R.R. Waiboer

Modelling and Identification of a Six Axes Industrial Robot

This paper deals with the modelling and identification of a six axes industrial St ¨aubli RX90 robot. A non-linear finite element method is used to generate the dynamic equations of motion in a form suitable for both simulation and identification. The latter requires that the equations of motion are linear in the inertia parameters. Joint friction is described by a friction model that describes the friction behaviour in the full velocity range necessary for identification. Experimental parameter identification by means of linear least squares techniques showed to be very suited for identification of the unknown parameters, provided that the problem is properly scaled and that the influence of disturbances is sufficiently analysed and managed. An analysis of the least squares problem by means of a singular value decomposition is preferred as it not only solves the problem of rank deficiency, but it also can correctly deal with measurement noise and unmodelled dynamics.

REALISTIC DYNAMIC SIMULATION OF AN INDUSTRIAL ROBOT WITH JOINT FRICTION

This paper presents a realistic dynamic simulation of the closed-loop tip motion of a rigid-link manipulator with joint friction. The results from two simulation techniques are compared with experimental results. A six-axis industrial Strobot is modelled. The LuGre friction model is used to account both for the sliding and pre-sliding regime. The manipulation task implies transferring a laser spot along a straight line with a trapezoidal velocity profile. Firstly, a non-linear finite element method is used to formulate the dynamic equations of the manipulator mechanism. In a closed-loop simulation the driving torques are generated by the control system. The computed trajectory tracking errors agree well with the experimental results. Unfortunately, the simulation is very time- consuming due to the small time step of the discrete-time controller. Secondly, a perturbation method has been applied. In this method the perturbed motion of the manipulator is modelled as a first-order perturbation of the nominal manipulator motion. Friction torques at the actuator joints are introduced at the stage of perturbed dynamics. A substantial reduction of the computer time is achieved without loss of accuracy.