Glioblastoma Multiforme (GBM) is a highly aggressive and lethal form of brain tumor, presenting significant challenges in treatment and management. In this study, we propose advanced control models for the management of GBM, focusing on the optimization of drug therapies and adaptive regulation of tumor volume. Leveraging fractional-order mathematical modeling, our approach integrates mathematical modeling techniques with control theory to develop comprehensive strategies for GBM management. The proposed control models aim to optimize drug therapies by dynamically adjusting treatment parameters based on real-time tumor volume monitoring. This adaptive approach allows for personalized treatment regimens tailored to the specific characteristics of the tumor, enhancing therapeutic efficacy while minimizing adverse effects. By harnessing the capabilities of fractional-order modeling, our research provides a novel framework for advancing the management of GBM, offering new insights and strategies for combating this formidable disease
MSC Classification: 92C55, 93C95, 92B05, 35R11, 35A22, 92C50, 35Q53, 49N90.