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Wireless ventilation control for large‐scale systems: The mining industrial case
Author(s) -
Witrant E.,
D'Innocenzo A.,
Sandou G.,
Santucci F.,
Di Benedetto M. D.,
Isaksson A. J.,
Johansson K. H.,
Niculescu S.I.,
Olaru S.,
Serra E.,
Tennina S.,
Tiberi U.
Publication year - 2009
Publication title -
international journal of robust and nonlinear control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.361
H-Index - 106
eISSN - 1099-1239
pISSN - 1049-8923
DOI - 10.1002/rnc.1485
Subject(s) - model predictive control , computer science , abstraction , automation , wireless sensor network , control engineering , wireless , energy consumption , control (management) , scale (ratio) , ventilation (architecture) , distributed computing , real time computing , engineering , artificial intelligence , telecommunications , computer network , mechanical engineering , philosophy , physics , electrical engineering , epistemology , quantum mechanics
This paper describes a new industrial case on automation, for large‐scale systems with high environmental impact: the mining ventilation control systems. Ventilation control is essential for the operation of a mine in terms of safety (CO and NO x regulation) and energy optimization. We first discuss a novel regulation architecture, highlighting the interest for a model‐based control approach and the use of distributed sensing capabilities thanks to a wireless sensor network (WSN). We propose a new model for underground ventilation. The main components of the system dynamics are described with time‐delays, transmission errors, energy losses and concentration profiles. Two different model‐based control approaches, which can embody the complex dynamics of the system, are proposed. The first one resorts to a nonlinear model predictive control strategy (receding horizon) and aims to energy minimization, thanks to a continuous operation of the fans. The second one, based on a hybrid description of the model and fans operation, provides automatic verification of the wireless control thanks to abstraction techniques. These control strategies are compared with simulations, in terms of regulation efficiency, energy consumption and the need for computational capabilities. The industrial case description and control strategies open new vistas for the development of global system approaches that allow for the optimization of energy consumption of complex large‐scale systems. Copyright © 2009 John Wiley & Sons, Ltd.