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

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.