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REAL-TIME ONLINE FUZZY MODELING FOR ROBOTIC MANIPULATORS

机译:机器人的实时在线模糊建模

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摘要

This paper presents a real-time fuzzy modeling approach based on on-line clustering for a family of complex systems with severe nonlinearity such as robotic manipulators.The fuzzy model (Takagi-Sugeno fuzzy system) is identified real-time by online clustering and recursive least square estimation (RLSE).Using this method, the fuzzy rules can be added, modified and deleted automatically when the new data comes, and the consequence parameters of the T-S model can be recursively updated.Simulation results for a two-degree-of-freedom robot demonstrate the effectiveness and advantages of this approach.
机译:本文提出了一种基于在线聚类的实时模糊建模方法,用于一类具有严重非线性的复杂系统,例如机械手。最小二乘估计(RLSE):使用此方法,可以在出现新数据时自动添加,修改和删除模糊规则,并且可以递归更新TS模型的结果参数。自由机器人展示了这种方法的有效性和优势。

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