A Data-Driven Performance Assessment Approach For Mpc Using Improved Distance Similarity Factor
PROCEEDINGS OF THE 2015 10TH IEEE CONFERENCE ON INDUSTRIAL ELECTRONICS AND APPLICATIONS(2015)
摘要
To keep the whole control system running well, a controller in Model Predictive Control (MPC) system plays an important role. Data-driven performance assessment approach can detect the poor performance of the controller in time and avoid the crash of the whole system. This paper proposes a method based on improved distance similarity factor in order to improve the accuracy of performance assessment. In this factor, Bhattacharyya distance is used for detecting the similarity of the real-time I/O data and historical I/O data. It considers both the mean absolute difference and the variance so as to enlarge the fluctuation change of the system I/O data and to improve the accuracy of performance assessment. A simulation on Wood-Berry distillation model is made to verify the effectiveness of this method.
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关键词
data-driven,performance assessment,improved distance similarity factor,Bhattacharyya distance
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