A supervisory on-line tuned fuzzy logic based sliding mode control for robotics: An application to surgical robots

Abstract

Ever since digital technology entered in the operating theater (OT) surgery has moved out through one of the big transformation on account of medical world and now we are foreseeing the era of digital OT. Robotic assisted surgery (RAS) is a way of technological development in the medical environment that uses robotic structure to assist in surgical measures. RAS was designed to beat the limitations of Minimal Invasive Surgery (MIS) and to improve the ability of medical doctor during surgery. The paper depicts the control methodology for surgical robots based on the combination of fuzzy logic control (FLC) with sliding mode control (SMC). The appreciable features of SMC like simplicity in design and high degree of robustness motivate researchers to employ this methodology in robotics. Nevertheless, the destructive chattering phenomenon is circumvented by espousing FLC in SMC. Additionally, the output gain of fuzzy sliding mode control (FSMC) is online tuned by a supervisory fuzzy logic control (SFLC), which results in chattering diminution. System stability is investigated using Lyapunov theorem. All numerical simulations have been carried out using MATLAB tool for 2 DOF surgical robot manipulator formulated for high speed trajectory tracking and for the typical condition during surgery. Moreover, the performance has been validated in real-time using Opal-RT Lab simulator show the efficacy of the proposed methodology. The simulation as well as real time digital simulator (OP-4500) results of FSMC and supervisory fuzzy logic based sliding mode control (SFSMC) are compared with the conventional SMC which represents the improvement of control law for attainment of optimized results by rejecting perturbations and achieving the desired system performance within a specific band of operation.