Path-Following Control of Autonomous Underwater Vehicles Subject to Velocity and Input Constraints via Neurodynamic Optimization

Zhouhua Peng, Jun Wang, Qing Long Han

Research output: Contribution to journalArticlepeer-review

146 Citations (Scopus)

Abstract

In this paper, a design method is presented for path-following control of underactuated autonomous underwater vehicles subject to velocity and input constraints, as well as internal and external disturbances. In the guidance loop, a kinematic control law of the desired surge speed and pitch rate is derived based on a backstepping technique and a line-of-sight guidance principle. In the control loop, an extended state observer is developed to estimate the extended state composed of unknown internal dynamics and external disturbances. Then, a disturbance rejection control law is constructed using the extended state observer. To bridge the guidance loop and the control loop, a reference governor is proposed for computing optimal guidance signals within the velocity and input constraints. The reference governor is formulated as a quadratically constrained optimization problem. A projection neural network is employed for solving the optimization problem in real time. Simulation results illustrate the effectiveness of the proposed method for path-following control of autonomous underwater vehicles subject to constraints and disturbances simultaneously in the vertical plane.

Original languageEnglish
Article number8575162
Pages (from-to)8724-8732
Number of pages9
JournalIEEE Transactions on Industrial Electronics
Volume66
Issue number11
DOIs
Publication statusPublished - Nov 2019
Externally publishedYes

Keywords

  • Autonomous underwater vehicles (AUVs)
  • extended state observer (ESO)
  • input and state constraints
  • neurodynamic optimization
  • path following

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