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Analysis of one dimensional and two dimensional fuzzy controllers

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Journal of Systems Engineering and Electronics 2006年第2期17卷 362-373页

作者： Ban Xiaojun gao xiaozhi Huang Xianlin Wu Tianbao Dept. of Control Theory and Engineering Harbin Inst. of Technology Harbin 150001 P. R. China Inst. of Intelligent Power Electronics Helsinki Univ. of Technology Espoo Finland

The analytical structures and the corresponding mathematical properties of the one dimensional and two dimensional fuzzy controllers are first investigated in detail. The nature of these two kinds of fuzzy controllers is next probed from the perspective of control engineering. For the one dimensional fuzzy controller, it is concluded that this controller is a combination of a saturation element and a nonlinear proportional controller, and the system that employs the one dimensional fuzzy controller is the combination of an open-loop control system and a closedloop control system. For the latter case, it is concluded that it is a hybrid controller, which comprises the saturation part, zero-output part, nonlinear derivative part, nonlinear proportional part, as well as nonlinear proportional-derivative part, and the two dimensional fuzzy controller-based control system is a loop-varying system with varying number of control loops.

关键词： one dimensional fuzzy controller two dimensional fuzzy controller analytical structures fuzzy inference control system analysis.

An embedded vertical‐federated feature selection algorithm based on particle swarm optimisation

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CAAI Transactions on Intelligence Technology 2023年第3期8卷 734-754页

作者： Yong Zhang Ying Hu xiaozhi gao Dunwei Gong Yinan Guo Kaizhou gao Wanqiu Zhang School of Information and Control Engineering China University of Mining and TechnologyXuzhouChina The Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchunChina School of Computing University of Eastern FinlandKuopioFinland The Macao Institute of Systems Engineering Macao University of Science and TechnologyTaipaChina

In real life,a large amount of data describing the same learning task may be stored in different institutions(called participants),and these data cannot be shared among par-ticipants due to privacy *** case that different attributes/features of the same instance are stored in different institutions is called vertically distributed *** pur-pose of vertical‐federated feature selection(FS)is to reduce the feature dimension of vertical distributed data jointly without sharing local original data so that the feature subset obtained has the same or better performance as the original feature *** solve this problem,in the paper,an embedded vertical‐federated FS algorithm based on particle swarm optimisation(PSO‐EVFFS)is proposed by incorporating evolutionary FS into the SecureBoost framework for the first *** optimising both hyper‐parameters of the XGBoost model and feature subsets,PSO‐EVFFS can obtain a feature subset,which makes the XGBoost model more *** the same time,since different participants only share insensitive parameters such as model loss function,PSO‐EVFFS can effec-tively ensure the privacy of participants'***,an ensemble ranking strategy of feature importance based on the XGBoost tree model is developed to effectively remove irrelevant features on each ***,the proposed algorithm is applied to 10 test datasets and compared with three typical vertical‐federated learning frameworks and two variants of the proposed algorithm with different initialisation ***-mental results show that the proposed algorithm can significantly improve the classifi-cation performance of selected feature subsets while fully protecting the data privacy of all participants.

关键词： Evolutionary optimization feature selection privacy protection vertical‐federated learning

Parametric Data-driven Control Method of Hybrid System via Virtual Reference Feedback Tuning

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维普期刊数据库

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Parametric Data-driven Control Method of Hybrid System via V...

半实物仿真实验在电气类专业教学中的实践与思考

第36届中国控制会议

作者： Liu Jiaqi Li Shuangquan Lyu Ning gao xiaozhi School of Automation Harbin University of Science and Technology Department of Electrical Engineering and Automation Aalto University

ISBN: (纸本)9781538629185

This paper presents a data-driven method to design parameterized controller for a class of hybrid *** method relies on the virtual reference feedback tuning（VRFT） that is ongoing does not derive any detailed model knowledge of hybrid *** other model-based control methods,the VRFT method direct use of the measurement I/O data and select desired controllers by employing optimization tools from virtual reference ***,the optimal variables are directly as the control parameters of the hybrid *** improve the efficiency of control parameter optimization,a particle swarm optimization（PSO） algorithm with a ε-dominance strategy is used to implement the developed *** addition,the effectiveness of the method is demonstrated experimentally on a leader-following tracking task of multiple unmanned aerial vehicles（multi-UAVs） formation flight.

关键词： hybrid system data-driven control global model reference optimization parameterized controller design

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中国现代教育装备 2024年第1期 60-62页

作者：李鹏程郭英军薛智宏高晓芝田书娅河北科技大学河北石家庄050018

电气类专业开展半实物仿真实验是培养学生实践能力的一种新模式。分析新工科背景下电气类专业教学中普遍存在的问题,采用半实物仿真实验开展实践教学探索。实践表明,半实物仿真实验可有效提高学生解决复杂工程问题的能力和科研创新能力... 详细信息

电气类专业开展半实物仿真实验是培养学生实践能力的一种新模式。分析新工科背景下电气类专业教学中普遍存在的问题,采用半实物仿真实验开展实践教学探索。实践表明,半实物仿真实验可有效提高学生解决复杂工程问题的能力和科研创新能力,是新工科背景下人才培养的新途径。

关键词：新工科半实物仿真实践教学沉浸式体验

A New CMAC Neural Network Model with Adaptive Quantization Input Layer

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A New CMAC Neural Network Model with Adaptive Quantization I...

