Adaptive backstepping and sliding mode control of fin stabilizer based on RBF neural network

被引：1
|
作者：
Zhang, Yuantao [1 ]
Shi, Weiren [1 ]
Yin, Lingling [1 ]
Qiu, Mingbai [2 ]
Zhao, Lin [2 ]
机构：
[1] Chongqing Univ, Coll Automat, Chongqing 400030, Peoples R China
[2] Chongqing Hua Elect Instrument Chief Plant, Chongqing 400021, Peoples R China
来源：
2009 IEEE INTERNATIONAL CONFERENCE ON INTELLIGENT COMPUTING AND INTELLIGENT SYSTEMS, PROCEEDINGS, VOL 2 | 2009年
关键词：
Fin stabilizer; ocean wave model; backstepping; sliding mode; RBF; PREDICTIVE CONTROL; DESIGN;
D O I：
10.1109/ICICISYS.2009.5358062
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Considering the influence of uncertainty as unknown nonlinearity, parameters perturbation and random waves disturbance to the fin stabilizer system during ship sailing in heavy sea, the random wave model is built and a robust controller based on adaptive backstepping, sliding mode and RBF neural network is proposed Adaptive backstepping and sliding mode control is the main controller and RBF neural network is used to compute the upper bound value of uncertainty which is composed of unknown nonlinearity, parameters perturbation and random waves disturbance, then the system stability is analyzed by using the Lyapunov theory The simulation results show that the control strategy is effective to decrease roll motion of fin stabilizer system in different sea conditions and has strong robust stability to overcome the uncertainty
引用
收藏
页码：302 / +
页数：2
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