Robust Controller Design with Particle Swarm Optimization for Nonlinear Prosthetic Hand System

The recent trend of a prosthetic hand is gradually importance due to its capability to replace amputee’s hand that is lost caused by various factors. However, precision control of prosthetic hand is challenging task especially dealing with its high precision response and functionality. Apart of comprehensive modelling, the controller is another essential part that playing a vital role in the enhancement of the prosthetic hand performance. In this paper, a Sliding Mode Control (SMC) has been designed and integrated with the prosthetic hand, which parameters have been obtained through try and error technique, followed by an optimization technique using Particle Swarm Optimization (PSO) algorithm. The finding shows that the SMC, which is optimized using PSO algorithm outperforms the conventional SMC and proportional-integral-derivative (PID) controllers. Therefore, it can be inferred that appropriate controller with proper tuning technique is essential to achieve high precision performance for a prosthetic hand.