Experimental Parallel Robot Dynamic Model Evaluation with Set Membership Estimation
Abstract
This paper presents the application of an ellipsoidal method for experimental robust dynamic identification of parallel robots. The robot is modelled with classical Lagrange equation which leads to an inverse dynamic model linear with respect to the parameters. Assuming the error additive on input (motor torque), the problem is expressed in a bounded error context. The ellipsoidal method is applied in a factorized form in order to guarantee numerical stability. Two friction models are evaluated via set membership identification from experimental data. Results are exhibited for a fully parallel robot with 4 degrees of freedom.