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Adaptive Decoupling Control of Pulp Levels in Flotation Cells
Author(s) -
Li Haibo,
Chai Tianyou,
Fu Jun,
Wang Hong
Publication year - 2013
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.720
Subject(s) - control theory (sociology) , decoupling (probability) , nonlinear system , adaptive neuro fuzzy inference system , adaptive control , control engineering , fuzzy control system , fuzzy logic , computer science , engineering , control (management) , artificial intelligence , physics , quantum mechanics
Abstract Control of the pulp levels in flotation cells directly affects the grade of the concentrate and the tailings in a concentration plant. Nevertheless, with strong coupling among cell levels and nonlinearities in the flotation process, conventional control strategies cannot achieve satisfactory control performance. In this paper, a nonlinear multi‐model adaptive decoupling control strategy based on adaptive‐network‐based fuzzy inference systems ( ANFIS ) is proposed for the flotation process, which includes a linear adaptive decoupling controller, an ANFIS ‐based nonlinear adaptive decoupling controller, and a switching mechanism. The proposed method not only improves the transient performance and mitigates effects of the nonlinearities on the system, but also guarantees the input‐output stability of the closed‐loop system. Successful application to the flotation process has been made in a concentration plant in C hina, and the feasibility and efficiency of the proposed method have been validated.