Research on anti-swaying of crane based on T-S type adaptive neural fuzzy control

Abstract

Aiming at the swing problem of container cranes in the process of loading and unloading cargo, an adaptive neural fuzzy (ANFIS) control method based on Takagi-Sugeno (T-S) model is proposed in this paper. Firstly, the mathematical model of crane trolley-hoist system was established based on Lagrange's equation. Secondly, an improved T-S fuzzy neural network is proposed. Since the SNPRP conjugate gradient method has sufficient descent and global convergence under strong search conditions. In this paper, SNPRP conjugate gradient method is used to train the premise parameters and the consequent parameters of T-S model. In order to obtain the best controller, the optimal control matrix of the system is obtained by linear quadratic optimal control using the minimum energy as an indicator, so that the neural network is used to train the ANFIS controller. Finally, the trained ANFIS controller is applied in the crane trolley-hoist system for simulation. The results show that this control method in this paper has better control effect and robustness under different rope lengths and different working conditions.