Self-Adjusting Fuzzy Logic Based Control of Robot Manipulators in Task Space
| Autor: | Aydogan Savran, B. Melih Yilmaz, Musa Alci, Enver Tatlicioglu |
|---|---|
| Rok vydání: | 2022 |
| Předmět: |
Lyapunov function
Kinematics Computer science Fuzzy approximation Adaptive fuzzy logic Aerospace electronics Fuzzy logic law.invention Computer Science::Robotics Tracking error symbols.namesake Robot manipulators Control theory law Torque Jacobian matrices Manipulator dynamics Electrical and Electronic Engineering Lyapunov methods Uncertainty Open-loop controller Robot end effector Control and Systems Engineering Task analysis Jacobian matrix and determinant symbols Nonlinear Tracking Control Robot Adaptive fuzzy logic (AFL) Task space control Universal fuzzy controller Redundant Manipulators Robots |
| Zdroj: | IEEE Transactions on Industrial Electronics. 69:1620-1629 |
| ISSN: | 1557-9948 0278-0046 |
| Popis: | End effector tracking control of robot manipulators subject to dynamical uncertainties is the main objective of this work. Direct task space control that aims minimizing the end effector tracking error directly is preferred. In the open loop error system, the vector that depends on uncertain dynamical terms is modeled via a fuzzy logic network and a self-adjusting adaptive fuzzy logic component is designed as part of the nonlinear proportional derivative based control input torque. The stability of the closed loop system is investigated via Lyapunov based arguments and practical tracking is proven. The viability of the proposed control strategy is shown with experimental results. Extensions to uncertain Jacobian case and kinematically redundant robots are also presented. IEEE |
| Databáze: | OpenAIRE |
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