A Methodology for Dynamic Parameters Identification of 3-DOF Parallel Robots in Terms of Relevant Parameters
This work addresses the challenge of improving model-based control and simulations for parallel robots, though it appears incremental as it builds on existing identification techniques with specific adaptations for robot geometry.
The paper tackles the problem of dynamic parameter identification for 3-DOF parallel robots by proposing a methodology that identifies a subset of relevant parameters, simplifying the model based on geometry and symmetry, and using Weighted Least Squares with statistical reduction to ensure physical feasibility. The result is experimentally validated on two robot configurations, showing agreement between identified models and experiments for inverse and forward dynamics.
The identification of dynamic parameters in mechanical systems is important for improving model-based control as well as for performing realistic dynamic simulations. Generally, when identification techniques are applied only a subset of so-called base parameters can be identified. More even, some of these parameters cannot be identified properly given that they have a small contribution to the robot dynamics and hence in the presence of noise in measurements and discrepancy in modeling, their quality of being identifiable decreases. For this reason, a strategy for dynamic parameter identification of fully parallel robots in terms of a subset called relevant parameters is put forward. The objective of the proposed methodology is to start from a full dynamic model, then simplification concerning the geometry of each link and, the symmetry due to legs of fully parallel robots, are carried out. After that, the identification is done by Weighted Least Squares. Then, with statistical considerations the model is reduced until the physical feasibility conditions are met. The application of the propose strategy has been experimentally tested on two difierent configurations of actual 3-DOF parallel robots. The response of the inverse and forward dynamics of the identified models agrees with experiments. In order to evaluate the forward dynamics response, an approach for obtaining the forward dynamics in terms of the relevant parameters is also proposed.