This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are si...This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.展开更多
针对柔性机械臂结构振动控制中可能出现的压电器件故障问题,以提高系统可靠性和稳定性为主要研究目标,提出了一种集小波神经网络与取代控制技术相结合的容错控制方法.首先设计了3种粘贴不同故障压电片的机械臂结构;然后采用小波包对各...针对柔性机械臂结构振动控制中可能出现的压电器件故障问题,以提高系统可靠性和稳定性为主要研究目标,提出了一种集小波神经网络与取代控制技术相结合的容错控制方法.首先设计了3种粘贴不同故障压电片的机械臂结构;然后采用小波包对各种故障压电片进行特征提取,通过径向基函数网络进行特征识别;再根据故障类型,选用硬件取代控制或基于一种新型非线性滑模观测器的软件取代控制;最后通过NI CRIO平台进行的容错控制实验结果表明,传感器件故障诊断的置信度达到0.9,前两阶振动模态的抑制效果达到10 d B以上.展开更多
文摘This article proposes an innovative strategy to the problem of non-linear estimation of states for electrical machine systems. This method allows the estimation of variables that are difficult to access or that are simply impossible to measure. Thus, as compared with a full-order sliding mode observer, in order to reduce the execution time of the estimation, a reduced-order discrete-time Extended sliding mode observer is proposed for on-line estimation of rotor flux, speed and rotor resistance in an induction motor using a robust feedback linearization control. Simulations results on Matlab-Simulink environment for a 1.8 kW induction motor are presented to prove the effectiveness and high robustness of the proposed nonlinear control and observer against modeling uncertainty and measurement noise.
文摘针对柔性机械臂结构振动控制中可能出现的压电器件故障问题,以提高系统可靠性和稳定性为主要研究目标,提出了一种集小波神经网络与取代控制技术相结合的容错控制方法.首先设计了3种粘贴不同故障压电片的机械臂结构;然后采用小波包对各种故障压电片进行特征提取,通过径向基函数网络进行特征识别;再根据故障类型,选用硬件取代控制或基于一种新型非线性滑模观测器的软件取代控制;最后通过NI CRIO平台进行的容错控制实验结果表明,传感器件故障诊断的置信度达到0.9,前两阶振动模态的抑制效果达到10 d B以上.
