In the era of digital OT (Operating Theatre), the developments in Robot-Assisted Surgery (RAS) can greatly benefit the medical field. RAS is a method of technological advancement that uses surgical robots to assist complicated surgeries. Its implementation improves the ability of the specialised doctors to perform surgery to a great extent. This paper addresses the dynamics and control of the highly non-linear 3DOF surgical robot manipulator in the occurrence of external disturbances and uncertainties. The integration of non-linear robust SMC (Sliding Mode Control) with smoothing mechanism, FOPID (Fractional-Order Proportional Integral Derivative) controller and fuzzy controller provides a high degree of robustness and minimal chatter. The addition of type-2 fuzzy logic to the controller, named intelligent T2F-SFOSMC (Type-2 Fuzzy-Smoothing Fractional Order Sliding Mode Controller), improves the system’s performance by ruling out the disturbances and uncertainties. The prototype model is developed in a laboratory and its outcomes are validated on OP5600: a real-time digital simulator. The simulation results and experimental results of the proposed T2F-SFOSMC are compared with conventional controllers, which illustrates the efficacy and superiority of the proposed controller’s performance during the typical situation of surgery. The proposed T2F-SFOSMC outperforms conventional controllers by providing greater precision, stability and robustness to time-varying nonlinear multi-incision trajectory.
In the era of digital OTs (operating theatres), the developments in robot-assisted surgery (RAS) can greatly benefit the medical field. RAS is a method of technological advancement that uses robotic articulations to assist in complicated surgeries. Its implementation improves the ability of the specialized doctor to perform surgery to a great extent. The paper addresses the dynamics and control of the highly non-linear 3DOF surgical robot manipulator in the event of external disturbances and uncertainties. The integration of non-linear robust SMC (sliding mode control) with a smoothing mechanism, a FOPID (fractional-order proportional integral derivative) controller, and a fuzzy controller provides a high degree of robustness and minimal chatter. The addition of fuzzy logic to the controller, named intelligent fuzzy-SFOSMC (smoothing fractional order sliding mode controller) improves the system’s performance by ruling out the disturbances and uncertainties. The prototype model is developed in a laboratory and its outcomes are validated on OP5600, a real-time digital simulator. Simulation and experimental results of the proposed fuzzy-SFOSMC are compared with conventional controllers, which illustrates the efficacy and superiority of the proposed controller’s performance during the typical surgical situations. The proposed fuzzy-SFOSMC outperforms conventional controllers by providing greater precision and robustness to time-varying nonlinear multi-incision trajectories.
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