Sampled-data event-triggered resilient consensus control of multiple flexible manipulators with actuator failures via iterative learning scheme

Abstract

In this article, a sampled-data event-triggered resilient consensus tracking control scheme is proposed for multiple flexible manipulators with actuator failures. First, for each flexible manipulator, the finite-time observer is designed to achieve state estimation of the virtual leader. Then, the periodic disturbances are effectively estimated by an iterative learning method. Furthermore, a resilient consensus control scheme is developed by integrating a sampled-data event-triggered mechanism, and it have been proved from the obtained stability results that the proposed control scheme can achieve consensus control and vibration suppression of multiple flexible manipulators while reducing communication consumptions. Finally, the effectiveness of the proposed control method is demonstrated through simulation results.

Keywords: Event-triggered mechanism; Iterative learning control; Multiple flexible manipulators; Resilient consensus tracking control; Vibration suppression.