scholarly journals Distributed Model Predictive Control Applied to a Sewer System

Processes ◽  
2020 ◽  
Vol 8 (12) ◽  
pp. 1595
Author(s):  
Antonio Cembellín ◽  
Mario Francisco ◽  
Pastora Vega
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
System Performance ◽  
Treatment Plant ◽  
Distributed Model ◽  
Sewer System ◽  
Distributed Model Predictive Control ◽  
Model Predictive Controllers ◽  
Predictive Controllers ◽  
Decentralized Model

In this work, a Distributed Model Predictive Control (MPC) methodology with fuzzy negotiation among subsystems has been developed and applied to a simulated sewer network. The wastewater treatment plant (WWTP) receiving this wastewater has also been considered in the methodology by means of an additional objective for the problem. In order to decompose the system into interconnected local subsystems, sectorization techniques have been applied based on structural analysis. In addition, a dynamic setpoint generation method has been added to improve system performance. The results obtained with the proposed methodology are compared to those obtained with standard centralized and decentralized model predictive controllers.

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.

scholarly journals A Coalitional Distributed Model Predictive Control Perspective for a Cyber-Physical Multi-Agent Application

Sensors ◽  
2021 ◽  
Vol 21 (12) ◽  
pp. 4041
Author(s):  
Anca Maxim ◽  
Constantin-Florin Caruntu
Keyword(s):  
Model Predictive Control ◽  
Communication Networks ◽  
Predictive Control ◽  
Technological Development ◽  
Distributed Model ◽  
Multi Agent Systems ◽  
Test Scenario ◽  
Distributed Model Predictive Control ◽  
Multi Agent ◽  
And Performance

Following the current technological development and informational advancement, more and more physical systems have become interconnected and linked via communication networks. The objective of this work is the development of a Coalitional Distributed Model Predictive Control (C- DMPC) strategy suitable for controlling cyber-physical, multi-agent systems. The motivation behind this endeavour is to design a novel algorithm with a flexible control architecture by combining the advantages of classical DMPC with Coalitional MPC. The simulation results were achieved using a test scenario composed of four dynamically coupled sub-systems, connected through an unidirectional communication topology. The obtained results illustrate that, when the feasibility of the local optimization problem is lost, forming a coalition between neighbouring agents solves this shortcoming and maintains the functionality of the entire system. These findings successfully prove the efficiency and performance of the proposed coalitional DMPC method.

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
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