2 - Preliminary simulation of intelligent force control

Abstract

In this chapter, simulations of an impedance model following force control using generalized learning-based fuzzy environment model (GFEM) are presented for articulated industrial robots with an open-architecture controller. The desired damping, which is one of the impedance parameters, has a substantial effect on force control performance, so that an important point for successfully using the force controller is how to suitably tune the desired damping according to each environment and task. We introduce an approach that produces the desired time-varying damping, giving the critical damping condition in contact with an object. However, the approach requires that the physical parameters of the object, such as viscosity and stiffness, are known beforehand. In order to deal with unknown environments, the proposed GFEM not only estimates the stiffness of unknown environments but also systematically yields the desired time-varying damping for stable force control. The effectiveness and promise of the proposed method are demonstrated through hybrid position/force control simulations using the dynamic model of a PUMA560 manipulator.