首页 | 本学科首页   官方微博 | 高级检索  
     检索      

基于SVM的水下机器人预测S面控制
引用本文:张国成,万磊,李岳明.基于SVM的水下机器人预测S面控制[J].华中科技大学学报(自然科学版),2012,40(3):40-44.
作者姓名:张国成  万磊  李岳明
作者单位:1. 哈尔滨工程大学船舶工程学院,黑龙江哈尔滨,150001
2. 哈尔滨工程大学水下机器人重点实验室,黑龙江哈尔滨,150001
基金项目:国家自然科学基金资助项目
摘    要:针对舵桨联合操控水下机器人系统的非线性特点,将预测控制的思想引入经典S面控制中,构造了一种基于支持向量机(SVM)的预测S面控制器,改善了S面控制器的控制效果,增强其自适应性.用支持向量机辨识水下机器人的非线性系统模型,充分发挥了SVM的泛化能力,能准确预测其运动状态.构造二次型性能优化函数以获取S面控制器的最优控制参数,进而获得水下机器人最优控制律.仿真结果表明:基于支持向量机的预测S面控制器具有结构简单、响应速度快、鲁棒性好等优点可行且有效.

关 键 词:智能水下机器人  运动控制  支持向量机  预测S面控制  参数优化

Predictive method of S surface control using on SVM for AUV
Zhang Guocheng Wan Lei Li Yueming.Predictive method of S surface control using on SVM for AUV[J].JOURNAL OF HUAZHONG UNIVERSITY OF SCIENCE AND TECHNOLOGY.NATURE SCIENCE,2012,40(3):40-44.
Authors:Zhang Guocheng Wan Lei Li Yueming
Institution:Zhang Guocheng Wan Lei Li Yueming(a College of Shipbuilding Engineering;b National Key Laboratory of Science and Technology on Underwater Vehicle,Harbin Engineering University,Harbin 150001,China)
Abstract:A predictive S surface controller based on support vector machine(SVM) was obtained to analyze typical nonlinearity control system of torpedo-shaped autonomous underwater vehicles(AUV).The control algorithm was based on the S surface controller,which imported the idea of prediction control and combined with the excellence of support vector machine.Firstly the model of AUV was established to predict the motion states by the SVM.Then the control parameters of S surface controller were optimized by the quadratic performance function.At last the best control law was obtained.Simulation on AUV shows that the controller has merits of easy design,quick response,and excellent robustness,which is feasible and effective.
Keywords:automatic underwater vehicle  motion control  support vector machine  predictive S surface control  parameter optimization
本文献已被 CNKI 万方数据 等数据库收录!
设为首页 | 免责声明 | 关于勤云 | 加入收藏

Copyright©北京勤云科技发展有限公司  京ICP备09084417号