Neural network‐based tracking control of autonomous marine vehicles with unknown actuator dead‐zone
Min Ma, Tong Wang, Runsheng Guo, Jianbin Qiu
Abstract
Abstract This article studies the neural‐network based backstepping control problem for autonomous marine vehicles perturbed by external disturbances. The actuator dead‐zone phenomenon, which is a common non‐smooth property caused by the complicated operating environment of autonomous marine vehicles, is also considered. To cope with the issue of “complexity explosion” and further decrease the tracking errors, a command filtering compensation strategy is also proposed, which guarantees satisfactory tracking performance and boundedness of the closed‐loop system signals. Finally, simulation studies are given to further demonstrate the effectiveness of the proposed control method.
Topics & Concepts
BacksteppingControl theory (sociology)Dead zoneActuatorCompensation (psychology)Tracking (education)Computer scienceControl engineeringArtificial neural networkProperty (philosophy)Control (management)EngineeringArtificial intelligenceAdaptive controlGeologyEpistemologyPhilosophyPedagogyPsychoanalysisOceanographyPsychologyAdaptive Control of Nonlinear SystemsStability and Control of Uncertain SystemsAdaptive Dynamic Programming Control