Human hands are a great challenge and fascinate many roboticists since they present tremendous skill and versatility .In this research, kinematic and dynamic equations of a 4-DOF 3-link robotic finger are derived using Lagrangian formulations. The main idea for modeling the muscles is placing several springs and dampers between the linkages. By using this idea, dynamic equations of a 4-DOF robotic finger will be derived. By taking advantage of these dynamic models for robotic finger and robotic hand, applying some advanced controllers, which can control the system in presence of parametric uncertainty, will be possible. In order to track the desired trajectory of tapping, tow advanced controllers consisting of adaptive-robust and adaptive-neural are applied to the robotic finger considering a 10% parametric uncertainty in the parameters of the system. By comparing the simulation results of tracking errors and input torques, it is revealed that the adaptive-neural controller has a better performance.
Katibeh, F., Eghtesad, M., & Bazargan-Lari, Y. (2016). Dynamic modeling and control of a 4 DOF robotic finger using robust adaptive and neural adaptive controllers. International Journal of Robotics, Theory and Applications, 4(4), 54-64.
MLA
Fatemeh Katibeh; Mohammad Eghtesad; Yousef Bazargan-Lari. "Dynamic modeling and control of a 4 DOF robotic finger using robust adaptive and neural adaptive controllers". International Journal of Robotics, Theory and Applications, 4, 4, 2016, 54-64.
HARVARD
Katibeh, F., Eghtesad, M., Bazargan-Lari, Y. (2016). 'Dynamic modeling and control of a 4 DOF robotic finger using robust adaptive and neural adaptive controllers', International Journal of Robotics, Theory and Applications, 4(4), pp. 54-64.
VANCOUVER
Katibeh, F., Eghtesad, M., Bazargan-Lari, Y. Dynamic modeling and control of a 4 DOF robotic finger using robust adaptive and neural adaptive controllers. International Journal of Robotics, Theory and Applications, 2016; 4(4): 54-64.
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