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Ma, Ling; Lou, Xuyang; Jia, Jiajia
Neurocomputing (Amsterdam), 01/2023, Letnik: 518Journal Article
This paper presents a neural-network-based boundary control method for a gantry system with unknown friction and output constraint. Firstly, to tackle the unknown friction, a radial basis function neural network (RBFNN) is adopted to approximate it. Secondly, we employ a barrier Lyapunov function to handle the output constraint problem. Then, a neural-network-based boundary controller is proposed to deal with the aforementioned problems. Subsequently, based on the Lyapunov stability approach, the uniformly ultimately bounded stability of the state of the closed-loop system is guaranteed. Finally, the effectiveness of the developed control method is illustrated through both numerical simulations and physical experiments.
