Miso Model Free Adaptive Control Of Single Joint Rehabilitation Robot Driven By Pneumatic Artificial Muscles

Pneumatic artificial muscles (PAMs) are widely used as actuators in the field of rehabilitation robots, but their intrinsic compliance properties make it difficult to control precisely. In this paper, an improved multiple input single output model free adaptive control (MISO-IMFAC) method is proposed for the modeling the uncertainty, high nonlinearity and time-variability of the single joint rehabilitation robot driven by antagonistic PAMs, so as to realize the high-precision control of the joint angle. Considering the influence of the error change of adjacent time on the actual control effect, a new control law is formed by adding a term representing error change to the original control input criterion function. The experiment is carried out on a real rehabilitation robot and four types of errors are used to evaluate the effectiveness of the control system. The results show that the control algorithm can improve the accuracy of angle trajectory tracking at different amplitudes. Compared with original algorithm, the experiment errors of MISO-IMFAC were significantly reduced. In addition, the MISO-IMFAC still maintains stable performance in the process of load variation and external disturbance.