It solves the problem of model order determination and model validation for multivariable processes . it improves model quality and reduces time for plant test and data analysis and reduces disturbance to unit operation during plant test 它避免了多變量過程辨識方法的模型階次估計、模型驗證的難點;與階躍測試法相比,采用多通道測試信號,對裝置生產(chǎn)的影響小,且允許操作工在測試期間進行操作。
5 . a multivariable process identification based on asymptotic black-box theory is studied . firstly, a high-order mimo arx model and its frequency error bound is estimated from identification data and low-order siso models is obtained from high-order mimo arx model 作者對一種基于漸近黑箱理論的多變量過程辨識方法進行了研究:首先用高階arx模型估計模型參數(shù),并給出高階模型的頻域均方誤差;然后,對高階arx模型進行降階處理。
Single variable statistical process control ( svspc ) and mspc are both spc, the shortage of svspc is that it only notices the value of one variable at some moment, not suiting to analyze the multivariable process data with interrelation among them 統(tǒng)計過程控制包括單變量統(tǒng)計方法和多元統(tǒng)計方法。傳統(tǒng)的單變量統(tǒng)計過程控制技術的局限性在于僅注意監(jiān)視某一時刻的一個質量變量或關鍵過程變量,不適合分析變量間存在相關特性的多變量過程數(shù)據(jù)。