| 基于递归神经网络的水下机器人故障辨识 |
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| 引用本文： | 袁芳,朱大奇,叶银忠.基于递归神经网络的水下机器人故障辨识[J].控制工程,2011,18(5):783-787. |
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| 作者姓名： | 袁芳 朱大奇 叶银忠 |
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| 作者单位： | 1. 上海海事大学水下机器人与智能系统实验室,上海,201306
2. 上海应用技术学院,上海,201418 |
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| 基金项目： | 上海市科委创新行动计划项目(10550502700); 长三角科技联合攻关项目(10595812700); 上海海事大学校基金项目(20110010,20110032) |
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| 摘 要： | 水下机器人故障检测与辨识是机器人实现主动客错控制的关键.针对一般非线性系统执行器和传感器故障辨识问题构造了一种基于递归神经网络的故障辨识模型,并将其应用于水下机器人执行器与传感器故障检测和辨识中.2个并行递归神经网络根据水下机器人实际输出与估计输出间的误差学习调整隐藏层与输出层权矩阵,辨识机器人中发生的执行器故障和传感...
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| 关 键 词： | 水下机器人 递归神经网络 故障辨识 传感器 执行器 |
Faults Identification of Underwater Vehicles Based on the Recurrent Neural Network |
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| YUAN Fang,ZHU Da-qi,YE Yin-zhong.Faults Identification of Underwater Vehicles Based on the Recurrent Neural Network[J].Control Engineering of China,2011,18(5):783-787. |
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| Authors: | YUAN Fang ZHU Da-qi YE Yin-zhong |
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| Affiliation: | YUAN Fang1,ZHU Da-qi1,YE Yin-zhong2 (1.Laboratory of Underwater Vehicles and Intelligent Systems,Shanghai Maritime University,Shanghai 201306,China,2.Shanghai Institute of Technology,Shanghai 201418,China) |
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| Abstract: | Fault detection and identification plays a key role to the active fault-tolerant control of underwater vehicles.A fault identification model based on the recurrent neural network is constructed to the general nonlinear system and is applied to the sensor and actuator faults detection and identification of underwater vehicles.The coefficient matrices of two parallel recurrent neural networks are adjusted according to the errors between the actual output states and the states estimation.The underwater vehicle... |
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| Keywords: | underwater vehicles recurrent neural network fault identification sensors actuators |
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