Stable Adaptive Compensation with Fuzzy Cerebellar Model Articulation Controller for Overhead Cranes

This chapter proposes a novel control strategy for overhead cranes. The controller includes both position regulation and anti-swing control. Since the crane model is not exactly known, fuzzy cerebellar model articulation controller (CMAC) is used to compensate friction, and gravity, as well as the coupling between position and anti-swing control. Using a Lyapunov method and an input-to-state stability technique, the controller is proven to be robustly stable with bounded uncertainties. Real-time experiments are presented comparing this new stable control strategy with regular crane controllers.