The Tracking Control of Unmanned Underwater Vehicles Based on QPSO-Model Predictive Control

被引：1

作者：

Gan, Wenyang ^{[1
]}

Zhu, Daqi ^{[1
]}

Sun, Bing ^{[1
]}

Luo, Chaomin ^{[2
]}

机构：

[1] Shanghai Maritime Univ, Lab Underwater Vehicles & Intelligent Syst, Shanghai 201306, Peoples R China

[2] Univ Detroit Mercy, Dept Elect & Comp Engn, Detroit, MI 48221 USA

来源：

INTELLIGENT ROBOTICS AND APPLICATIONS, ICIRA 2017, PT I | 2017年 / 10462卷

关键词：

Unmanned Underwater Vehicle; Trajectory tracking; Quantum-behaved particle swarm optimization; Model predictive control; Backstepping control;

D O I：

10.1007/978-3-319-65289-4_66

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

For the trajectory tracking control of Unmanned Underwater Vehicles (UUV), an improved Model Predictive Control (MPC) method based on Quantum-behaved Particle Swarm Optimization (QPSO) is proposed. The concept of trajectory tracking is given firstly in this paper. Then QPSO-MPC is employed to realize the tracking control. The QPSO problem is suggested to optimization problem of minimizing the objective function with the conditions of satisfying the control constraints. The simulation results which is under the two-dimensional situation show that QPSO-MPC can effectively solve the speed jump problem. More effective and feasible for trajectory tracking problem compared with backstepping control method.

引用

页码：711 / 720

页数：10

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