### Abstract

The control problem of an agitated contactor is considered in this work. A Scheibel extraction column is modeled using the non-equilibrium backflow mixing cell model. Model dynamic analysis shows that this process is highly nonlinear, thus the control problem solution of such a system needs to tackle the process nonlinearity efficiently. The control problem of this process is solved by developing a multivariable nonlinear control system implemented in MATLAB™. In this control methodology, a new controller tuning method is adopted, in which the time-domain control parameter-tuning problem is solved as a constrained optimization problem. A MIMO (multi-input multi-output) PI controller structure is used in this strategy. The centralized controller uses a 2 × 2 transfer function and accounts for loops interaction. The controller parameters are tuned using an optimization-based algorithm with constraints imposed on the process variables reference trajectories. Incremental tuning procedure is performed until the extractor output variables transient response satisfies a preset uncertainty which bounds around the reference trajectory. A decentralized model-based IMC (internal model control) control strategy is compared with the newly developed centralized MIMO PI control one. Stability and robustness tests are applied to the two algorithms. The performance of the MIMO PI controller is found to be superior to that of the conventional IMC controller in terms of stability, robustness, loops interaction handling, and step-change tracking characteristics.

Original language | English |
---|---|

Pages (from-to) | 561-582 |

Number of pages | 22 |

Journal | Solvent Extraction and Ion Exchange |

Volume | 23 |

Issue number | 4 |

DOIs | |

Publication status | Published - Jul 2005 |

### Fingerprint

### Keywords

- Centralized control
- Internal model control
- Liquid-liquid extraction
- Multivariable control
- NCD
- Nonlinear control
- Scheibel extractor

### ASJC Scopus subject areas

- Chemistry(all)
- Filtration and Separation

### Cite this

**Optimization-based nonlinear centralized controller tuning of liquid-liquid extraction processes.** / Mjalli, Farouq S.

Research output: Contribution to journal › Article

}

TY - JOUR

T1 - Optimization-based nonlinear centralized controller tuning of liquid-liquid extraction processes

AU - Mjalli, Farouq S.

PY - 2005/7

Y1 - 2005/7

N2 - The control problem of an agitated contactor is considered in this work. A Scheibel extraction column is modeled using the non-equilibrium backflow mixing cell model. Model dynamic analysis shows that this process is highly nonlinear, thus the control problem solution of such a system needs to tackle the process nonlinearity efficiently. The control problem of this process is solved by developing a multivariable nonlinear control system implemented in MATLAB™. In this control methodology, a new controller tuning method is adopted, in which the time-domain control parameter-tuning problem is solved as a constrained optimization problem. A MIMO (multi-input multi-output) PI controller structure is used in this strategy. The centralized controller uses a 2 × 2 transfer function and accounts for loops interaction. The controller parameters are tuned using an optimization-based algorithm with constraints imposed on the process variables reference trajectories. Incremental tuning procedure is performed until the extractor output variables transient response satisfies a preset uncertainty which bounds around the reference trajectory. A decentralized model-based IMC (internal model control) control strategy is compared with the newly developed centralized MIMO PI control one. Stability and robustness tests are applied to the two algorithms. The performance of the MIMO PI controller is found to be superior to that of the conventional IMC controller in terms of stability, robustness, loops interaction handling, and step-change tracking characteristics.

AB - The control problem of an agitated contactor is considered in this work. A Scheibel extraction column is modeled using the non-equilibrium backflow mixing cell model. Model dynamic analysis shows that this process is highly nonlinear, thus the control problem solution of such a system needs to tackle the process nonlinearity efficiently. The control problem of this process is solved by developing a multivariable nonlinear control system implemented in MATLAB™. In this control methodology, a new controller tuning method is adopted, in which the time-domain control parameter-tuning problem is solved as a constrained optimization problem. A MIMO (multi-input multi-output) PI controller structure is used in this strategy. The centralized controller uses a 2 × 2 transfer function and accounts for loops interaction. The controller parameters are tuned using an optimization-based algorithm with constraints imposed on the process variables reference trajectories. Incremental tuning procedure is performed until the extractor output variables transient response satisfies a preset uncertainty which bounds around the reference trajectory. A decentralized model-based IMC (internal model control) control strategy is compared with the newly developed centralized MIMO PI control one. Stability and robustness tests are applied to the two algorithms. The performance of the MIMO PI controller is found to be superior to that of the conventional IMC controller in terms of stability, robustness, loops interaction handling, and step-change tracking characteristics.

KW - Centralized control

KW - Internal model control

KW - Liquid-liquid extraction

KW - Multivariable control

KW - NCD

KW - Nonlinear control

KW - Scheibel extractor

UR - http://www.scopus.com/inward/record.url?scp=23944512208&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=23944512208&partnerID=8YFLogxK

U2 - 10.1081/SEI-200062607

DO - 10.1081/SEI-200062607

M3 - Article

AN - SCOPUS:23944512208

VL - 23

SP - 561

EP - 582

JO - Solvent Extraction and Ion Exchange

JF - Solvent Extraction and Ion Exchange

SN - 0736-6299

IS - 4

ER -