Intelligent Optimal Feed-Back Torque Control of a 6DOF Surgical Rotary Robot

فاقد چكيده فارسي

Surgical robotic revolution has assisted surgeons to perform sophisticated surgeries, and increased accuracy, reduced risk, operative and recovery time. Parallel mechanisms are widely used for designing of surgical robots due to their advantage of low inertia and high precision. Specific surgical procedures confine, and restrict their workspace, while controlling and validating the robots are complicated regarding to their complex dynamic. To this end, in this paper, a 6-DOF robot, with rotary manipulators, is designed and controlled. Addressing nonlinearity of parallel robots, a novel approach is designed to robustly penalize the error of tracking at end effector employing a Linear Quadratic Integral (LQI) regulator with online Artificial Neural Network (ANN) gain tuning, based on non-linear model in format of a Linear Time Invariant (LTI) model. As validation, the controller is implemented using MATLAB on the non-linear model designed in Adams software online. Simulation results demonstrates the optimal controller penalizing the error while minimizing torque on each rotary manipulator. In addition, the method defines the workspace of both the states and torques, which is an introduction to comprehensive design of such robots.