Constrained Control of Autonomous Underwater Gliders Based on Disturbance Estimation and Tracking Back Calculation

IF 3.2 3区 计算机科学 Q2 AUTOMATION & CONTROL SYSTEMS International Journal of Robust and Nonlinear Control Pub Date : 2024-11-11 DOI:10.1002/rnc.7708
Ming Lei, Fuxin Jia, Haoruo Chai, Shuoshuo Ding, Tiedong Zhang
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引用次数: 0

Abstract

This article presents an anti-disturbance constrained control scheme for the pitch channel of autonomous underwater gliders subject to internal and external disturbances, as well as actuator saturation. First, the integral control technique is employed to develop a disturbance observer to estimate the overall effect of possible uncertainties and disturbances on the nominal vehicle model, which is referred to as the mismatched lumped disturbance. Then, a disturbance rejection control law is constructed based on the disturbance observer. Following that, a straightforward anti-windup modification is proposed to handle potential input constraints by using the tracking back calculation technique. Specifically, the difference between saturated and unsaturated control input signals is utilized to create a feedback signal that addresses the disturbance observer input, thereby alleviating system windup during actuator saturation events. Furthermore, the stability of the overall closed-loop system is established in term of the Lyapunov stability theorem, demonstrating that the tracking error is ultimately bounded. Compared with some existing anti-windup control schemes, the suggested approach offers intuitive design guidelines, resulting in a simple controller that can be easily implemented. Finally, the effectiveness and robustness of the proposed control scheme are verified through simulation results.

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来源期刊
International Journal of Robust and Nonlinear Control
International Journal of Robust and Nonlinear Control 工程技术-工程:电子与电气
CiteScore
6.70
自引率
20.50%
发文量
505
审稿时长
2.7 months
期刊介绍: Papers that do not include an element of robust or nonlinear control and estimation theory will not be considered by the journal, and all papers will be expected to include significant novel content. The focus of the journal is on model based control design approaches rather than heuristic or rule based methods. Papers on neural networks will have to be of exceptional novelty to be considered for the journal.
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