Improvement of predictive control algorithm based on fuzzy fractional order PID
The existing predictive control strategy has comprehensive prior knowledge of the controlled process, requires weak continuity of the search space for parameter optimization, and its application is limited to some extent. Therefore, improved research on the fuzzy fractional proportional integral dif...
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| Published in | Journal of intelligent systems Vol. 32; no. 1; pp. 18219 - 27 |
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| Main Author | |
| Format | Journal Article |
| Language | English |
| Published |
Berlin
De Gruyter
01.01.2023
Walter de Gruyter GmbH |
| Subjects | |
| Online Access | Get full text |
| ISSN | 2191-026X 0334-1860 2191-026X |
| DOI | 10.1515/jisys-2022-0288 |
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| Summary: | The existing predictive control strategy has comprehensive prior knowledge of the controlled process, requires weak continuity of the search space for parameter optimization, and its application is limited to some extent. Therefore, improved research on the fuzzy fractional proportional integral differential (PID) predictive control algorithm is proposed. First, the control principle of PID predictive control equipment is proposed. According to this principle, the structure of the PID predictive control equipment adaptive fuzzy PID energy-saving controller is constructed. Through the PID energy-saving control parameter setting principle and fuzzy control rules, the adaptive fuzzy PID energy-saving control of PID predictive control equipment is realized. Finally, the fractional order PID predictive transfer function model is constructed to improve the predictive control algorithm based on PID optimization technology. The experimental results show that the accuracy and efficiency of the designed algorithm can get the best performance index, and its stability, overshoot, time, and control accuracy are basically unchanged. In the small area temperature control, the disturbance interference is small, the anti-disturbance ability is good, and it has strong robustness. |
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| Bibliography: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 2191-026X 0334-1860 2191-026X |
| DOI: | 10.1515/jisys-2022-0288 |