Robust neural network‐based tracking control for unmanned surface vessels under deferred asymmetric constraints
Yanchao Sun, Cheng‐Peng Li, Hongde Qin, Zhongchao Deng, Zhe Chen
Abstract
Abstract In this article, the constraints on unmanned surface vessels are imposed after a certain time after the system operation. Based on the shift function, this article proposes an asymmetric barrier Lyapunov function and achieves the control scheme with deferred and asymmetric full‐state constraints. In addition, radial basis function neural network and an antiwindup compensator are adopted for the problems of uncertainties and input saturation. The simulation results demonstrate the feasibility of the proposed control strategies.
Topics & Concepts
Control theory (sociology)Unmanned surface vehicleArtificial neural networkLyapunov functionComputer scienceControl (management)State (computer science)Tracking (education)Scheme (mathematics)Function (biology)Surface (topology)Control engineeringNonlinear systemEngineeringMathematicsArtificial intelligenceAlgorithmPsychologyBiologyMathematical analysisQuantum mechanicsEvolutionary biologyPedagogyMarine engineeringGeometryPhysicsAdaptive Control of Nonlinear SystemsAdaptive Dynamic Programming ControlAdvanced Control Systems Optimization