The auxiliary controller design based on model-free control in the brain-machine interface

In this paper, a model-free control (MFC) method is used to design an artificial feedback to compensate the lack of natural feedback and achieve the reaching task for a voluntary single joint. Considering the MFC only depends on the I/O data of system, and does not need the system model, it can avoid the complex analysis on the brain model, and reduce the difficulty of controller design. Moreover, through choosing different pseudo-partial-derivative values, the influence of the pseudo-partial- derivative value is analyzed and a series of control results are given; further, the computing efficiency is improved drastically through a comparison in the simulation.