光伏直流微网系统的蓄电池新型充放电控制策略

1996 3rd International Conference on Signal Processing(ICSP’96)

作者： gao xiaozhi WANG Changhong X.M.gao Seppo J.Ovaska Department of Control Engineering P.O.Box 329Harbin Institute of Technology

＜正＞In this paper,we first discuss the structure, principle and learning algorithm of CMAC neural network model.A new adaptive quantization method based on competitive learning is then proposed to quantimize the inputs of CMAC according to the degree of variations of the approximated *** analysis and simulation results show that with the input layer using this algorithm CMAC can approximate more accurately and efficiently than the original model using equal-size quantization method.

关键词： Neural networks Adaptive systems Quantization Signal processing algorithms Function approximation Control engineering Laboratories Algorithm design and analysis Arithmetic Robots

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电力系统及其自动化学报 2019年第11期31卷 75-80页

作者：高晓芝高帆姜枫河北科技大学电气工程学院

光伏发电与蓄电池组成的直流微网系统可以实现能量平衡并且提高电能质量。在综合考虑光伏发电与蓄电池储能控制的基础上,设计了一种新型的适用于光伏直流微网系统的蓄电池充放电策略。该策略采用双闭环控制双向直流变换,保证了蓄电池与... 详细信息

光伏发电与蓄电池组成的直流微网系统可以实现能量平衡并且提高电能质量。在综合考虑光伏发电与蓄电池储能控制的基础上,设计了一种新型的适用于光伏直流微网系统的蓄电池充放电策略。该策略采用双闭环控制双向直流变换,保证了蓄电池与光伏电池间的正常能量交换。同时在考虑蓄电池电压变化、温度变化的基础上,采用模糊控制进行综合决策来避免蓄电池过充过放。最后在MATLAB/Simulink中建立了仿真模型,在不同运行情况下对光伏直流微网进行仿真,其结果验证了所提控制策略的有效性和可行性。

关键词：光伏发电蓄电池直流微网模糊控制器

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基于粒子群和免疫克隆的模糊C-均值聚类

沈阳建筑大学学报（自然科学版） 2009年第3期25卷 585-589页

作者：刘福荣高晓智王常虹哈尔滨工业大学空间控制与惯性技术研究中心黑龙江哈尔滨150001 赫尔辛基工业大学智能电力电子实验室芬兰0215

目的基于梯度下降的模糊聚类算法(FCM)选择最优解做改进,降低原FCM对初始值的敏感度,改进模糊C-均值算法,加快收敛速度,改善聚类的效果.方法该算法通过克隆选择改变粒子群优化算法(PSO)中群体的多样性,用PSO代替了FCM算法的基于梯度下... 详细信息

目的基于梯度下降的模糊聚类算法(FCM)选择最优解做改进,降低原FCM对初始值的敏感度,改进模糊C-均值算法,加快收敛速度,改善聚类的效果.方法该算法通过克隆选择改变粒子群优化算法(PSO)中群体的多样性,用PSO代替了FCM算法的基于梯度下降的迭代过程.结果算法具有很强的全局搜索能力,很大程度上避免了FCM算法易陷入局部极值的缺陷,同时也降低了FCM算法对初始值的敏感度.通过机器学习中的W ine和Iris数据对所提出的算法进行验证,取W ine样本数据为178个,条件属性为13,聚类类别数为3;Iris数据150个,条件属性个数为4,对这两类数据分别进行聚类分析,将试验结果与单纯的FCM和基于PSO的FCM比较,聚类的正确性有所提高.结论基于粒子群和免疫克隆的模糊C-均值聚类算法具有很强的全局搜索能力,提高了聚类的效果和效率.

关键词：粒子群优化算法聚类分析克隆选择模糊C-均值算法

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包神铁路公司绩效考评方法研究

神华科技 2018年第7期16卷 7-10页

作者：高小智神华包神铁路有限责任公司综合办公室内蒙古鄂尔多斯017000

在新形势下,传统的企业管理方式已经无法满足当前的实际发展需求,企业应根据当前市场经济特点,针对管理工作方式进行创新,制定完善的考评体系,提升企业管理工作的效率与质量,为公司快速稳健发展奠定基础。

关键词：管理考评提升

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前提不匹配的T-S模糊系统的时滞相关镇定

哈尔滨工业大学学报 2013年第11期45卷 1-7页

作者：张泽健黄显林班晓军高晓智 Zenger Kai 哈尔滨工业大学导航制导与控制理论中心哈尔滨150001 阿尔托大学自动化与系统技术系埃斯波00076

为了降低T-S模糊时滞系统稳定性条件的保守性以及提高其控制器设计的灵活性,本文提出了在前提不匹配条件下考虑T-S模糊时滞系统的时滞相关稳定性以及控制器设计问题.首次通过构造包含三重积分的增广Lyapunov泛函的方法,提出一个新的具... 详细信息

为了降低T-S模糊时滞系统稳定性条件的保守性以及提高其控制器设计的灵活性,本文提出了在前提不匹配条件下考虑T-S模糊时滞系统的时滞相关稳定性以及控制器设计问题.首次通过构造包含三重积分的增广Lyapunov泛函的方法,提出一个新的具有较小保守性的时滞相关稳定性准则;同时在前提不匹配条件下,给出了保证该系统渐近稳定的控制器设计方法,该方法提高了控制器设计的灵活性,并且对于具有不确定隶属度函数的模糊系统同样适用.最后通过两个仿真例子验证本文所提出的方法的有效性.

关键词： T-S模糊系统时滞相关前提不匹配线性矩阵不等式