Novel adaptive balanced control of humanoid robot type NAO robot

This paper presents a novel adaptive tracking controller based on the modified function approximation technique (MFAT). The proposed approach includes a sliding mode with MFAT to approximate the unknown dynamic model of the NAO robot on which it mainly relies. The impact policy and unknown dynamics of the system are considered when implementing the control approach to improve the NAO’s robot locomotion. Unlike conventional FAT, the basis functions in the dynamic parameters approximation updated law are avoided in the proposed MFAT. The Lyapunov function is presented a stability analysis according to which all error signals are uniformly ultimately bounded in a closed loop. Simulations were performed to validate the design MFAT approach for the NAO robot by carrying out a comparative study with a conventional model-based controller.