Intelligent fractional-order sliding mode optimised control of surgical manipulator for healthcare system

The advancements in Robot-Assisted Surgery (RAS) may be a huge advantage to the healthcare systems in the world of digital OTs (Operating Theatres). RAS is a technical breakthrough that makes use of robotic articulations in order to assist the surgeon in complex surgeries. In occurrence of uncertainties and external disturbances, the control and dynamics of a highly nonlinear 3DOF surgical robot manipulator are addressed in this paper. Conventional controllers can be effective when used to single incisions and linear trajectories, but they are ineffective when applied to time-varying and nonlinear trajectories that include uncertainty. An intelligent GA (genetic algorithm) optimised adaptive fuzzy fractional-order sliding mode controller (AFFOSMC) is designed to cope with disturbances and uncertainties inherent in the system by introducing the fractional-order dynamics. GA provides optimal controller parameters for time-varying and nonlinear trajectories that include uncertainty. Therefore, the three-link surgical robot is being utilised as a case study to show the efficacy of proposed controller. The prototype of model is designed in laboratory, where its performance is validated on real-time using the OP5600 digital simulator to demonstrate the effectiveness of proposed technique. When compared with conventional controllers, the comparative analysis of simulation and experimental results of proposed AFFOSMC shed light on the efficiency and supremacy of proposed controller’s performance based on time response parameters and accuracy. The attained accuracy is less than 2 mm which is imperative for the proper functioning of a surgical manipulator.