Intelligent Fuzzy Control Comparative Study for Servo Motor Application

The Prosthetic hand plays an important role in rehabilitation as a considered type of advanced medical technology designed to enable individuals who have lost hand due to wars, accidents, or medical conditions. It enables amputees to manage daily activities such as writing, typing, grasping object and doing specific needs, to stay independent. Motors in prosthetic devices are designed to deliver precise control over both positioning and torque, which are crucial for tasks ranging from basic gripping to more intricate movements. In a standard prosthetic hand, servo motors work in tandem with sensors that pick-up muscle signals from the remaining part of the limb or from external controllers. This setup allows users to operate the prosthesis in a natural, intuitive way. Additionally, the feedback systems in these servo motors enable the prosthetic hand to adjust its grip strength automatically, depending on the object being held, which improves both the user’s experience and safety This paper targets a comparative study between different control methodologies to select the best controller for controlling prosthetic hand. The optimal selection should be targeted for smooth moving without overshoot, minimum sharp curve, and minimum delay time The mathematical modelling for prosthetic hands is progressed in the form of a second order transfer function. This paper represent result depend on practical experiment using sensors, servo motor, and Arduino then applied two different control methodologies which are applied to the system are, intelligent Proportional –Integral- Derivative (PID) controller and adaptive fuzzy –PID controller. The adaptive fuzzy- PID controller shows the best results compared to the results of the other controllers.