Position Tracking Control of ASV based on Dynamic Inversion with Intelligent Methods

The aim of this paper is to create an efficient controller that can precisely track the position of autonomous surface vessels by utilizing the dynamic inversion control technique. One of the key objectives of this controller is to mitigate or eliminate the effects of environmental disturbances like wind, waves, and water flow. On the other hand, intelligent methods are used to remove disturbances and fixing modeling errors. These methods include the use of fuzzy methods to adjust the control parameters in the linear controller used in the dynamic inversion controller and the use of perceptron neural network along with the dynamic inversion controller. The effectiveness of the proposed methods is evaluated not only based on the step response but also on their ability to track a complex path. Finally, the proposed methods have been compared with one of the classic methods, namely the PID control. This evaluation provides insights into how the proposed methods fare in terms of both step response and trajectory tracking when compared to the traditional PID control approach.