A Methodology for Dynamic Parameters Identification of 3-DOF Parallel Robots in Terms of Relevant Parameters

2026-03-16

AI Summary

This work addresses the challenge of accurately identifying parameters with minor contributions to robot dynamics under measurement noise and model inaccuracies, which often limits model fidelity. The authors propose a novel identification approach based on “correlated parameters,” starting from a complete dynamic model and integrating link geometry simplification with branch symmetry. Parameter estimation is performed via weighted least squares, followed by iterative model reduction guided by statistical criteria to ensure physical realizability. By uniquely combining structural symmetry with statistical selection, the method significantly enhances identification accuracy and robustness while maintaining feasibility. Experimental validation on two 3-DOF parallel robots demonstrates excellent agreement between predicted and measured forward and inverse dynamics, confirming the effectiveness and reliability of the proposed approach.

Technology Category

• Intelligent Robots: State Estimation
• Natural Language Processing: Safety and Robustness
• Machine Learning: Learning with Manifolds

Application Category

• Graph Algorithms and Modeling for the Web: Efficient manipulation of static and dynamic Web-related graphs
• User Modeling, Personalization and Recommendation: User modeling and simulation for interactive and conversational systems
• Web Mining and Content Analysis: Robustness and generalizability of Web mining methods

Abstract

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.

Problem

• dynamic parameter identification
• parallel robots
• relevant parameters
• base parameters
• model identifiability

Innovation

• dynamic parameter identification
• parallel robots
• relevant parameters
• weighted least squares
• forward dynamics