scholarly journals Time-Varying Scheme for Noncentralized Model Predictive Control of Large-Scale Systems

2015 ◽  
Vol 2015 ◽  
pp. 1-17 ◽  
Author(s):  
Alfredo Núñez ◽  
Carlos Ocampo-Martinez ◽  
José María Maestre ◽  
Bart De Schutter
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Large Scale ◽  
Reduction Methods ◽  
Predictive Controller ◽  
Online Methods ◽  
Water Tanks ◽  
Predictive Controllers ◽  
Decentralized Model

The noncentralized model predictive control (NC-MPC) framework in this paper refers to any distributed, hierarchical, or decentralized model predictive controller (or a combination of them) the structure of which can change over time and the control actions of which are not obtained based on a centralized computation. Within this framework, we propose suitable online methods to decide which information is shared and how this information is used between the different local predictive controllers operating in a decentralized, distributed, and/or hierarchical way. Evaluating all the possible structures of the NC-MPC controller leads to a combinatorial optimization problem. Therefore, we also propose heuristic reduction methods, to keep the number of NC-MPC problems tractable to be solved. To show the benefits of the proposed framework, a case study of a set of coupled water tanks is presented.

Coordinated Model Predictive Control on Multi-Lane Roads

2019 ◽  
Author(s):  
Nathan Goulet ◽  
Beshah Ayalew
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Autonomous Vehicles ◽  
Large Scale ◽  
Heterogeneous Traffic ◽  
Road Transportation ◽  
The Road ◽  
Energy Saving Potential ◽  
Coordination Scheme ◽  
Predictive Controller

Abstract There are significant economic, environmental, energy, and other societal costs incurred by the road transportation sector. With the advent and penetration of connected and autonomous vehicles there are vast opportunities to optimize the control of individual vehicles for reducing energy consumption and increasing traffic flow. Model predictive control is a useful tool to achieve such goals, while accommodating ego-centric objectives typical of heterogeneous traffic and explicitly enforcing collision and other constraints. In this paper, we describe a multi-agent distributed maneuver planning and lane selection model predictive controller that includes an information sharing and coordination scheme. The energy saving potential of the proposed coordination scheme is then evaluated via large scale microscopic traffic simulations considering different penetration levels of connected and automated vehicles.

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.

RECEDING HORIZON FUZZY OPTIMIZATION UNDER LOCAL INFORMATION ENVIRONMENT WITH A CASE STUDY

2004 ◽  
Vol 03 (01) ◽  
pp. 109-127 ◽  
Author(s):  
SHAO-YUAN LI ◽  
HU WU ◽  
YI-PENG YANG
Keyword(s):  
Model Predictive Control ◽  
Control Systems ◽  
Predictive Control ◽  
Fuzzy Theory ◽  
Fuzzy Optimization ◽  
Decision Function ◽  
Fuzzy Constraints ◽  
Fuzzy Goals ◽  
Predictive Controller

Model predictive control (MPC) has been used in process control systems with constraints; however, the constrained optimization problem involved in control systems has generally been solved in practice in a piece-meal fashion. To solve the problem systemically, in this paper, the Multi-Objective Fuzzy-Optimization (MOFO) is used in the constrained predictive control for online applications as a means of dealing with fuzzy goals and fuzzy constraints in control systems. The conventional model predictive control is integrated with the techniques from fuzzy multi-criteria decision making, translating the goals and the constraints to predictive control in a transparent way. The information regarding the fuzzy goals and the fuzzy constraints of the control problem is combined by using a decision function from the fuzzy theory, so it is possible to aggregate the fuzzy goals and the fuzzy constraints using fuzzy operators, e.g. t-norms, s-norms or the convex sum. It is shown that the model predictive controller based on MOFO allows the designers for a more flexible aggregation of the control objectives than the usual weighting sum of squared errors in MPC. The visual robot path planning validates the efficiency of the presented algorithm.

scholarly journals Model Predictive Control of a Food Production Unit: A Case Study for Lettuce Production

2020 ◽  
Vol 53 (2) ◽  
pp. 15771-15776
Author(s):  
Murali Padmanabha ◽  
Lukas Beckenbach ◽  
Stefan Streif
Keyword(s):  
Model Predictive Control ◽  
Predictive Control ◽  
Food Production ◽  
Production Unit
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