Adaptive synchronization control of networked robot systems without velocity measurements

This paper addresses the adaptive synchronization control problem of networked robot systems characterized by the Lagrangian function, where exact dynamic models are unknown and velocity measurements are unavailable. A class of distributed observers, comprised of multiple dynamic variables and static variables, are established based on no a priori restriction on the boundness of the observer states. The observer is compatible for different control schemes with or without structure uncertainties. Using the estimated states given by the observer, adaptive distributed control input is developed, and then, closed-loop dynamic models for filtered vectors are established. It is proven that our proposed control scheme permits global exact state estimation and global asymptotic synchronization while compensating for structure uncertainties. Simulations are provided to demonstrate the effectiveness of the results.