Abstract
In this paper, the concept of networked control system (NCS) is introduced into the course autopilot of the ship. A network-based neural adaptive sliding mode controller is designed for the ship steering in waves. The unknown term, including the wave disturbances and the unmodeled dynamics, is approximated by the RBF neural network. The sliding mode controller is designed to compensate the neural network approximation error besides of the network-induced delay. The stability of the closed-loop system is proven and the neural network weight is updated using the Lyapunov theory. It indicates that the designed controller can guarantee the system state tracks the desired state asymptotically. Finally, a simulation on a Mariner class vessel in waves is carried out to demonstrate the effectiveness of the proposed control scheme.
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Xia, G., Wu, H. (2013). Network-Based Neural Adaptive Sliding Mode Controller for the Ship Steering Problem. In: Tan, Y., Shi, Y., Mo, H. (eds) Advances in Swarm Intelligence. ICSI 2013. Lecture Notes in Computer Science, vol 7928. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38703-6_58
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DOI: https://doi.org/10.1007/978-3-642-38703-6_58
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