A gain-scheduling control strategy and short-term path optimization with genetic algorithm for autonomous navigation of a sailboat robot

A gain-scheduling control strategy and short-term path optimization with genetic algorithm for autonomous navigation of a sailboat robot

Blog Article

The development of a navigation system for autonomous robotic sailing is a particularly challenging task since the sailboat robot uses unpredictable wind forces for its propulsion besides working in a highly nonlinear and harsh environment, the water.Toward solving the problems that appear in this kind of environment, we propose a navigation system which allows the sailboat to reach any desired target points in its working environment.This navigation system consists of a low-level heading controller and a short-term path planner for situations against the wind.For the low-level heading controller, a gain-scheduling proportional-integral (GS-PI) rab 4ft led fixture controller is shown to better describe the nonlinearities inherent to the sailboat movement.

The gain-scheduling-PI consists of a table that contains the best control parameters that are learned/defined for a particular maneuver and perform the scheduling according to each situation.The idea is to design specialized controllers which meet the specific control objectives of each application.For achieving short-term path-planned targets, a new approach for optimization of the tacking maneuvering to reach targets against the wind is also proposed.This method takes into account two tacking parameters: the side distance available for the maneuvering and the desired sailboat heading when tacking.

An optimization method based on genetic algorithm is used in order to find satisfactory igora vibrance 4-99 upwind paths.Results of various experiments verify the validity and robustness of the developed methods and navigation system.