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Identification of Non Linear Multivariable Processes Modelled on Reproducing Kernel Hilbert Space: Application to Tennessee Process

机译:识别在再生核心核空间中建模的非线性多变量过程:田纳西州的应用

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In this paper we extend the results obtained in Reproducing Kernel Hilbert Space (RKHS) modelling in the case of Single Input Single Output (SISO) processes to the multivariable (MIMO) ones. Once the model structure is established the model parameters are identified. The validation of the identified model is built on the Tennessee Eastman Process (TE) which is a highly non linear multivariable and non minimum phase chemical process. This process which is unstable in open loop is handled as closed loop controlled process.
机译:在本文中,我们扩展了在单个输入单输出(SISO)过程的情况下再现内核HILBERT空间(RKHS)建模在多变量(MIMO)。建立模型结构后,识别模型参数。所识别模型的验证是基于田纳西州的Eastman Process(TE),这是一种高度线性多变量和非最小相化学过程。在开环中不稳定的此过程被处理为闭环控制过程。

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