Adaptive control of parallel robots with uncertain kinematics and dynamics

One of the most challenging issues in adaptive control of robot manipulators with kinematic uncertainties is the requirement of inverse Jacobian matrix in regressor form. This requirement is inevitable in the case of the control of parallel robots, whose dynamics formulation are derived in the task space. In this paper, an adaptive controller is proposed for parallel robots based on representation of Jacobian matrix in regressor form with asymptotic trajectory tracking. The main idea of this paper is separation of determinant and adjugate of Jacobian matrix in order to represent them into a new regressor forms. Simulation and experimental results on a 2-DOF RPR and a 3-DOF redundant cable driven robot, respectively, verify promising performance of the proposed method in practice. (c) 2021 Elsevier Ltd. All rights reserved. One of the most challenging issues in adaptive control of robot manipulators with kinematic uncertainties is the requirement of inverse Jacobian matrix in regressor form. This requirement is inevitable in the case of the control of parallel robots, whose dynamics formulation are derived in the task space. In this paper, an adaptive controller is proposed for parallel robots based on representation of Jacobian matrix in regressor form with asymptotic trajectory tracking. The main idea of this paper is separation of determinant and adjugate of Jacobian matrix in order to represent them into a new regressor forms. Simulation and experimental results on a 2-DOF RPR and a 3-DOF redundant cable driven robot, respectively, verify promising performance of the proposed method in practice.