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Control strategies for ventilation networks in small‐scale mines using an experimental benchmark
Author(s) -
RodriguezDiaz OscarOswaldo,
NovellaRodriguez David Fernando,
Witrant Emmanuel,
FrancoMejia Edinson
Publication year - 2021
Publication title -
asian journal of control
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.769
H-Index - 53
eISSN - 1934-6093
pISSN - 1561-8625
DOI - 10.1002/asjc.2394
Subject(s) - benchmark (surveying) , actuator , ventilation (architecture) , control engineering , constraint (computer aided design) , control (management) , computer science , scale (ratio) , state space , identification (biology) , work (physics) , wireless sensor network , state space representation , engineering , control theory (sociology) , artificial intelligence , mechanical engineering , statistics , physics , mathematics , geodesy , algorithm , quantum mechanics , geography , computer network , botany , biology
In view of the frequent ventilation network changes during production in underground mining, decreasing sensors and actuators without altering production control and safety is one of the chief engineering challenges. This work is focused on modeling identification and control strategies for underground ventilation networks in small‐scale mines using an experimental benchmark. Guidelines to obtain a discrete state space model are provided, considering the conservation laws in the network to define the structure of the linear model. The main purpose of the paper is to analyze the use of classic controllers in the mine ventilation system when there are limitations on the number of sensors and actuators available to design a feedback control system. A comparison of three classic control strategies is presented considering the a constraint on the available number of sensors. Experimental and simulation results are presented.