Robust Impedance Control-based Lyapunov-Hamiltonian Approach for Constrained Robots

A new design of a robust impedance controller for constrained robotic manipulators is presented. The main objective is to stabilize asymptotically, in the task space, the robotic manipulator's end effectors into a desired position, via a desired contact force under model uncertainties and measurement noise. In this work, the proposed approach is enough straightforward for application without force and position control separation. Robust asymptotic stability in the approach is proved using a Hamiltonian-Lyapunov approach. Besides this, a state/parameter observer and an acceleration estimator are proposed to handle the problems of force estimation, disturbance rejection and acceleration measurement. To ensure high performance, a Particle Swarm Optimization (PSO) algorithm is used finally as an efficient and fast method for the offline fine-tuning of the controller's parameters. In designing the PSO method, the Mean of Root Squared Error (MRSE) is considered as a cost function in the Cartesian space. Finally, the example of the ABB-IRB 140 industrial robot with 6DOFs is used to validate the performances of the proposed approach.