Path-Following Control of Autonomous Underwater Vehicles Subject to Velocity and Input Constraints via Neurodynamic Optimization
Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review
Author(s)
Related Research Unit(s)
Detail(s)
Original language | English |
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Pages (from-to) | 8724-8732 |
Journal / Publication | IEEE Transactions on Industrial Electronics |
Volume | 66 |
Issue number | 11 |
Online published | 13 Dec 2018 |
Publication status | Published - Nov 2019 |
Link(s)
Abstract
A design method is presented for path-following control of under-actuated 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 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 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.
Research Area(s)
- Path-following, input and state constraints, neurodynamic optimization, extended state observer, autonomous underwater vehicles
Citation Format(s)
Path-Following Control of Autonomous Underwater Vehicles Subject to Velocity and Input Constraints via Neurodynamic Optimization. / Peng, Zhouhua; Wang, Jun; Han, Qing-Long.
In: IEEE Transactions on Industrial Electronics, Vol. 66, No. 11, 11.2019, p. 8724-8732.Research output: Journal Publications and Reviews (RGC: 21, 22, 62) › 21_Publication in refereed journal › peer-review