Decentralized adaptive control of multiple manipulators in co-operations

A model-based decentralized adaptive controller is proposed for multiple manipulators in a class of co-operations called holonomic co-operations, in which the manipulators are holonomically constrained. In this controller we calculate the control input and estimate unknown robotic parameters in individual state spaces of the manipulators instead of that of the whole system. Consequently, no coordinator exists in the system and the control architecture is decentralized. The model-based adaptive algorithm is used to estimate the unknown or uncertain parameters. It is proven that a Lyapunov function guarantees asymptotic convergence of tracking errors of both the trajectory and interactive force among the manipulators. We also discuss issues regarding communication among the robots according to motion constraints associated with the co-operation. Finally, the validity and performance of the proposed method are verified by simulations on two six-DOF manipulators.