Model predictive control of underwater gliders based on a one-layer recurrent neural network

Publication Type:
Conference Proceeding
Citation:
2013 6th International Conference on Advanced Computational Intelligence, ICACI 2013 - Proceedings, 2013, pp. 328 - 333
Issue Date:
2013-01-01
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In this paper, a motion control problem for underwater gilders in longitudinal plane is considered. A recurrent neural network based model predictive control approach is developed. The model predictive control of underwater gliders is formulated as a time-varying constrained quadratic programming problem, which is solved by using a recurrent neural network called the simplified dual network in real-time. Simulation results are further presented to show the effectiveness and performance of the proposed model predictive control approach. © 2013 IEEE.
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