A neural-network-based robust control strategy applying to omnidirectional lower limbs rehabilitation robot during centre-of-gravity shift

Motion control of mobile rehabilitation robot during centre-of-gravity shift is an intrinsic problem with mechanism. This paper deals with the tracking control of an omnidirectional lower limbs rehabilitation robot during centre-of-gravity shift. The main research contents of this paper consist of two parts: 1) The dynamic model that considered centre-of-gravity position is integrated within the control framework. 2) A robust control strategy based on neural network structure is developed and used to achieve the desired trajectories. Simulation tests are performed and demonstrate the feasibility and efficacy of the proposed method.