Backstepping-Based Trajectory Tracking for Underwater Gliders

IF 1 Q4 AUTOMATION & CONTROL SYSTEMS Mechatronic Systems and Control Pub Date : 2019-11-26 DOI:10.1115/dscc2019-9028
Demetris Coleman, Maria L. Castaño, Osama Ennasr, Xiaobo Tan
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引用次数: 3

Abstract

Autonomous underwater gliders have become valuable tools for a myriad of applications ranging from ocean exploration to fish tracking to environmental sampling. To be suitable for these types of applications, precise sensing and monitoring is desired, which makes accurate trajectory control important. However, highly nonlinear under-actuated dynamics present significant challenges in control of gliders. In this work a backstepping-based controller is proposed for an underwater glider to track a desired position and heading reference in the sagittal plane with only two control inputs, the buoyancy and center of gravity along the longitudinal direction. In particular,the under-actuation issue is addressed by exploiting the coupled dynamics and introducing a new modified error that combines the tracking errors of heading and position references. In addition, an auxiliary system is incorporated to account for input constraints. Finally, a sliding mode observer is designed to obtain the estimates of body-fixed velocities, to facilitate practical implementation of the designed controller. The effectiveness of the proposed control scheme is demonstrated via simulations and its advantages are shown via comparison with a PID controller.
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基于后退的水下滑翔机轨迹跟踪
自主水下滑翔机已经成为无数应用的宝贵工具,从海洋勘探到鱼类跟踪到环境采样。为了适应这些类型的应用,需要精确的传感和监测,这使得精确的轨迹控制变得重要。然而,高度非线性的欠驱动动力学对滑翔机的控制提出了重大挑战。本文提出了一种基于后退的水下滑翔机控制器,该控制器只需要两个控制输入,即沿纵向的浮力和重心,即可在矢状面上跟踪所需的位置和航向参考。特别地,通过利用耦合动力学和引入一种新的修正误差来解决欠驱动问题,该修正误差结合了航向和位置参考的跟踪误差。此外,一个辅助系统被纳入考虑输入约束。最后,设计了一个滑模观测器来获得定体速度的估计,以方便所设计控制器的实际实现。通过仿真验证了所提控制方案的有效性,并与PID控制器进行了比较。
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来源期刊
Mechatronic Systems and Control
Mechatronic Systems and Control AUTOMATION & CONTROL SYSTEMS-
CiteScore
1.40
自引率
66.70%
发文量
27
期刊介绍: This international journal publishes both theoretical and application-oriented papers on various aspects of mechatronic systems, modelling, design, conventional and intelligent control, and intelligent systems. Application areas of mechatronics may include robotics, transportation, energy systems, manufacturing, sensors, actuators, and automation. Techniques of artificial intelligence may include soft computing (fuzzy logic, neural networks, genetic algorithms/evolutionary computing, probabilistic methods, etc.). Techniques may cover frequency and time domains, linear and nonlinear systems, and deterministic and stochastic processes. Hybrid techniques of mechatronics that combine conventional and intelligent methods are also included. First published in 1972, this journal originated with an emphasis on conventional control systems and computer-based applications. Subsequently, with rapid advances in the field and in view of the widespread interest and application of soft computing in control systems, this latter aspect was integrated into the journal. Now the area of mechatronics is included as the main focus. A unique feature of the journal is its pioneering role in bridging the gap between conventional systems and intelligent systems, with an equal emphasis on theory and practical applications, including system modelling, design and instrumentation. It appears four times per year.
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