Singularity Avoidance Fixed-Time Adaptive Neural Control for Autonomous Underwater Vehicles Considering Unmodelled Dynamics and Disturbances
Yuqing Liu, Jiapeng Liu, Jinpeng Yu
Abstract
This brief concerns the fixed-time backstepping trajectory tracking control problem for uncertain AUVs subject to unknown input saturation. By making use of the command filter technique, the adaptive control method and neural networks, a low-complexity nonlinear controller that contains only three dynamic update laws is proposed. And the new fixed-time stabilizing function is proposed to avoid the singularity problem. System performance analysis shows that the fixed-time stability is guaranteed for the AUV closed-loop system without violating the input saturation. The simulation result is given to demonstrate the effectiveness of our developed strategy.
Topics & Concepts
Control theory (sociology)SingularityDynamics (music)UnderwaterComputer scienceBacksteppingAdaptive controlControl (management)Control engineeringEngineeringMathematicsPhysicsArtificial intelligenceGeologyMathematical analysisAcousticsOceanographyAdaptive Control of Nonlinear SystemsAdaptive Dynamic Programming ControlUnderwater Vehicles and Communication Systems