SCI和EI收录∣中国化工学会会刊

Chinese Journal of Chemical Engineering ›› 2012, Vol. 20 ›› Issue (6): 1206-1212.

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Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process*

周平1, 向波2, 柴天佑1   

  1. 1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;
    2. Automation Department, Tangshan College, Tangshan 063020, China
  • 收稿日期:2012-05-26 修回日期:2012-07-25 出版日期:2012-12-28 发布日期:2012-12-28
  • 通讯作者: ZHOU Ping,E-mail:zhouping@mail.neu.edu.cn
  • 基金资助:
    Supported by the National Natural Science Foundation of China (61104084;61290323);the Guangdong Education University-Industry Cooperation Projects (2010B090400410)

Improved Disturbance Observer (DOB) Based Advanced Feedback Control for Optimal Operation of a Mineral Grinding Process*

ZHOU Ping1, XIANG Bo2, CHAI Tianyou1   

  1. 1. State Key Laboratory of Synthetical Automation for Process Industries, Northeastern University, Shenyang 110819, China;
    2. Automation Department, Tangshan College, Tangshan 063020, China
  • Received:2012-05-26 Revised:2012-07-25 Online:2012-12-28 Published:2012-12-28
  • Supported by:
    Supported by the National Natural Science Foundation of China (61104084;61290323);the Guangdong Education University-Industry Cooperation Projects (2010B090400410)

摘要: Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization.Since the MPC does not handle disturbances directly by controller design,it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties.In this paper,an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation.The improved DOB is based on the optimal achievable H2 performance and can deal with disturbance observation for the nonminimum-phase delay systems.In this DOB-MPC advanced feedback control,the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level.The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system.The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties.Several simulations are performed to demonstrate the proposed control method for grinding process operation.

关键词: disturbance observer, model predictive control, advanced feedback control, grinding process, steady-state optimization, disturbance rejection

Abstract: Advanced feedback control for optimal operation of mineral grinding process is usually based on the model predictive control (MPC) dynamic optimization.Since the MPC does not handle disturbances directly by controller design,it cannot achieve satisfactory effects in controlling complex grinding processes in the presence of strong disturbances and large uncertainties.In this paper,an improved disturbance observer (DOB) based MPC advanced feedback control is proposed to control the multivariable grinding operation.The improved DOB is based on the optimal achievable H2 performance and can deal with disturbance observation for the nonminimum-phase delay systems.In this DOB-MPC advanced feedback control,the higher-level optimizer computes the optimal operation points by maximize the profit function and passes them to the MPC level.The MPC acts as a presetting controller and is employed to generate proper pre-setpoint for the lower-level basic feedback control system.The DOB acts as a compensator and improves the operation performance by dynamically compensating the setpoints for the basic control system according to the observed various disturbances and plant uncertainties.Several simulations are performed to demonstrate the proposed control method for grinding process operation.

Key words: disturbance observer, model predictive control, advanced feedback control, grinding process, steady-state optimization, disturbance rejection