Enhanced Unknown System Dynamics Estimator With Measurement Noise Rejection for Series Elastic Actuators

Abstract

Implementing the model-based control strategies for Series Elastic Actuators (SEAs) is not an easy task due to the unknown system dynamics in their force models such as modeling uncertainties and external disturbances. 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 performance. In this line, a high-order filter is 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.

Keywords

• Series elastic actuator
• unknown system dynamics estimator
• measurement noise rejection
• frequency-domain analysis