Abstract

This paper is devoted to the problem of prescribed performance trajectory tracking control for symmetrical underactuated unmanned surface vessels (USVs) in the presence of model uncertainties and input quantization. By combining backstepping filter mechanisms and adaptive algorithms, two robust control architectures are investigated for surge motion and yaw motion. To guarantee the prespecified performance requirements for position tracking control, the constrained error dynamics are transformed to unconstrained ones by virtue of a tangent-type nonlinear mapping function. On the other hand, the inaccurate model can be identified through radial basis neural networks (RBFNNs), where the minimum learning parameter (MLP) algorithm is employed with a low computational complexity. Furthermore, quantization errors can be effectively reduced even when the parameters of the quantizer remain unavailable to designers. Finally, the effectiveness of the proposed controllers is verified via theoretical analyses and numerical simulations.

Highlights

  • At present, unmanned surface vessels (USVs) are expected to play an increasingly important role in both military and civilian domains, such as reconnaissance and surveillance, marine surveying and mapping, marine resources exploration and development, etc. [1,2,3,4]

  • As one of the most significant components of USVs, trajectory tracking control systems determine the success of various missions and have received tremendous interest from the field of ocean engineering

  • As sliding mode control (SMC) is capable of realizing fast responses, is insensitive to interference, and can help to improve robustness, fruitful results have been obtained in many fields from utilizing newly developed sliding mode methods

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Summary

Introduction

USVs are expected to play an increasingly important role in both military and civilian domains, such as reconnaissance and surveillance, marine surveying and mapping, marine resources exploration and development, etc. [1,2,3,4]. In addition to input quantization, another important issue that deserves further investigation is the state constraint control of USVs, which has been ignored in numerous studies [7,8,11,16,17,25,26,27,28] In practical applications, it is realistic and of great significance to consider that the USV position error should be limited strictly by both sides of the feasible channel to ensure the navigation safety of the vessel [6]. It is assumed that all of the hydrodynamic parameters are bounded and unavailable

Formulation of HLQ
Function Approximation Based on RBFNNs
Problem Statement
Adaptive Backstepping Design Based on Quantized Input
Attitude Controller Design
Stability Analysis
Simulation
Parameter Setting
Robustness Test under Different Intensity of Disturbance
Conclusions

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