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To overcome the shortcomings of traditional dynamic parameter identification methods in accuracy and efficiency, this paper aims to propose a dynamic parameter identification method based on improved iterative reweighted least squares (IIRLS) algorithm.

First, Newton–Euler method is used to establish the dynamic model of the robot, which is linearized and reorganized. Then, taking the improved Fourier series as the excitation trajectory, the optimization model with objective function is established and optimized. Then, the manipulator runs the optimized trajectory and collects the running state of the joint. Finally, the iterative process of iterative reweighted least squares (IRLS) algorithm is improved by combining clustering algorithm and matrix inversion operation rules, and the dynamic model of robot is identified by using the processed collected data.

Experimental results show that, compared with the IRLS algorithm, the root mean square of the proposed IIRLS algorithm is reduced by 4.18% and the identification time is reduced by 94.92% when the sampling point is 1001. This shows that IIRLS algorithm can identify the dynamic model more accurately and efficiently.

It effectively solves the problem of low accuracy and efficiency of parameter identification in robot dynamic model and can be used as an effective method for parameter estimation of robot dynamic model, which is of great significance to the research of control method based on robot model.

The purpose of this study is to address the gaps in existing research on the nonlinear characteristics of floating ring bearings, particularly by focusing on second-order nonlinear stiffness and damping coefficients. Traditional analytical models have limitations in terms of accuracy and computational efficiency. This research aims to develop a more efficient and accurate method for analyzing these nonlinear characteristics, which are crucial for optimizing the design and performance of turbocharger floating ring bearings. The study also seeks to explore how variations in clearance ratio and load influence these coefficients.

This study develops a novel approach for analyzing the nonlinear characteristics of floating ring bearings by utilizing second-order nonlinear stiffness and damping coefficients. The proposed method replaces traditional analytical solution models with a nonlinear stiffness and damping coefficient model, enhancing both computational efficiency and accuracy. The model is validated through extensive simulations that account for varying clearance ratios and load conditions. The results are compared with those obtained from conventional methods, demonstrating the effectiveness of the proposed approach in accurately capturing the nonlinear behavior of turbocharger floating ring bearings.

The study finds that the proposed nonlinear stiffness and damping coefficient model significantly enhances computational efficiency while accurately representing the nonlinear characteristics of floating ring bearings. The model not only reduces computation time but also provides a more precise analysis compared to traditional methods. Moreover, the research reveals that the clearance ratio and load conditions of the floating ring bearings have a substantial impact on the nonlinear stiffness and damping coefficients. These findings suggest that the proposed model and method could be highly beneficial for advancing the design and research of floating ring bearings in turbochargers.

With this statement, the authors hereby certify that the manuscript “Investigation on the nonlinear behaviors of floating ring bearings based on nonlinear stiffness and damping coefficient models” submitted to the journal Industrial Lubrication and Tribology is the results of their own effort and ability. They hereby confirm that this manuscript is their original work and has not been published nor has it been submitted simultaneously elsewhere. They further confirm that they have checked the manuscript and have agreed to the submission.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-09-2024-0324/