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PROJECT TITLE :

Robust control strategy for electrically driven robot manipulators: adaptive fuzzy sliding mode

ABSTRACT:

In this study, a sliding mode controller is meant to manage the position tracking of robot manipulator. The proposed control has global asymptotical stability within the presence of structured uncertainties, un-structured uncertainties and un-modelled dynamics of the robot manipulator in addition to in motors dynamics. The proposed management structure is intended in such a approach that initially, by using inverse dynamic method, it reduces the uncertainties certain and eventually, sliding mode management eliminates the influence of the remaining uncertainties in closed-loop system stability. Additional, in control input for eliminating undesirable chattering phenomena using the fuzzy logic, an adaptive fuzzy approximator is intended in such approach that approximates the uncertainty bounds. Mathematical proof shows that the adaptive fuzzy sliding mode control of a closed-loop system has global asymptotical stability. Since the quantity of existing fuzzy rules are low in adaptive fuzzy approximator rules base and in single input-single output form, so management input computational load is terribly low and this order makes the proposed management of sensible implementation doable. To judge the performance of the proposed controller, a case study on a robot manipulator with 2 degrees of freedom is implemented. Simulation results show the required performance of the proposed controller.


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