Variable Bandwidth Adaptive Course Keeping Control Strategy for Unmanned Surface Vehicle

Dongdong Mu, Guofeng Wang and Yunsheng Fan
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Dongdong Mu: School of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China
Guofeng Wang: School of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China
Yunsheng Fan: School of Marine Electrical Engineering, Dalian Maritime University, Dalian 116026, Liaoning, China

Energies, 2020, vol. 13, issue 19, 1-16

Abstract: This paper proposes a new and original course keeping control strategy for an unmanned surface vehicle in the presence of modeling error, external disturbance and input saturation. The trajectory linearization control method is used as the basic algorithm to design the course keeping strategy, and the radial basis function neural network and disturbance observer are used to compensate modeling error and external disturbance respectively to enhance the robustness of the control system. Moreover, a robust term is used to compensate various compensation errors to further improve the robustness of the system. In addition, hyperbolic tangent function and Nussbaum function are hired to deal with the potential input saturation problem, and the neural shunting model is adopted to avoid the computational explosion caused by the derivation of virtual control law. Taking the above facts into account will help to further realize engineering practice. Finally, the control strategy proposed in this paper is compared with the classical proportional–integral–derivative control strategy. The simulation results show that the course control results of the proposed control strategy are more robust than proportional–integral–derivative control, regardless of whether the external disturbance is weak or strong.

Keywords: unmanned surface vehicle; course keeping; adaptive control; input saturation (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2020
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