Intelligent Control of Surgical Robot for Telesurgery: An Application to Smart Healthcare Systems

Abstract

Wireless communication network in robotic telesurgery can be a huge advantage to smart healthcare systems that allows the surgeon to perform surgery on remote patients utilizing a surgical robot. It enables the surgical robotic manipulator to replicate the natural hand motions of the surgeon, allowing it to carry out operations with greater acuity and dexterity. This paper addresses the development of an intelligent controller to assure the safe functioning of a telesurgical robotic manipulator. The intelligent optimized, adaptive, and learning-based adaptive neuro-fuzzy fractional order sliding mode control (ANFFOSMC) controller is proposed to attain dexterity and acuity of the surgical manipulator for surgical interventions. The proposed controller for telesurgical system exhibits superior accuracy and performance compared to conventional controllers, as evidenced by reduced root mean square error (RMSE), integral squared error (ISE), and integral absolute error (IAE). The performance of the robot is evaluated using performance indices in the occurrence of uncertainties and external disturbances.