Applied Research on Generative Artificial Intelligence for Modern Control Systems

Generative artificial intelligence, as a new technology paradigm, has received more and more attention for its powerful generative ability and wide application prospects. Especially in automated control systems, the application of technology based on generative artificial intelligence is gradually becoming a hot spot of research. In this paper, the generative AI automation control system is divided into four levels: input layer, processing layer, instruction generation and control execution layer, and combined with dual encoders, the attention model of multilingual to semantic expression is constructed. Two-dimensional variables are selected to construct a fuzzy PID control system to realize automation control for generative AI system. Comparing the control effects of fuzzy control PID and classical PID, the average errors of the two systems are 1= , 2= respectively. The maximum overshoot and rise time are 9% and 0.08 s, 5% and 0.04 s. The fuzzy PID control effect is more accurate, and at the same time improves the dynamic performance of the system. Analyze the implementation effect on the innovative service application of generative artificial intelligence. Comparing the overall recognition effect of the control system B proposed in this paper, and the two systems with reference to A, their overall recognition effect indexes are 0.94755 and 0.87211, respectively, and the fuzzy PID control system plays an auxiliary enhancement role in the contextual feature recognition of translation services in the intelligent library.

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Publication Details

Journal
Journal of Combinatorial Mathematics and Combinatorial Computing
Published
2025-04-15
DOI
https://doi.org/10.61091/jcmcc127a-123
Primary Topic
Advanced Data Processing Techniques
Type
article
Field-Weighted Citation Impact
0.00
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article

Applied Research on Generative Artificial Intelligence for Modern Control Systems

Shaoping Li
Journal of Combinatorial Mathematics and Combinatorial Computing
Advanced Data Processing Techniques
article

Applied Research on Generative Artificial Intelligence for Modern Control Systems

Shaoping Li
article en

Abstract

Generative artificial intelligence, as a new technology paradigm, has received more and more attention for its powerful generative ability and wide application prospects. Especially in automated control systems, the application of technology based on generative artificial intelligence is gradually becoming a hot spot of research. In this paper, the generative AI automation control system is divided into four levels: input layer, processing layer, instruction generation and control execution layer, and combined with dual encoders, the attention model of multilingual to semantic expression is constructed. Two-dimensional variables are selected to construct a fuzzy PID control system to realize automation control for generative AI system. Comparing the control effects of fuzzy control PID and classical PID, the average errors of the two systems are 1= , 2= respectively. The maximum overshoot and rise time are 9% and 0.08 s, 5% and 0.04 s. The fuzzy PID control effect is more accurate, and at the same time improves the dynamic performance of the system. Analyze the implementation effect on the innovative service application of generative artificial intelligence. Comparing the overall recognition effect of the control system B proposed in this paper, and the two systems with reference to A, their overall recognition effect indexes are 0.94755 and 0.87211, respectively, and the fuzzy PID control system plays an auxiliary enhancement role in the contextual feature recognition of translation services in the intelligent library.

Journal of Combinatorial Mathematics and Combinatorial ComputingVol. 127a
Openalex Percentile: Top 92%
Advanced Data Processing Techniques
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Applied Research on Generative Artificial Intelligence for Modern Control Systems — Shaoping Li · Journal of Combinatorial Mathematics and Combinatorial Computing (2025) | TGRS Research Map | TGRS