文献类型：期刊文献

英文题名：Value-iteration-based Adaptive Optimal Reagents Control for Antimony Flotation Process

作者：Li, Zhongmei[1]; Huang, Mengzhe[2]; Gui, Weihua[3]; Jiang, Zhong-Ping[2]

机构：[1] East China University of Science and Technology, School of Information Science and Engineering, Shanghai, 200237, China; [2] New York University, Tandon School of Engineering, Brooklyn, NY, 11201, United States; [3] Central South University, School of Automation, Changsha, 410083, China

年份：2020

卷号：2020-July

起止页码：2244

外文期刊名：Chinese Control Conference, CCC

收录：EI(收录号：20203909242543)

语种：英文

外文关键词：Adaptive control systems - Riccati equations - Antimony - Iterative methods - Disturbance rejection - Flotation - Time delay - Dynamic programming - Timing circuits - Delay control systems

摘要：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. ? 2020 Technical Committee on Control Theory, Chinese Association of Automation.