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A new hybrid approach in the estimation of end-states of a tubular plug-flow reactor by Kalman filter

机译:用卡尔曼滤波器估计管状推流反应器终态的新混合方法

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摘要

The state of a chemical plug-flow reactor is estimated at the reactor outlet by designing a hybrid extended Kalman filter algorithm.Temperature,activity and six(6)compositions are considered as typical reactor states and measurements are obtained by the addition of a random noise to the deterministic values of the dynamic reactor model.The system is non-linear in the eight states and distributed in time and axial position.A hybrid approach is introduced parallel to the conventional architecture of Kalman filter,which utilizes a so called end-state derivation block(ESDB)in order to cope with Kalman filtering of a multi-dimensional model.The real-world observations of the system are combined with the values of partial derivatives of the states,obtained from deterministic simulation results at system boundary,to handle the problem of special-variation of the states.So there is no need to update Kalman filter with respect to local variation of the states,and therefore this technique significantly decreases the amount of computer burden encountered with Kalman filtering of a distributed system.However it is limited to application of Kalman filter for estimation of the end-states.
机译:通过设计混合扩展卡尔曼滤波算法估算反应堆出口处的化学推流反应器状态,将温度,活度和六(6)组成视为典型反应器状态,并通过添加随机噪声获得测量值该系统在八个状态下是非线性的,并在时间和轴向位置上分布。与卡尔曼滤波器的传统架构并行引入了一种混合方法,该方法利用了所谓的最终状态为了应对多维模型的卡尔曼滤波,将系统的真实观测值与状态偏导数的值相结合(从系统边界处的确定性仿真结果获得)来处理因此,不需要针对状态的局部变化来更新卡尔曼滤波器,因此该技术具有重要的意义。可以减轻分布式系统的Kalman滤波遇到的计算机负担,但仅限于将Kalman滤波用于估计最终状态。

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