Decentralized adaptive and nonadaptive position force controllers for redundant manipulators in cooperations

This paper addresses the problem of controlling positions and forces of multiple redundant manipulators cooperatively handling an object in a decentralized manner while optimizing a performance index. The authors propose one adaptive and two nonadaptive decentralized controllers. The adaptive controller is able to cope with unknown or uncertain physical parameters of the system. The Lyapunov approach proves that this controller nor only yields asymptotic convergence of the position and force errors bur also optimizes the specified performance index. To improve the transition performance, besides the nonadaptive version of the controller an implicit decentralized force controller with exponential stability is developed. The controllers realize the force and position controls simultaneously by using coupled force and position signals. The coupled signals distinguish these methods from traditional hybrid controllers in which decoupling of the signals is a must. The decentralized architectures of all the controllers must be emphasized. In detail, the joint input for each robot is designed in its own state space; thus, no coordinator exists, and the computation cost is less expensive than that of centralized controllers designed in the stare space of the whole system.