Path-Following Control of an AUV: A Multiobjective Model Predictive Control Approach

被引：114

作者：

Shen, Chao ^{[1
]}

Shi, Yang ^{[1
]}

Buckham, Brad ^{[1
]}

机构：

[1] Univ Victoria, Dept Mech Engn, Inst Integrated Energy Syst IESVic, Victoria, BC V8W 2Y2, Canada

来源：

IEEE TRANSACTIONS ON CONTROL SYSTEMS TECHNOLOGY | 2019年 / 27卷 / 03期

基金：

中国国家自然科学基金; 加拿大自然科学与工程研究理事会;

关键词：

Autonomous underwater vehicle (AUV); multiobjective MPC (MOMPC); PF control; weighted sum (WS); logistic function; lexicographic ordering (LO); STABILITY;

D O I：

10.1109/TCST.2018.2789440

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

The path-following (PF) problem of an autonomous underwater vehicle (AUV) is studied, in which the path convergence is viewed as the main task while the speed profile is also taken into consideration as a secondary task. To accommodate the prioritized PF tasks, a novel multiobjective model predictive control (MPC) (MOMPC) framework is developed. Two methods, namely, weighted sum (WS) and lexicographic ordering, are investigated for solving the MOMPC PF problem. A logistic function is proposed for the WS method in an attempt to automatically select the appropriate weights. The Pontryagin minimum principle is subsequently applied for the WS-MOMPC implementation. The implicit relation between the two methods is shown, and the convergence of the solution with the MOMPC PF control algorithms is analyzed. Simulation studies on the Saab SeaEye Falcon AUV demonstrate the effectiveness of the proposed MOMPC PF control.

引用

页码：1334 / 1342

页数：9

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