Neural adaptive robust control of underactuated marine surface vehicles with input saturation |
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Institution: | 1. School of Marine Engineering, Jimei University, Xiamen 361021, PR China;2. Fujian Provincial Key Laboratory of Naval Architecture and Ocean Engineering, Xiamen 361021, PR China;3. School of Mathematics and Statistics Science, Ludong University, Yantai 264025, PR China;1. Navigation College, Dalian Maritime University, Dalian 116026, China;2. Department of Computer and Information Science, Faculty of Science and Technology, University of Macau, Macau 99999, China;3. Department of Computer Science, The University of Alabama, Tusaloosa, AL 35487-0290, USA |
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Abstract: | This paper proposes a saturated tracking controller for underactuated autonomous marine surface vehicles with limited torque. First, a second-order open-loop error dynamic model is developed in the actuated degrees of freedom to simplify the design procedure. Then, a saturated tracking controller is designed by utilizing generalized saturation functions to reduce the risk of actuator saturation. This, in turn, improves the transient performance of the control system. A multi-layer neural network and adaptive robust control techniques are also employed to preserve the controller robustness against unmodeled dynamics and environmental disturbances induced by waves and ocean currents. A Lyapunov stability analysis shows that all signals of the closed-loop system are bounded and tracking errors are semi-globally uniformly ultimately bounded. Finally, simulation results are provided for a hovercraft vehicle to illustrate the effectiveness of the proposed controller as a qualified candidate for real implementations in offshore applications. |
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Keywords: | Actuator saturation Adaptive robust control Generalized saturation function Hovercraft vehicle Neural network Underactuated surface vehicle |
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