Control of Overhead Crane System Using Adaptive Model-Free and Adaptive Fuzzy Sliding Mode Controllers

In this study, a model-free adaptive controller (MFAC) using feedback linearization and an adaptive fuzzy sliding mode controller (AFSMC) using fuzzy approximation are employed to control an underactuated overhead crane system. Both controllers use trolley position and load swing angle information for controlling process. Innovation of the proposed MFAC is based on utilizing the appropriate control signal value of last level for determining the control signal value of new level which depends on position error in these levels. In AFSMC, sliding mode scheme is exploited adaptive Sugeno fuzzy algorithm to update estimation of unknown function and counteract the effect of unknown nonlinear terms of overhead crane's dynamic model. External disturbances such as the wind and the hit are also considered to verify the efficiency of the proposed model-free methods.