Pneumatic artificial muscles (PAMs) are artificial devices that can simulate the mechanics of human muscles, and have shown great promise in industries requiring human-robot interaction systems. Despite their potential, controlling the trajectory performance of PAM-based systems is challenging owing to their nonlinear characteristics. Now, researchers have developed a novel adaptive sliding mode controller that uses fuzzy logic to estimate PAM-based system's parameters, promising enhanced tracking accuracy and adaptability compared to traditional control methods.
