哈尔滨工程大学学报Issue(3)：267-273,7.DOI:10.3969/j.issn.1006-70432.01211078
基于预测模型的模糊参数自寻优S面控制器
Fuzzy parametre sefl-optimized S surface controller based on the prediction model
摘要
Abstract
In order to improve the adaptability of the S surface controller , a fuzzy parameter self-optimized method based on the prediction model was proposed .Firstly, the nonlinear auto-regressive moving average ( NARMA) mod-el was adopted to describe the dynamic characteristics of submersibles , and then the prediction model was estab-lished by identifying the NARMA model using the Elman neural network .For the requirement of the on-line identifi-cation, two improvements were made , i.e.sample size and model structure , thus the Elman network could replace its weights based samples updated with the change of environment .Finally, the prediction model was applied to the fuzzy parameter selfo-ptimized S surface controller .The simulation experiment was carried out and the expected effect was obtained with the parameter adjustments to the S surface controller using the proposed method .The im-proved S surface controller achieved faster response speed .关键词
潜水器/S面控制/参数自寻优/预测模型/模糊规则/模糊参数Key words
submersibles/Ssurface control/parameter self-optimized method/prediction model/fuzzy rules/fuzzy parameters分类
信息技术与安全科学引用本文复制引用
何斌,万磊,姜大鹏,张国成..基于预测模型的模糊参数自寻优S面控制器[J].哈尔滨工程大学学报,2014,(3):267-273,7.基金项目
国家自然科学基金资助项目（51209051）；国家863计划资助项目（2011AA09A106）；中国博士后科学基金面上资助项目（2012M520708）；中央高校基本科研业务费专项资金资助项目（ HEUCFR1203， HEUCF110112）． （）
