Group consensus control for multiple robotic manipulators in task space under directed acyclic graph topology

This paper investigates the adaptive group consensus of multiple robotic manipulator systems in task space under directed acyclic graph topology. Two adaptive control strategies are proposed based on parameters linearity method and neural network method, respectively. The criteria for solving group consensus problems are established by using Lyapunov approach. It is shown that, under some reasonable assumptions, the group consensus of multiple robotic manipulator systems can always be achieved by the structure of acyclic interaction topology in task space. Finally, numerical simulations are given to demonstrate the effectiveness of the proposed control methodologies.