scholarly journals Optimization of Bioethanol In Silico Production Process in a Fed-Batch Bioreactor Using Non-Linear Model Predictive Control and Evolutionary Computation Techniques

Energies ◽  
2017 ◽  
Vol 10 (11) ◽  
pp. 1763 ◽  
Author(s):  
Hanniel Freitas ◽  
José Olivo ◽  
Cid Andrade
2019 ◽  
Vol 79 (6-7) ◽  
pp. 2281-2313 ◽  
Author(s):  
S. Rogg ◽  
D. H. Fuertinger ◽  
S. Volkwein ◽  
F. Kappel ◽  
P. Kotanko

Abstract Anemia management with erythropoiesis stimulating agents is a challenging task in hemodialysis patients since their response to treatment varies highly. In general, it is difficult to achieve and maintain the predefined hemoglobin (Hgb) target levels in clinical practice. The aim of this study is to develop a fully personalizable controller scheme to stabilize Hgb levels within a narrow target window while keeping drug doses low to mitigate side effects. First in-silico results of this framework are presented in this paper. Based on a model of erythropoiesis we formulate a non-linear model predictive control (NMPC) algorithm for the individualized optimization of epoetin alfa (EPO) doses. Previous to this work, model parameters were estimated for individual patients using clinical data. The optimal control problem is formulated for a continuous drug administration. This is currently a hypothetical form of drug administration for EPO as it would require a programmable EPO pump similar to insulin pumps used to treat patients with diabetes mellitus. In each step of the NMPC method the open-loop problem is solved with a projected quasi-Newton method. The controller is successfully tested in-silico on several patient parameter sets. An appropriate control is feasible in the tested patients under the assumption that the controlled quantity is measured regularly and that continuous EPO administration is adjusted on a daily, weekly or monthly basis. Further, the controller satisfactorily handles the following challenging problems in simulations: bleedings, missed administrations and dosing errors.


Author(s):  
Zhi Qi ◽  
Qianyue Luo ◽  
Hui Zhang

In this paper, we aim to design the trajectory tracking controller for variable curvature duty-cycled rotation flexible needles with a tube-based model predictive control approach. A non-linear model is adopted according to the kinematic characteristics of the flexible needle and a bicycle method. The modeling error is assumed to be an unknown but bounded disturbance. The non-linear model is transformed to a discrete time form for the benefit of predictive controller design. From the application perspective, the flexible needle system states and control inputs are bounded within a robust invariant set when subject to disturbance. Then, the tube-based model predictive control is designed for the system with bounded state vector and inputs. Finally, the simulation experiments are carried out with tube-based model predictive control and proportional integral derivative controller based on the particle swarm optimisation method. The simulation results show that the tube-based model predictive control method is more robust and it leads to much smaller tracking errors in different scenarios.


2019 ◽  
Vol 123 ◽  
pp. 184-195 ◽  
Author(s):  
S.O. Hauger ◽  
N. Enaasen Flø ◽  
H. Kvamsdal ◽  
F. Gjertsen ◽  
T. Mejdell ◽  
...  

2020 ◽  
Vol 14 (2) ◽  
pp. 343-351 ◽  
Author(s):  
Yutao Chen ◽  
Nicoló Scarabottolo ◽  
Mattia Bruschetta ◽  
Alessandro Beghi

2016 ◽  
Vol 43 (7) ◽  
pp. 541-549 ◽  
Author(s):  
H. Wu ◽  
R. Speets ◽  
G. Ozcan ◽  
R. Ekhart ◽  
R. Heijke ◽  
...  

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