Switched Two-Level H∞ and Robust Fuzzy Learning Control of an Overhead Crane

Abstract EN

Overhead cranes are typical dynamic systems which can be modeled as a combination of a nominal linear part and a highly nonlinear part.

For such kind of systems, we propose a control scheme that deals with each part separately, yet ensures global Lyapunov stability.

The former part is readily controllable by the H∞ PDC techniques, and the latter part is compensated by fuzzy mixture of affine constants, leaving the remaining unmodeled dynamics or modeling error under robust learning control using the Nelder-Mead simplex algorithm.

Comparison with the adaptive fuzzy control method is given via simulation studies, and the validity of the proposed control scheme is demonstrated by experiments on a prototype crane system.