Model Predictive Control of Underwater Gliders Based on a One-layer Recurrent Neural Network

被引：0
|
作者：
Shan, Yuan [1 ]
Yan, Zheng [2 ]
Wang, Jun [1 ,2 ]
机构：
[1] Dalian Univ Technol, Sch Control Sci & Engn, Dalian, Liaoning, Peoples R China
[2] Chinese Univ Hong Kong, Dept Mech & Aeronaut Engn, Shatin, Hong Kong, Peoples R China
来源：
2013 SIXTH INTERNATIONAL CONFERENCE ON ADVANCED COMPUTATIONAL INTELLIGENCE (ICACI) | 2013年
关键词：
LIMITING ACTIVATION FUNCTION; MOTION CONTROL; STABILITY; SYSTEMS;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a motion control problem for underwater gilders in longitudinal plane is considered. A recurrent neural network based model predictive control approach is developed. The model predictive control of underwater gliders is formulated as a time-varying constrained quadratic programming problem, which is solved by using a rcurrent neural network called the simplified dual network in real-time. Simulation results are further presented to show the effectiveness and performance of the proposed model predictive control approach.
引用
收藏
页码：328 / 333
页数：6
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