Hybrid adaptive control for series elastic actuator of humanoid robot

Abstract

PurposeGenerally, humanoid robots usually suffer significant impact force when walking or running in a non-predefined environment that could easily damage the actuators due to high stiffness. In recent years, the utilization of passive compliant series elastic actuators (SEA) for driving humanoid's joints has proved the capability in many aspects so far. However, despite being widely applied in the biped robot research field, the stable control problem for a humanoid powered by the SEAs, especially in the walking process, is still a challenge. This paper proposes a model reference adaptive control (MRAC) combined with the back-stepping algorithm to deal with the parameter uncertainties in a humanoid's lower limb driven by the SEA system. This is an extension of our previous research (Lanh et al., 2021).Design/methodology/approachFirstly, a dynamic model of SEA is obtained. Secondly, since there are unknown and uncertain parameters in the SEA model, a Model Reference Adaptive Controller (MRAC) is employed to guarantee the robust performance of the humanoid's lower limb. Finally, an experiment is carried out to evaluate the effectiveness of the proposed controller and the SEA mechanism.FindingsThis paper proposes an effective control algorithm that can be widely applied for the humanoid-SEA system. Besides, the effect of the coefficients in the control law is analyzed to further improve the response's quality.Research limitations/implicationsEven though the simulation shows good results with stable system response, the practical experiment has not been implemented to fully evaluate the quality of the controller.Originality/valueThe MRAC is applied to control the humanoid's lower limb and the back-stepping process is utilized to combine with an external SEA system but still maintain stabilization. The simplified model of the lower-limb system proposed in the paper is proven to be appropriate and can be taken for further research in the future.