Fuzzy-Logic-Based PID Control of Brain Tumor via Chemotherapy

Effective chemotherapy for brain tumors requires precise control of drug delivery to minimize tumor growth while preserving healthy and immune cells. This study proposes a novel Fuzzy Proportional-Integral-Derivative (Fuzzy PID) control scheme to regulate the dosage rate of drug administration in a nonlinear brain tumor model. The nonlinear model incorporates four states: tumor cells, healthy cells, immune cells, and drug concentration. A Fuzzy Inference System (FIS) is employed to dynamically adjust PID gains in terms of the error signal of the drug amount to achieve optimal tracking of the desired drug concentration while ensuring appropriate bounded steady-state responses for all states. A Genetic-Algorithm-Based optimization (GA) approach is also implemented to derive the optimal control law and compared with the proposed Fuzzy PID technique. Simulation results demonstrate that the Fuzzy PID controller remarkably outperforms the GA-based control, achieving superior tracking performance and faster settling times for the drug concentration state. Additionally, the Fuzzy PID approach results in significantly lower tumor cell populations and higher healthy and immune cell counts in steady-state conditions. A number of simulations conducted for the brain tumor model highlight the potential of the Fuzzy PID control for improving chemotherapy outcomes in brain tumor treatment, offering a robust and adaptive solution for nonlinear systems.

کلیدواژه ها:

Fuzzy PID control ، Brain tumor model ، Genetic-algorithm-based optimization ، Nonlinear systems