Value-iteration-based Adaptive Optimal Reagents Control for Antimony Flotation Process

Zhongmei Li, Mengzhe Huang, Weihua Gui, Zhong Ping Jiang

Research output: Chapter in Book/Report/Conference proceedingConference contribution


This paper investigates a data-driven adaptive optimal control approach for antimony flotation process in presence of input time-delay and disturbance. The integration frame of adaptive dynamic programming (ADP) and value iteration (VI) is applied to the optimal controller design without requirement of system dynamics. Fundamentally different from the existing reagents control methods, the input time-delay and disturbance are simultaneously considered in the VI-based ADP control scheme. Specifically, the disturbance is compensated directly by adding an inner model as the feedforward component to the control action and the optimal feedback gain is computed by iteratively solving Riccati equation. By exploiting industrial collected data, the numerical simulation proves that the proposed data-driven methodology can enable the concentrate and tailing grade to keep tracking the target trajectories with a minimum reagents consumption.

Original languageEnglish (US)
Title of host publicationProceedings of the 39th Chinese Control Conference, CCC 2020
EditorsJun Fu, Jian Sun
PublisherIEEE Computer Society
Number of pages8
ISBN (Electronic)9789881563903
StatePublished - Jul 2020
Event39th Chinese Control Conference, CCC 2020 - Shenyang, China
Duration: Jul 27 2020Jul 29 2020

Publication series

NameChinese Control Conference, CCC
ISSN (Print)1934-1768
ISSN (Electronic)2161-2927


Conference39th Chinese Control Conference, CCC 2020


  • Disturbance rejection
  • Flotation process
  • Input time-delay
  • Optimal control

ASJC Scopus subject areas

  • Computer Science Applications
  • Control and Systems Engineering
  • Applied Mathematics
  • Modeling and Simulation


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