Variable stiffness estimation of a Series Elastic Actuator

Abstract

This paper focuses on estimating the variable stiffness of the Series Elastic Actuator(SEA) through torque and relative position between the motor and the payload measurements. Although position and torque sensors are effective in control schemes, the exorbitant price are not convenient for the application of robotics. Through the mathematical modeling, the variable stiffness of the series elastic actuator sometimes is difficult to obtain accurately. It should be noticed that, an accurate estimation of the variable stiffness is important. In this paper, a Kalman filter based on Taylor expansion is designed to estimate the variable stiffness. Specially, in order to improve the accuracy of the model, the process is divided into two steps for solving the problem of hysteresis, and the recursive least squares algorithm is used to estimate the spring stiffness. Then, according to the accurate spring stiffness value, an estimator of the variable stiffness is presented. The effectiveness of the proposed method on variable stiffness identification is proved through experiments.