Optimal fuzzy P + Dµ controller for cancer chemotherapy

Abstract

This paper aims to develop a robust, effective, and optimal controller for an automatic intravenous drug delivery system for the chemotherapy treatment of cancer patients. For this purpose, a novel hybrid control method, namely the Fuzzy P + Dµ controller, is designed by combining fractional calculus and fuzzy logic controller (FLC). Particle swarm optimization (PSO) algorithm is employed to tune the controller parameters optimally. To evaluate the performance of the proposed controller, a cancer patient model that considers cumulative drug toxicity, one of the most common side effects of chemotherapy, is utilized. Limits on toxicity and drug concentration for patient safety are incorporated into the controller design and optimization process. The graphical and numerical simulation results show that almost no cancerous cells are left at the end of the treatment period. The effectiveness of the controller is proven by the performance index (PI) obtained. Our optimal hybrid Fuzzy P + Dµ outclasses other control techniques in previous related studies with the best PI of 44.426 and the minimum final number of cancerous cells (FNCCs) of 5.084E-08. Moreover, in robustness tests perturbing intra-patient parameters and using different treatment protocols, the cumulative drug toxicity level is kept within safe limits, and almost no cancerous cells remain.