Improved Image Based Visual Servoing with Parallel Robot
The position regulation problem of an eye-in-hand type of parallel robot based pointing systems (PRBPS) is considered in this paper. A fuzzy logic system is first designed to compensate for the uncertainties of the parallel robot and the uncertainty of the image Jacobian, then a hybrid controller (HC) including the image-based nonlinear controller and the adaptive supervisory fuzzy logic controller (ASFLC) is derived by using the Lyapunov direct method to realize the position regulation (PR). The stability of the closed-loop system in the Lyapunov sense is proven theoretically. The fuzzy scaling matrix is combined with the HC to improve the performance of the control system. The simulation results demonstrate that the PRBPS realizes PR with very good robustness to the parameter uncertainties, and the control input torques and settling time are reduce greatly in the case of large initial feature errors.
parallel robot position regulation image jacobian adaptive supervisory fuzzy logic controller fuzzy scaling matrix settling time