Improvement of robotic hand control with the help of PI fuzzy adaptive controller using classification of EMG signals

Neda Mahdavi¹

1) Master s degree in medical engineering, bioelectrical specialization, Islamic Azad University, Aliabad Katul branch

Publication : The first international conference on new approaches in engineering and basic sciences(icnabs.ir/1st)
Abstract :
This paper investigates the use of a fuzzy PID adaptive controller based on EMG signal classification to improve robotic hand control. This technique combines the advantages of PID control, fuzzy logic and EMG signal analysis, resulting in increased accuracy and performance of robotic hand movements. The adaptive fuzzy PID controller has the ability to adapt to changing conditions and environmental uncertainty, and by continuously adjusting the control parameters, it can adapt to different users and accommodate individual changes in muscle activity patterns. The experimental results show the effectiveness of the proposed approach in improving the accuracy and responsiveness of the robotic hand. This system is able to accurately classify different hand movement patterns and enables accurate and natural control of the robotic hand. Potential applications of this research include helping people with upper limb disabilities, rehabilitation robotics, prosthetics, and industrial automation. The results of this research pave the way for wider uses of this innovative control technique.
Keywords : improvement of hand control robotics fuzzy adaptive controller pi classification of emg signals