Improved neural network adaptive control for compound helicopter with uncertain cross-coupling in multimodal maneuver

This study focuses on addressing the constrained attitude stabilization problem for an unmanned helicopter (UH) system subject to disturbances, input delay and actuator saturation. A constrained memory sliding mode is first presented to constrain the flight attitude while handling the input delay. On this basis, an adaptive finite-time nonlinear observer is proposed to estimate the lumped disturbance with unknown upper bound. Moreover, based on the hyperbolic tangent function, a saturated attitude controller is designed to tackle the input saturation problem via the adaptive laws. The finite-time stability of the closed-loop constrained attitude system is proved by Lyapunov synthesis. Finally, the developed scheme can accomplish attitude stabilization and overcome the influence of disturbances, attitude constraint, input delay and actuator saturation in an easy way. Numerical simulations are carried out to demonstrate the effectiveness of the proposed control scheme.

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Improved neural network adaptive control for compound helicopter with uncertain cross-coupling in multimodal maneuver

Abstract: Nonlinear Dyn manuscript No.

Cited by 2 publications

References 45 publications

Uncertainty meets fixed-time control in neural networks

Uncertainty meets fixed-time control in neural networks

Adaptive Finite-Time Constrained Attitude Stabilization for an Unmanned Helicopter System under Input Delay and Saturation

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