The problem of distributed coordinated tracking control for networked Euler-Lagrange systems without velocity measurements is investigated. Under the condition that only a portion of the followers have access to the leader, sliding mode estimators are developed to estimate the states of the dynamic leader in finite time. To cope with the absence of velocity measurements,the distributed observers which only use position information are designed. Based on the outputs of the estimators and observers,distributed tracking control laws are proposed such that all the followers with parameter uncertainties can track the dynamic leader under a directed graph containing a spanning tree. It is shown that the distributed observer-controller guarantees asymptotical stability of the closed-loop system. Numerical simulations are worked out to illustrate the effectiveness of the control laws.
Analysis and design techniques for cooperative flocking of nonholonomic multi-robot systems with connectivity maintenance on directed graphs are presented. First, a set of bounded and smoothly distributed control protocols are devised via carefully designing a class of bounded artificial potential fields(APF) which could guarantee the connectivity maintenance, collision avoidance and distance stabilization simultaneously during the system evolution. The connectivity of the underlying network can be preserved,and the desired stable flocking behavior can be achieved provided that the initial communication topology is strongly connected rather than undirected or balanced, which relaxes the constraints for group topology and extends the previous work to more generalized directed graphs. Furthermore, the proposed control algorithm is extended to solve the flocking problem with a virtual leader. In this case, it is shown that all robots can asymptotically move with the desired velocity and orientation even if there is only one informed robot in the team. Finally, nontrivial simulations and experiments are conducted to verify the effectiveness of the proposed algorithm.
