This research investigates applying the Proportional-Integral-Derivative (PID) fuzzy control system to enhance hand movement performance in humanoid teaching assistant robots specifically for mathematics education. Humanoid robots are increasingly used as interactive partners and educational tools in academic settings, significantly facilitating mathematics learning. Traditional linear control algorithms, including PID, face challenges due to uncertainties such as variations in load and stiffness in robot hands, which can affect the precision needed for teaching mathematical concepts. This study aims to improve the efficiency and accuracy of robot hand movements through a PID-Fuzzy control approach, thereby enhancing the robot’s ability to teach mathematics. The methodology includes designing and developing humanoid teaching assistant robots, implementing the PID-Fuzzy control algorithm, and conducting experimental tests focused on mathematics education scenarios. The results compare the performance of the PID-Fuzzy control system with conventional control methods, showing that the PID-Fuzzy approach significantly enhances hand movement performance, overcoming the limitations of linear control systems. The findings suggest that implementing PID-Fuzzy control can substantially improve the effectiveness of humanoid teaching assistant robots in mathematics education, making them more reliable and capable tools for enhancing students’ learning experiences. These positive outcomes provide a foundation for further advancements in intelligent educational robotics tailored to mathematics instruction.