  It is widely recognized that the existing parameter estimators and adaptive
controllers for robot manipulators are extremely complicated to be of practical
use. This is mainly due to the fact that the existing parameterization includes
the complicated signal and parameter relations introduced by the Coriolis and
centrifugal forces matrix. In an insightful remark of their seminal paper
Slotine and Li suggested to use the parameterization of the power balance
equation, which avoids these terms -- yielding significantly simpler designs.
To the best of our knowledge, such an approach was never actually pursued in
on-line implementations, because the excitation requirements for the consistent
estimation of the parameters is ``very high". In this paper we use a recent
technique of generation of ``exciting" regressors developed by the authors to
overcome this fundamental problem. The result is applied to general
Euler-Lagrange systems and the fundamental advantages of the new
parameterization are illustrated with comprehensive simulations of a 2
degrees-of-freedom robot manipulator.
