Abstract
Robust neural-network controller of propeller thrust is proposed for autonomous underwater vehicles (AUVs). The cascaded plant consists of the dynamics of surge motion of an AUV, that of the propeller axial flow, that of the propeller shaft and that of the electrically-driven circuit. Uncertainties including modeling errors and external disturbances are taken into account simultaneously. A hybrid control strategy is proposed to the cascaded system with uncertainties. An on-line robust neural-network is used to compensate the modeling errors while L2-gain design is used to suppress the external disturbances. By backstepping method, the terminated control input to the thrust system is obtained. Design of the controller with L2-gain performance observes the recursive Lyapunov function method, which guarantee the uniformly ultimately bounded stability of tracking system. Simulation results demonstrate the validity of controller proposed.
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Luo, Wl., Zou, Zj. (2011). Robust Cascaded Control of Propeller Thrust for AUVs. In: Liu, D., Zhang, H., Polycarpou, M., Alippi, C., He, H. (eds) Advances in Neural Networks – ISNN 2011. ISNN 2011. Lecture Notes in Computer Science, vol 6676. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-21090-7_66
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DOI: https://doi.org/10.1007/978-3-642-21090-7_66
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