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国家自然科学基金(61103196)

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相关作者:王海红更多>>
相关机构:青岛科技大学更多>>
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Reconstruction Model of Ocean Observing Complex Virtual Instrument
2018年
With the newly proposed Global Ocean Observing Integration,ocean observing scope has been expanded from the region to the global,therefore the need of large-scale ocean observing system integration has become more and more urgent.Currently,ocean observing systems enabled ocean sensor networks are commonly developed by different organizations using specific technologies and platforms,which brings several challenges in ocean observing instrument(OOI) access and ocean observing system seamless integration.Furthermore,the development of ocean observing systems often suffers from low efficiency due to the complex programming and debugging process.To solve these problems,a novel model,Complex Virtual Instrument(CVI) Model,is proposed.The model provides formal definitions on observing instrument description file,CVI description file,model calculation method,development model and interaction standard.In addition,this model establishes mathematical expressions of two model calculation operations,meanwhile builds the mapping relationship between observing instrument description file and CVI description file.The CVI based on the new model can achieve automatic access to different OOIs,seamless integration and communication for heterogeneous environments,and further implement standardized data access and management for the global unified ocean observing network.Throughout the development,integration and application of such CVI,the rationality and feasibility of the model have been evaluated.The results confirm that the proposed model can effectively implement heterogeneous system integration,improve development efficiency,make full usage of reusable components,reduce development cost,and enhance overall software system quality.We believe that our new model has great significance to promote the large-scale ocean observing system integration.
QIU ZhijinGUO ZhongwenWANG YuHU TongLIU ChaoLI Ting
关键词:全球海洋传感器网络观察仪器数据存取
基于U模型的模糊免疫自抗扰控制方法研究
2022年
针对一类非线性系统在持续扰动下的控制问题,设计基于U模型的模糊免疫自抗扰控制方法;首先,引入U模型方法进行被控对象建模,提高处理非线性系统的能力,结合自抗扰控制方法,设计基于U模型的改进自抗扰控制器;在非线性反馈环节引入模糊免疫方法实现非线性智能反馈,设计基于U模型的模糊免疫自抗扰控制系统;最后仿真实验表明:基于U模型的模糊免疫自抗扰控制方法在保持了基于U模型的自抗扰控制的简洁性和良好抗扰性能的基础上,简化了控制器参数调节过程,在持续未知扰动下的跟踪速度、精度都更优。
韩明秀王海红
关键词:模糊控制免疫算法自抗扰控制非线性系统
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