Advanced model predictive control strategies for evaporation processes in the pharmaceutical industries

被引:2
|
作者
Nascu, Ioana [1 ]
Diangelakis, Nikolaos A. [2 ]
Munoz, Salvador Garcia [3 ]
Pistikopoulos, Efstratios N. [4 ,5 ]
机构
[1] Tech Univ Cluj Napoca, Fac Automat & Comp Sci, Dept Automat, Cluj Napoca 400114, Romania
[2] Tech Univ Crete, Sch Chem & Environm Engn, Khania 73100, Greece
[3] Eli Lilly & Co, LillyResearch Labs, Synthet Mol Design & Dev, Indianapolis, IN 46074 USA
[4] Texas A&M Univ, Texas A&M Energy Inst, College Stn, TX USA
[5] Texas A&M Univ, Artie McFerrin Dept Chem Engn, College Stn, TX USA
关键词
Evaporation process; Pharmaceuticals; Process control; PID; MPC; Multiparameric; explicit model based; predictive control; OPTIMIZATION; DESIGN; QUALITY; PERSPECTIVES;
D O I
10.1016/j.compchemeng.2023.108212
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper we present a framework to design control systems for an evaporation process in the pharmaceutical industry with the aim to deliver guaranteed operability for different molecules and under different thermody-namic scenarios. Based on a mathematical model developed within the gPROMS platform calibrated and vali-dated with real data from experiments, three control methods are implemented and compared, (i) Proportional Integrative Derivative control (PID), (ii) Model Predictive Control (MPC) and (iii) explicit/multi-parametric Model Predictive Control (mp-MPC). The performance and limits of the derived control schemes are then established and tested for reference tracking as well as disturbances rejection.
引用
收藏
页数:16
相关论文
共 50 条
  • [1] Advanced methodologies for model-based optimization and control of pharmaceutical processes
    Destro, Francesco
    Inguva, Pavan K.
    Srisuma, Prakitr
    Braatz, Richard D.
    CURRENT OPINION IN CHEMICAL ENGINEERING, 2024, 45
  • [2] Advanced model predictive control strategies for nondestructive monitoring quality of fruit and vegetables during supply chain processes
    Zhang, Lihui
    Zhang, Min
    Mujumdar, Arun S.
    Wu, Chenlin
    Wang, Dayuan
    COMPUTERS AND ELECTRONICS IN AGRICULTURE, 2024, 225
  • [3] Nonlinear model predictive control of evaporation process
    Key Laboratory of Integrated Automation of Process Industry, Northeastern University, Shenyang 110004, China
    Dongbei Daxue Xuebao, 2008, 10 (1369-1372):
  • [4] Model Predictive Control OF pH IN Pharmaceutical Process
    Balaji, V.
    Vasudevan, N.
    2009 IEEE INTERNATIONAL CONFERENCE ON MECHATRONICS, VOLS 1 AND 2, 2009, : 762 - +
  • [5] Control and optimization strategies for thermo-mechanical pulping processes: Nonlinear model predictive control
    Harinath, Eranda
    Biegler, L. T.
    Dumont, Guy A.
    JOURNAL OF PROCESS CONTROL, 2011, 21 (04) : 519 - 528
  • [6] Development and implementation of an advanced model predictive control system into continuous pharmaceutical tablet compaction process
    Bhaskar, Aparajith
    Barros, Fernando N.
    Singh, Ravendra
    INTERNATIONAL JOURNAL OF PHARMACEUTICS, 2017, 534 (1-2) : 159 - 178
  • [7] A Survey of Model Predictive Control Development in Automotive Industries
    Swief, Asmaa
    El-Zawawi, Amr
    El-Habrouk, Mohamed
    2019 3RD INTERNATIONAL CONFERENCE ON APPLIED AUTOMATION AND INDUSTRIAL DIAGNOSTICS (ICAAID 2019), 2019,
  • [8] Advanced Control Strategies of Induction Machine: Field Oriented Control, Direct Torque Control and Model Predictive Control
    Wang, Fengxiang
    Zhang, Zhenbin
    Mei, Xuezhu
    Rodriguez, Jose
    Kennel, Ralph
    ENERGIES, 2018, 11 (01):
  • [9] Model predictive control of sputter processes
    Woelfel, Christian
    2023 AMERICAN CONTROL CONFERENCE, ACC, 2023, : 4038 - 4043
  • [10] Model predictive control for multivariable processes
    VanDoren, J
    CONTROL ENGINEERING, 1997, 44 (06) : 87 - 87