Mechanical Engineering for Society and Industry

Soft robotic technologies using pneumatic networks have emerged as potential solutions for assistive applications due to their inherent flexibility and adaptability with humans. However, the nonlinear behavior and delayed response of pneumatic bending actuators as exoskeleton gloves pose significant challenges in achieving precise and stable control. This research aims to develop and evaluate a portable soft pneumatic exoskeleton glove integrated with a fuzzy logic control to regulate the internal air pressure for smooth and adaptive finger flexion motion. The glove was fabricated using silicone rubber pneumatic actuators attached to a flexible base glove, while a mini compressor, solenoid valve, pressure sensor, and Arduino Mega microcontroller were employed to realize the control system. A fuzzy inference system was designed with pressure error as the input and PWM as the output to drive the mini compressor’s operation. Various output membership function configurations, including trapezoidal and S-shaped types, were implemented and tested in real-time operation. Experimental results demonstrated that the fuzzy logic controller effectively maintained stable pneumatic pressure with minimal overshoot, exhibiting time constants between 1.61 s and 1.66 s, rise times of 2.30–2.50 s, and negligible steady-state error. The developed glove also successfully performed adaptive grasping of objects with different shapes and sizes. These results demonstrate that fuzzy logic control provides an effective, stable, and low-cost solution for pressure regulation in soft pneumatic exoskeleton gloves, supporting their potential for wearable hand assistance and rehabilitation applications.