Finite-time Adaptive Gain Terminal Sliding Mode Control for Uncertain Ball and Beam System Based on Honey Badger-RBF Algorithm

This paper presents a finite-time fast terminal sliding mode control (FTSMC) for an uncertain ball and beam system (BBS) to achieve desired states or corrections within a finite time frame, which is a crucial aspect of the control system performance. An integral-based parameter identification method was first derived to give a nominal model of the BBS before designing the FTSMC. A robustness analysis reveals that this method could robustly achieve identification within a bound. The designed FTSMC was enhanced through the use of the honey badger algorithm (HBA), which was combined with the normal radial basis function neural network (RBF-NN) to create an HBA-RBF network. Experimental results show that the proposed HBA-RBF network-based finite-time adaptive terminal sliding mode controller improved the response rate, as well as reduced the risk of chattering. The HBA-RBF network not only enhances controller performance but also ensures robust and reliable control, making it a promising approach for handling uncertainties in control systems.