Control strategies for ventilation networks in small‐scale mines using an experimental benchmark

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.