Open AccessEnhanced Unknown System Dynamics Estimator with Measurement Noise Rejection for Series Elastic Actuators
Author(s) -
Chenghuan Li,
Siyu Chen,
Jing Na,
Yingbo Huang,
Jun Ma
Publication year - 2024
Publication title -
ieee access
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.587
H-Index - 127
ISSN - 2169-3536
DOI - 10.1109/access.2024.3382208
Subject(s) - aerospace , bioengineering , communication, networking and broadcast technologies , components, circuits, devices and systems , computing and processing , engineered materials, dielectrics and plasmas , engineering profession , fields, waves and electromagnetics , general topics for engineers , geoscience , nuclear engineering , photonics and electrooptics , power, energy and industry applications , robotics and control systems , signal processing and analysis , transportation
Implementing the model-based control strategy for Series Elastic Actuators (SEAs) is not an easy task due to its complicated unknown system dynamics in the force models such as modeling uncertainties and measurement noise. In this paper, an enhanced unknown system dynamics estimator (EUSDE) is presented for the SEAs to online estimate the lumped unknown system dynamics in real time with guaranteed convergence and noise rejection response. The proposed approach is an extension of our previously developed unknown system dynamics estimator (USDE). The key idea is to further address the sensitivity of the USDE to measurement noise to further enhance the estimation and control performance. In this line, a high-order filter is further introduced to the design and analysis of USDE. Moreover, this study also provides a comparative analysis of USDE and EUSDE from both the time-domain and frequency-domain perspectives. Finally, comparative simulation and experimental results are provided to demonstrate the effectiveness of the proposed methods.