Event-triggered adaptive command filtered asymptotic tracking control for a class of flexible robotic manipulators

Abstract

This work proposes an event-triggered adaptive asymptotic tracking control scheme for flexible robotic manipulators. Firstly, by employing the command filtered backstepping technology, the “explosion of complexity” problem is overcame. Then, the event-triggered strategy is utilized which makes that the control input is updated aperiodically when the event-trigger occurs. The utilized event-triggered mechanism reduces the transmission frequency of computer and saves computer resources. Moreover, it can be proved that all the variables in the closed-loop system are bounded and the tracking error converges asymptotically to zero. Finally, the simulation studies are included to show the effectiveness of the proposed control scheme.