Controle IHMPC de um processo industrial de hidrotratamento de diesel.

Strutzel, Flavio A.M.

doi:10.11606/d.3.2014.tde-24062014-102335

Cited by 1 publication

(2 citation statements)

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“…The state observer (eq 13) uses online measurements (contaminated with noise and uncertainty) and generates results that tend to approximate the measured quantities to the real values. 43,44 The vector Δu (k + j|k) represents the control actions calculated at k + j with measurements realized at time k. However, only the first action of this sequence is applied to the process (Δu (k|k)) in the MPC. Q and R are the positive define diagonal matrices that contain the weight referring to the set point tracking error and control efforts realized by the controller in the manipulated variables and m is the control horizon.…”

Section: ■ Model Predictive Controlmentioning

confidence: 99%

“…Equation represents the feedback action from the process, based on output measured values. The state observer (eq ) uses online measurements (contaminated with noise and uncertainty) and generates results that tend to approximate the measured quantities to the real values. , The vector Δ u ( k + j | k ) represents the control actions calculated at k + j with measurements realized at time k . However, only the first action of this sequence is applied to the process ( Δ u ( k | k )) in the MPC.…”

Section: Model Predictive Controlmentioning

confidence: 99%

See 1 more Smart Citation

Simultaneous Process Design and Control of the Williams–Otto Reactor Using Infinite Horizon Model Predictive Control

Carvalho

Alvarez

2020

Ind. Eng. Chem. Res.

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In this work, we study a simultaneous process design and control methodology using infinite horizon model predictive control (IHMPC). The methodology is based on the change in market conditions caused by the difference in the raw material and product prices. The economic and dynamic objectives are integrated into a single structure in the formulation of the optimization problem. The presented solution divides the problem into three stages and the final problem is solved using two strategies: goal attainment and quadratic cost. In the first two stages, utopian designs are calculated by the isolated solution of economic and dynamic problems. Finally, an integrated problem is solved to achieve the utopian values calculated in the previous stages, in order to produce simultaneously the plant with the best economic and dynamic performance. The results demonstrate the advantages of the methodology for process design, compared with the traditional sequential methodology.

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Section: ■ Model Predictive Controlmentioning

confidence: 99%

Section: Model Predictive Controlmentioning

confidence: 99%