Abstract
This work presents the design and implementation results of a model predictive control strategy used to control the pulp level of a Rougher flotation circuit in a mine located in the third region of Chile, which is composed by five flotation banks. The strategy considers a state space representation to model the pulp level of each bank (with a multiple input - single output model), which is obtained by a system identification procedure and uses a Kalman filter as a state estimator. To solve the optimization problem that calculates the control law, a genetic algorithm based optimization tool is used. Experimental data is used to show the results of the proposed control strategy.
Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callMore From: Revista Iberoamericana de Automática e Informática Industrial
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
