Direct Adaptive Data Cloud based Fuzzy Control for NARMAX System
Yang,Zhao Xu1; Rong,Hai Jun1; Yang,Zhi Xin2
Source PublicationIEEE International Conference on Industrial Engineering and Engineering Management
AbstractThis work presents a novel nonlinear direct adaptive data cloud based fuzzy controller design method for a general class of NARMAX systems employing the evolving fuzzy approximation. In the proposed fuzzy controller, dynamic approximation capability is performed by the combined action of structure configuration and parameter adjustment using multiple strategies of recruiting, pruning and updating the data clouds, and self-tuning the consequent parameters. The normalization distance between two local densities is employed to measure the familiarity of each two data clouds, which is the criteria to trigger the pruning of redundant data cloud to further avoid the overlap or conflict. The simulation results demonstrate low computation cost and favorable tracking performance.
KeywordData Clouds Direct Adaptive Fuzzy Control Evolving Fuzzy System NARMAX System Pruning Strategy
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Document TypeConference paper
CollectionUniversity of Macau
Affiliation1.State Key Laboratory for Strength and Vibration of Mechanical Structures,Shaanxi Key Laboratory of Environment and Control for Flight Vehicle,School of Aerospace Engineering,Xi'an Jiaotong University,Xi'an,China
2.State Key Laboratory of Internet of Things for Smart,University of Macau,Department of Electromechanical Engineering,Macao
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GB/T 7714
Yang,Zhao Xu,Rong,Hai Jun,Yang,Zhi Xin. Direct Adaptive Data Cloud based Fuzzy Control for NARMAX System[C],2019:288-292.
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