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ADAPTIVE FUZZY KALMAN FILTER APPLIED FOR IDENTIFICATION OF ROTOR/ACTIVE MAGNETIC BEARING DYNAMICS

机译:适用于转子/主动磁轴承动力学识别的自适应模糊卡尔曼滤波器

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The main goal of this research is to identify the system parameters of the dynamics of Rotor/Active Magnetic Bearing (Rotor/AMB) system employed in turbo molecular pumps (TMPs). The identification approach adopted in this work is based on experimental analysis and the application of Fuzzy Logic Adaptive Control- Extended Kalman Filter (FLAC-EKF). The estimation error for either system state or system parameters can be gradually converged to zero via self-tuning of the design parameters of FLAC-EKF. The proposed algorithm has been verified by numerical simulations and intensive experiments. It is concluded that the FLAC-EKF can exhibit satisfactory performance in terms of estimation accuracy on the system parameters even under contamination of a certain degree of process disturbance and sensor noise.
机译:该研究的主要目标是识别涡轮分子泵(TMPS)中采用的转子/有源磁轴承(转子/ AMB)系统的动态系统参数。本工作采用的识别方法是基于实验分析和模糊逻辑自适应控制扩展卡尔曼滤波器(FLAC-EKF)的应用。通过FLAC-EKF的设计参数的自我调整,系统状态或系统参数的估计误差可以逐渐融合到零。通过数值模拟和密集实验验证了所提出的算法。结论是,即使在一定程度的过程干扰和传感器噪声的污染下,FLAC-EKF也可以在系统参数上的估计精度方面表现出令人满意的性能。

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