Nonlinear Tracking Control for Reducing Cancerous Tumor Volume Using Three Different Cell Kill Models

In this research, an input-state feedback linearization method is developed for manipulation of the drug usage and accordingly the cancerous tumor volume in chemotherapy. Three nonlinear mathematical cell-kill models including log-kill hypothesis, Norton-Simon hypothesis and Emax hypothesis are considered for the process. By Using a nonlinear control algorithm and with implementing each of the three mentioned nonlinear cell kill models, the tumor volume is minimized through two prescribed time intervals of chemotherapy (30 days and 15 days) prescribed by the potential cancer physician with a reasonable and constant usage of drugs to minimize side effects and costs of the process.