In this paper, the adaptive impedance control proposed by Seul is studied in detail aiming at the disadvantages of traditional impedance control algorithm. In simulation experiment, above two methods are used to control the planar robot. The performance of merits of two algorithms is analyzed detailedly. From the final result of simulation, the adaptive impedance control algorithm has the performance of robustness, that is: it can perform well as though the mathematical model of robot is not accurate and it can work well in the bad working circumstance.
This paper presents an adaptive impedance control scheme for an $n$-link constrained rigid robot manipulator without using the regressor. In addition, inversion of the estimated inertia matrix is also avoided and the new design is free from end-point acceleration measurements. The dynamics of the robot manipulator is assumed that all of the matrices in robot model are unavailable. Since these matrices are time-varying and their variation bounds are not given, traditional adaptive or robust designs do not apply. The function approximation technique is used here to represent uncertainties in some finite linear combinations of the orthogonal basis. The dynamics of the output tracking can thus be proved to be a stable first order filter driven by function approximation errors. Using the Lyapunov stability theory, a set of update laws is derived to give closed loop stability with proper tracking performance. A 2 DOF planar robot with environment constraint is used in the computer simulations to test the efficacy of the proposed scheme.
Biomimetic adaptive impedance control in physical Human Robot Interaction