Abstarct: Abstract Various methods have been suggested for the drug dosage delivery of chemotherapy. However, the majority of the control techniques proposed for chemotherapy predominantly rely on model-baxsed approaches. This is while applying these approaches to cancer models, which are highly nonlinear and have many uncertainties, is not ideal. Therefore, in this study, a fractional-order predictive controller has been designed using a model-free approach that is able to better manage nonlinear dynamics and uncertainties, to control the chemotherapy drug dosage for a malignant tumor model consisting of a nonlinear four-state ordinary differential equation. The control system proposed here is comprised of two major controllers including a predictive controller baxsed on General Type-2 Fuzzy Logic (PGT2-FLC) and a compensator. A mathematical model with fractional-order along with an interval Type-2 fuzzy system is used for online estimation of the system’s dynamics. An evolutionary optimization technique named biogeography-baxsed optimization (BBO) algorithm is applied for the optimization of GT2-FLC, the main controller of the closed-loop system, to optimize a performance index when the prediction horizon is fixed. To boost the efficiency of the control system, a compensator is also designed to assure the closed-loop asymptotic stability. A simulation is then conducted in MATLAB/Simulixnk environment to obtain the response of the designed controllers under various conditions and scenarios. The simulation results show the effectiveness of the proposed control algorithm in tumor treatment under different conditions and its applicability to cancer patients.