Like many other mechanical dynamic systems, flexible manipulator systems experience stiction or sticking friction, which may cause input-dependent instabilities. Manipulator performance can be enhanced by including friction forces. But it is hard and expensive to measure friction directly. This work addresses the problem of identifying flexible manipulator joint friction using the technique suggested by Cheok in 1988.
A dynamic model of a two-link flexible manipulator based upon finite element and Lagrange's methods is constructed. The dynamic model includes the effects of joint compliances and actuator dynamics. Friction is also incorporated in the dynamic model in order to account for stick-slip at the joints. Next, the friction parameters in the model are determined. The identification problem is posed as an optimization problem to be solved using nonlinear programming methods. A genetic algorithm is used to improve the convergence rate and to raise the chances of finding the global optimum.
The identified friction parameters are experimentally verified and it is expected that the identification technique is applicable to a system parameter identification problem associated with a wide class of nonlinear systems.
