Optimized Nonlinear Control Approaches for Effective Bone Cancer Treatment

This research addresses novel approaches for efficient disease management by using sophisticated control techniques to solve the difficult problem of synchronizing symmetric bones in the human body for the treatment of bone cancer. Sliding mode control and supertwisting sliding mode control are the main controllers under investigation. These controllers were selected because to their ability to withstand uncertainties and disruptions that are present in the dynamic behavior of bone cancer. Gain tuning, a critical aspect of controller design, is optimized using a genetic algorithm, ensuring optimal performance and stability. A comprehensive comparison between SMC and STSMC highlights the superiority of STSMC due to its chattering-free nature, robustness against disturbances, and finite-time stability. Furthermore, the practical applicability of the proposed controllers is validated through real-time implementation using the C2000 Delfino and MCU F28379D Launchpad.