Trajectory control of a laparoscopic 3-PUU parallel manipulator based on neural network in SIMSCAPE SIMULINK environment

Robotics in laparoscopic surgery - A review

“…Moreover, modeling and control of a laparoscopic parallel manipulator with three limbs having identical prismatic-universal-universal (3-PUU) architecture are discussed in a recent study [193,194]. The manipulator has 3 DOFs corresponding to rotation about x-axis (E x ), y-axis (E y ), and translation along the z-axis (P z ).…”

“…The manipulator has 3 DOFs corresponding to rotation about x-axis (E x ), y-axis (E y ), and translation along the z-axis (P z ). To avoid the computational complexity of solving the manipulator's kinematics in real-time application, two feed-forward artificial neural networks (ANNs) are used as forward and inverse kinematics estimators [194,195]. The dynamic model of the 3-PUU manipulator is built using MATLAB Simscape environment, and several control schemes are investigated.…”

“…Simulation results were compared to the PID and adaptive fuzzy logic control schemes implemented in a previous study by Khalifa et al [168]. Figure 16 depicts the comparison and shows that the PID plus feed-forward control scheme provides the best motor performance between the other control schemes [193,194]. Compared to the adaptive fuzzy logic controller [168], the PID plus feed-forward control provided better motor performance with 78.26% less maximum tracking error, in addition to being easier to implement online than the adaptive fuzzy logic controller.…”

“…Figure 17 shows the complete schematic control block diagram of the 3-PUU manipulator with closed-loop trajectory control. In this control system [193,194], the position and orientation error is fed-back to the inverse kinematics ANN which acts as a controller. The ANN's output represents the error in the prismatic displacements d 1 , d 2 , and d 3 resulting from any change in the manipulator's actual model.…”

“…The closed-loop control scheme can enhance the system's performance, eliminating the error resulting from any change in the manipulator's actual model due to manufacturing or assembly defects. Simulation results of a defected manipulator model show that the closed-loop control scheme improves the manipulator's trajectory tracking capability compared to motor control, reducing the z-axis position error by 89.23% and the orientation error by 86.76% and 82.83% about x-axis and y-axis directions, respectively [193,194].…”