Abstract
This article addresses the subject for bottom-following control of underactuated unmanned undersea vehicles (UUVs) with input saturation in the presence of unknown model uncertainties and unknown external disturbances. A robust adaptive dynamic surface bottom-following control scheme is developed based on the recursive sliding mode with nonlinear gains and neural networks, which can steer an underactuated UUV to precisely follow the bottom profile at a constant altitude as a basic feature. The bottom-following guidance law is derived based on the Serret-Frenet frame, the line of sight (LOS) and Lyapunov's direct technique. Then, the bottom-following controller is designed based on the recursive sliding mode and dynamic surface control (DSC), to stabilize the bottom-following errors. The radial basis function neural networks (RBF NNs) are employed to online approximate the uncertain dynamics of underactuated UUVs, while the adaptive laws are introduced to estimate the bounds of the RBF NN approximation errors and unknown environmental disturbances. Additionally, an auxiliary dynamic system (ADS) is presented to handle the effect of input saturation. The uniform boundedness of all the closed-loop signals is guaranteed via Lyapunov analysis. The simulation results are presented to verify and illustrate the effectiveness of the proposed control scheme.
Highlights
Unmanned undersea vehicles (UUVs) have be used for a broad range of marine scientific, marine commercial and marine military applications [1]–[4], as they can perform the dull, dirty and dangerous tasks (3D tasks)
The bottom-following is a typical motion control problem of underactuated UUVs, which is concerned with the design of control strategies that steer an UUV to sail on such a desired path relies on the bottom terrain at a constant altitude
For the aforementioned control schemes, the dynamics of underactuated UUVs must be accurate or that there is only parameter perturbation with known supremum, while all bottom-following controllers are based on the assumption of unconstrained motion-control actuators
Summary
Unmanned undersea vehicles (UUVs) have be used for a broad range of marine scientific, marine commercial and marine military applications [1]–[4], as they can perform the dull, dirty and dangerous tasks (3D tasks). For the aforementioned control schemes, the dynamics of underactuated UUVs must be accurate or that there is only parameter perturbation with known supremum, while all bottom-following controllers are based on the assumption of unconstrained motion-control actuators. SMC-class controllers are widely used for the motion control of underactuated UUVs. Inspired by the above considerations, this work develops the adaptive RBF NN-DSC-based recursive sliding mode control scheme for the bottom-following of the underactuated UUV with uncertainties and input saturation. It is known that all the closed-loop signals are uniform boundedness via Lyapunov analysis This approach is able to effectively solve the contradiction of possess high control accuracy and good transient performance at the same time in the presence of input saturation and the designed controller is non-fragile to the perturbation of its own parameters. UUV can be available for the feedback in real-time, including positon, pitch angle and surge velocity
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