Abstract
In this paper, the identification problem of the PUMA 762 robot for grinding applications is considered by using several different recursive identification methods. A detailed procedure of modelling the robot is described. Various experiments have been performed using the PUMA 762/VAL II industrial robot equipped with a 4 Hp pneumatic grinder and a JR 3 force sensor. The PUMA 762 robot has been successfully modelled by a linear third order model with reliable accuracy. The nonlinearities of the robot have been investigated by utilizing different pseudorandom binary sequence (PRBS) signals. Clearly, these linear models, representing the input-output dynamics of the robot, will make it possible to design and develop adaptive controllers for the robotic grinding process.
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