Combined Model-Free Adaptive Control with Fuzzy Component by Virtual Reference Feedback Tuning for Tower Crane Systems - Roman, Raul-Cristian; Precup, Radu-Emil; Bojan-Dragos, Claudia-Adina; Szedlak-Stinean, Alexandra-Iulia (Procedia computer science, 2019)
A novel mix of two data-driven algorithms is proposed in this paper. The mix of the algorithms aims to exploit the main advantage of data-driven Virtual Reference Feedback Tuning (VRFT) algorithm, that is represented by the automatic computation of the optimal parameters using a metaheuristic Grey Wolf Optimizer (GWO) for the Compact Form Dynamic Linearization (CFDL) version of the authors’ Model-Free Adaptive Control Takagi-Sugeno Fuzzy Algorithm (CFDL-PDTSFA), so the parameters of the CFDL-PDTSFA are optimally tuned in a model-free manner via VRFT. Three specific optimization problems are defined and solved by Model-Free Adaptive Control, VRFT and GWO algorithms. The new resulted algorithm is validated using experimental results to the arm angular position of the nonlinear tower crane system laboratory equipment.