Model-based control algorithms for optimal therapy of high-impact public health diseases

2013 IEEE 17th International Conference on Intelligent Engineering Systems (INES)

Sápi

Ferenci

et al. 2013

Self Cite

“…The article briefly presents the newest results obtained as a direct continuation of the results presented at the INES 2011 and 2012 conferences [2], [3].…”

Section: Introductionmentioning

confidence: 75%

“…DEVELOPED ROBUST CONTROL FRAMEWORK Last year at the INES 2012 conference we have summarized the validation results obtained on our robust control framework regarding a large set of 83 type 1 diabetic patients [3].…”

Section: Preliminary Model-free Results Of Thementioning

confidence: 99%

Model-based optimal therapy for high-impact diseases

2013 IEEE 17th International Conference on Intelligent Engineering Systems (INES)

Sápi

Ferenci

et al. 2013

Self Cite

“…The current article summarizes the newest results obtained following the tradition established at previous IEEE INES and SACI conferences [2][3][4][5].…”

Section: Introductionmentioning

confidence: 84%

Physiological modeling and control at Obuda University

2015 IEEE 10th Jubilee International Symposium on Applied Computational Intelligence and Informatics

Ferenci

Sápi

et al. 2015

Self Cite

“…There are several examples concerning optimal tumor growth regulation using chemotherapy [4] or angiogenic inhibition [5]. Solutions in the literature vary from classical linear techniques [6] to sophisticated modern control methods, such as TP-LPV control [7], H ∞ control [8] or feedback linearization [9]. However, a controller can not be designed without a proper mathematical description of the problem.…”

Section: Introductionmentioning

confidence: 99%

Impulsive Control of Tumor Growth via Nonlinear Model Predictive Control Using Direct Multiple Shooting

Czakó

Drexler

2020 European Control Conference (ECC)

2020

Nonlinear Model Predictive Control (NMPC) is utilized to compute optimal administration protocols for chemotherapeutic treatment. By using model-based methods, the side effects of the drug can be mitigated in conjunction with a decrease in treatment expenses. The designed controller was able to provide the protocol in the form of impulses that can model administration by injection, using a smooth approximation of the Dirac delta distribution. For the implementation of the NMPC algorithm, Direct Multiple Shooting (DMS) was chosen so that the computational time of the problem remains reasonable. Numerical effects on the stability of the computation were discussed, with a solution for each issue present. The controller was also tested on virtual patients, with data from mice experiments, which concluded in applicable treatment protocols.