DOB based model predictive control for grinding and classification circuits

WANG Hongchao; GUO Cong; YANG Jun; CHEN Xisong

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DOB based model predictive control for grinding and classification circuits

更新时间：2025-12-10

- DOB based model predictive control for grinding and classification circuits
- CIESC Journal Issue 8, Pages: 2170-2175(2011)
- 作者机构：
  
  东南大学自动化学院,江苏,南京,210096
- 作者简介：
- 基金信息：
- DOI：
  CLC： P273
- Online First：05 August 2011，
  
  Published：05 August 2011
- 稿件说明：
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WANG Hongchao, GUO Cong, YANG Jun, et al. DOB based model predictive control for grinding and classification circuits[J]. CIESC Journal, 2011, (8): 2170-2175.
DOI：

WANG Hongchao, GUO Cong, YANG Jun, et al. DOB based model predictive control for grinding and classification circuits[J]. CIESC Journal, 2011, (8): 2170-2175. DOI：

摘要

磨矿分级过程（GCP）是冶金选矿行业的关键流程，其产品粒度指标必须严格控制，以保证精矿产品品位和金属回收率。GCP本质上是一个多变量强耦合过程，具有时滞和逆向特性，且存在强扰动。扰动的存在造成系统控制性能变差，甚至不稳定。以两输入两输出GCP为研究对象，提出了一种基于扰动观测器（DOB）的模型预测控制（MPC）复合控制方案DOB-MPC。仿真研究表明DOB-MPC不仅可以有效抑制GCP的外部扰动，而且可以抑制由模型失配和变量之间的耦合而导致的内部扰动;在获得良好的解耦控制能力的同时，取得了满意的抗扰动性能。

Abstract

Grinding and classification processes(GCP)are the key unit operations in metallurgical concentration plants.The product particle size directly affects the final product’s ore grade and metal recovery rate.GCP is essentially a multi-input-multi-output(MIMO)system characterized by strong disturbances

dead time and reverse response.Disturbance observer(DOB)based model predictive control(DOB-MPC)is proposed to handle the external and internal disturbances.The simulation results demonstrate that the proposed methods have better disturbance rejection properties than the MPC method

whether in rejecting external disturbances or in rejecting internal disturbances

such as model mismatches and coupling effects.

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