Modeling and identification for robot motion control

This chapter deals with the problems of robot modelling and identification for high-performance model-based motion control. A derivation of robot kinematic and dynamic models was explained. Modelling of friction effects was also discussed. Use of a writing task to establish correctness of the models was suggested. Guidelines for design of an exciting identification trajectory were given. A Kalman filtering technique for on-line reconstruction of joint motions, speeds, and accelerations was explained. A straightforward but efficient estimation of parameters of the rigid-body dynamic model with friction effects was described. The effectiveness of the procedure was experimentally demonstrated on a direct-drive robot with three revolute joints. For this robot, models of kinematics and rigid-body dynamics were derived in closed-form, and presented in full detail. The correctness of the models was established in simulation. Results of experimental estimation of the dynamic model parameters were presented. The appropriateness of the dynamic model for model-based control purposes was verified. However, it was also indicated that this model is still not sufficient for a perfect match to the real robot dynamics, as these dynamics may contain more effects than covered by the rigid-body model. A procedure to identify the dynamics not covered by the rigid-body model was proposed. With these additional dynamics available, more advanced feedback control designs become possible