Sliding mode control for flexible structural vibration reduction based on hybrid neural network models

In this paper, the hybrid modelling based on neural network is introduced for discrete sliding mode control. This model is used to control the random vibration of the flexible structures with parametric uncertainty. The design objective of the discrete sliding mode surface is determinated by the quadratic optimal cost function and solved from the algebraic Riccati equation based on the nominal system. To reduce the chatter from the large uncertainty of the system, the hybrid model of neural network and nominal system is adopted. The neural network method with multilayer feed-forward neural network is used to model the uncertainty part. In the end, the system controlled by sliding mode control and that by neural network sliding mode control are simulated, respectively. The simulation results show that the neural network sliding mode control is more effective than the sliding mode control for the vibration of flexible structures with large parametric uncertainty and random external disturbances.