Consensus for Multiple Random Mechanical Systems With Applications on Robot Manipulator

Abstract

This paper studies the consensus problem of multiple random mechanical/Euler-Lagrange systems. First, an event-triggered adaptive distributed observer is proposed. It can estimate both the system matrix and states of the leader. Compared with the existing works, the leader system contains unknown parameters, which makes the design of the observer challenging. Second, an event-triggered adaptive control method is proposed. The proposed method not only can deal with the random disturbance, but also can save the energy and execution times of the actuators by event-triggered mechanisms. Finally, a practical application on a real multiple-joint robot is conducted. Each joint of the robot is regarded as a mechanical system. We show that by the presented controller, the angular position of each joint can track a reference signal despite uncertainties and random disturbances.