This article presents the development of a new medical robot system comprising a spherical remote center motion (RCM) mechanism with modular design and two mechanical decoupling methods for Minimally Invasive Surgery (MIS). We achieved excellent comprehensive performance indices through a novel multi-objective optimization model comprising four optimization objective functions, three constrained conditions and two optimization variables. In order to enhance the manipulability, remove the coupling between motors, and reduce the control difficulty, two new decoupling mechanism means were proposed to remove coupling motion between the wrist and pincers, coupling motion between the translational joint of mobile platform and four interface disks of surgical instrument as a results of rear drive motor, respectively. The control system architecture is designed to include intuitive motion control, incremental motion control, and proportional motion control. Master-slave attitude registration and surgical instrument replacement strategies improve the master-slave control efficiency. We tested the spherical RCM mechanism performance indices and developed two mechanical decoupling methods and a master-slave control algorithm. Our experimental test results validated that fixing point accuracy, the coupling motions, the positioning and repeated positioning accuracy of the MIS robot, and master-slave control algorithm meet the requirements of MIS. Successful animal experiments confirmed effectiveness of the novel MIS robot system.
In order to solve the problem of the strict condition of traditional saturation function, a new generalized saturation function was proposed and applied in nonlinear PID (Proportion-Integration-Differentiation) control laws, which consisted of linear D + nonlinear PI and linear PD + nonlinear PI. The new generalized saturation function has powerful reaction near the equilibrium point, and has the capability to make the control converge to the equilibrium point swiftly. The global asymptotic stability condition of nonlinear PID control laws were derived by employing Lyapunov's method and LaSalle's invariance principle. In order to improve the accuracy of nonlinear PID control laws, time integration of the absolute value of position tracking error and time integration of the absolute value of torque error were chosen as the objective functions. Global asymptotic stability conditions and rated driving torque of each motor were set as the constraint conditions. Nonlinear PID controller parameters were tuned by employing multi-objective genetic algorithm, non-dominated sorted genetic algorithm-II (NSGA-II). Compared with the optimization results of nonlinear PID with traditional saturation function, the accuracy of position tracking using the proposed method was improved by nearly one order of magnitude. The new generalized saturation functions with minimum time integration of position tracking error were selected to study the robustness of the nonlinear PID controller in modeling uncertainty, input torque disturbance, and noise. The position tracking accuracy of the proposed method compared to those of the traditional PID controller and nonlinear PID controller with traditional saturation function was improved by nearly two orders of magnitude and one order of magnitude, respectively. The introduced saturation function significantly improves position tracking accuracy and robustness of the nonlinear PID controller.
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