State observer-based model reference adaptive balance control for one-leg stance

PurposeHumanoid robots have been utilized in many fields such as medical, construction, and disaster response. While humanoid robots nowadays can achieve great capabilities, the one-leg balancing task still poses a challenging problem. This paper aims to propose a novel approach to solve the problem.Design/methodology/approachTo aid the balance of one leg in humanoid robot, an external balance mechanism is inserted to the back of the humanoid robot. First, a dynamic model of the humanoid robot with balance mechanism and its simplified model are introduced. Second, a backstepping-based control method is utilized to build the proposed controller for one-leg stance system through two steps. For the first step, a minimum observer-based controller with a virtual control input is used to control the first sub-system reaching the desired reference input. For the second step, a virtual control input is considered as a reference input of a second sub-system, then a model reference adaptive controller (MRAC) is employed to control the second sub-system reaching the virtual control input in presence of uncertainties. By using the external balance mechanism, the sideway balancing task is separated from normal walking function. Furthermore, the utilization of the balance mechanism ensures the humanoid robot's hip adduction does not exceed the threshold of a human when walking. Finally, a simulation study is carried out to evaluate the effectiveness of the proposed method.FindingsThis paper proposes a model reference adaptive control using state observer for balancing one leg of humanoid robot in stance phase that extends our previous research (Tran et al., 2021).Originality/valueThe main research contents have been introduced.