Optimum design of type-2 fuzzy controller using chaos game optimization algorithms, marine predators and slime mold for chemotherapy drug injection rate in cancer treatment

In this paper, a modern dynamic model for cancer is utilized, featuring five differential equations. These equations account for healthy cells, vascular wall cells, cancer cells, the remaining anti-angiogenic agents in the body, and the drug injection rate. The remaining anti-angiogenic agents and the drug injection rate are considered as the control signals. The study then designs an optimal Type-2 fuzzy controller using the Slime Mould Algorithm (SMA), Chaos Game Optimization (CGO), and Marine Predators Algorithm (MPA). Importantly, constrained optimization methods are employed to prevent the controller from injecting excessive medication after a certain period. Simulation results demonstrate the excellent capability of the CGO-optimized controller in reducing the number of cancer tumors while increasing the number of normal and endothelial cells. Furthermore, experimental data confirm these results, indicating compliance with the system’s permissible constraints and validating the fuzzy controller’s response.