. Hence, in this paper, the feasibility of a distributed model predictive control (DiMPC) strategy with an extended prediction self-adaptive control (EPSAC) framework is studied, in which the multiple controllers allow each sub-loop to have its own requirement flexibility. Meanwhile, the model predictive control can guarantee a good performance for the system with constraints. The performance is compared against a decentralized model predictive control (DeMPC) and a centralized model predictive control (CMPC). In order to improve the computing speed, a multiple objective model predictive control (MOMPC) is proposed. For the stability of the control system, the convergence of the DiMPC is discussed. Simulation tests are performed on the five different sub-loops of steam/water loop. The results indicate that the DiMPC may achieve similar performance as CMPC while outperforming the DeMPC method.

scholarly journals Distributed Model Predictive Control over Multiple Groups of Vehicles in Highway Intelligent Space for Large Scale System

2014 ◽  
Vol 2014 ◽  
pp. 1-12
Author(s):  
Tang Xiaofeng ◽  
Gao Feng ◽  
Xu Guoyan ◽  
Ding Nenggen ◽  
Cai Yao ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Large Scale ◽  
Distributed Model ◽  
Large Scale System ◽  
Control Approach ◽  
Distributed Model Predictive Control ◽  
Intelligent Space ◽  
Multiple Groups ◽  
Information Framework

The paper presents the three time warning distances for solving the large scale system of multiple groups of vehicles safety driving characteristics towards highway tunnel environment based on distributed model prediction control approach. Generally speaking, the system includes two parts. First, multiple vehicles are divided into multiple groups. Meanwhile, the distributed model predictive control approach is proposed to calculate the information framework of each group. Each group of optimization performance considers the local optimization and the neighboring subgroup of optimization characteristics, which could ensure the global optimization performance. Second, the three time warning distances are studied based on the basic principles used for highway intelligent space (HIS) and the information framework concept is proposed according to the multiple groups of vehicles. The math model is built to avoid the chain avoidance of vehicles. The results demonstrate that the proposed highway intelligent space method could effectively ensure driving safety of multiple groups of vehicles under the environment of fog, rain, or snow.

Distributed Model Predictive Control and Estimation of Large-Scale Multi-Rate Systems

2011 ◽  
Vol 44 (1) ◽  
pp. 416-422 ◽  
Author(s):  
Samira Roshany-Yamchi ◽  
Rudy R. Negenborn ◽  
Marcin Cychowski ◽  
Bart De Schutter ◽  
Joe Connell ◽  
...  
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Large Scale ◽  
Distributed Model ◽  
Distributed Model Predictive Control
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