Model-Free Adaptive Control for Three-Dimensional Crane Systems

This paper proposes the development of and validation of a Model-Free Adaptive Control (MFAC) algorithm for a three-dimensional crane system in a multi input-multi output setting. The three-dimensional cranes are complex systems with various nonlinearities providing a robust environment for testing the adaptability and efficiency of the MFAC algorithms. The paper aims to compare two distinct versions of the algorithm, i.e., the compact form dynamic linearization (CFDL) and the partial form dynamic linearization (PFDL). Both versions are analyzed in terms of their performance in controlling the three-dimensional crane’s movement by controlling the x, y, and z-axes under varying conditions. Experimental validation highlights the strengths and limitations of CFDL and PFDL versions, offering insights into their practical applications and theoretical underpinnings.