The effect of model structure on the noise and disturbance sensitivity of predictive functional control
An Independent Model (IM) structure has become a standard form used in Predictive Functional Control (PFC) for handling uncertainty. Nevertheless, despite its popularity and efficacy, there is a lack of systematic analysis or academic rigour in the literature to justify this preference. This paper s...
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| 主要な著者: | , |
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| フォーマット: | Conference or Workshop Item |
| 言語: | English |
| 出版事項: |
Institute of Electrical and Electronics Engineers Inc.
2018
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| 主題: | |
| オンライン･アクセス: | http://irep.iium.edu.my/75839/1/75839_The%20effect%20of%20model%20structure%20on%20the%20noise_complete.pdf http://irep.iium.edu.my/75839/ https://ieeexplore.ieee.org/document/8550374 |
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| 要約: | An Independent Model (IM) structure has become a standard form used in Predictive Functional Control (PFC) for handling uncertainty. Nevertheless, despite its popularity and efficacy, there is a lack of systematic analysis or academic rigour in the literature to justify this preference. This paper seeks to fill this gap by analysing the effectiveness of different prediction models, specifically the IM structure and T-filter, for handling noise and disturbances. The observations are validated via both closed-loop simulation and real-time implementation and show that the sensitivity relationships are system dependent, which in turn emphasises the importance of performing this analysis to ensure a robust PFC implementation. |
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