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Publication Date
Fall 2023
Degree Type
Thesis - Campus Access Only
Degree Name
Master of Science (MS)
Department
Mechanical Engineering
Advisor
Lin Jiang; Mojtaba Sharifi; Winncy Du
Abstract
Teleoperated robotics technologies are expected to expand rapidly, with applications in education, manufacturing, medical science, and space exploration. Robots can be controlled remotely using advanced control methods, allowing real-time interactions within physical environments and sufficient stabilization. The proposed work aims to track the designed path for a teleoperated robotic needling insertion system with adaptive fuzzy neural network modeling and control. The T-S fuzzy neural network model is employed to represent a nonlinear manipulator dynamic system. The proposed adaptive control aims to estimate the parameters of the dynamic system online and adapt to the end effector force and velocity uncertainties. The estimated parameters for the T-S fuzzy model's link, mass, and load will be used to compute the serve torque for each joint. Simulation studies will be used to illustrate the system's stability and tracking performance. The success of this work will facilitate the application of the teleoperated robotic system in a complex operation that requires stabilization and accuracy during the process.
Recommended Citation
Zhao, Yirong, "Adaptive Fuzzy PID Path Planning For a Teleoperated Robotic System" (2023). Master's Theses. 5489.
DOI: https://doi.org/10.31979/etd.9faa-2yys
https://scholarworks.sjsu.edu/etd_theses/5489
