Incremental PI-like Fuzzy Logic Control of a Vacuum-Powered Artificial Muscle for Soft Exoskeletons

Newborns with lower limb motor deficiencies do need rehabilitation. Soft exoskeletons based on soft artificial muscles are promising for this purpose. However, the highly non-linear dynamic behavior of their system makes very difficult to obtain an accurate model to be controlled. This paper proposes to use a free-model method called Incremental PI-Like Fuzzy logic controller (PI-Like FLC). This variation facilitates the design and interpretation of the fuzzy rules; furthermore, we were capable of using optimization algorithms and fuzzy-C-means to obtain the fuzzy sets and membership functions based on data obtained from a previously tuned PID controller. The PI-Like FLC was physically implemented on infant dummies of 0 and 6 months of age to control the knee flexion-extension motion, and a PID was used as a comparison. The results demonstrate a successful tracking control and exhibit robustness against parametric uncertainties and disturbances for both dummies' motion without the need of tuning the controller.