Review on System Identification, Control, and Optimization Based on Artificial Intelligence
Control engineering plays an indispensable role in enhancing safety, improving comfort, and reducing fuel consumption and emissions for various industries, for which system identification, control, and optimization are primary topics. Alternatively, artificial intelligence (AI) is a leading, multi-disciplinary technology, which tries to incorporate human learning and reasoning into machines or systems. AI exploits data to improve accuracy, efficiency, and intelligence, which is beneficial, especially in complex and challenging cases. The rapid progress of AI facilitates major changes in control engineering and is helping advance the next generation of system identification, control, and optimization methods. In this study, we review the developments, key technologies, and recent advancements of AI-based system identification, control, and optimization methods, as well as present potential future research directions.
Authors
- Xu Chen (ORCID: https://orcid.org/0000-0002-9870-7287)
- Hui Wan (ORCID: https://orcid.org/0000-0002-3201-068X)
- Qiang Wu (ORCID: https://orcid.org/0000-0002-9169-3791)
- Bozhi Zhang (ORCID: https://orcid.org/0009-0008-4267-4325)
- Pan Yu (ORCID: https://orcid.org/0000-0002-3333-9719)
- Bin Zhao (ORCID: https://orcid.org/0000-0002-0889-2504)
- Shangbin Yang
Institutions
- Beijing University of Technology (CN)
Publication Details
- Journal
- Mathematics
- Published
- 2025-03-13
- DOI
- https://doi.org/10.3390/math13060952
- Citations
- 4
- Primary Topic
- Advanced Sensor and Control Systems
- Type
- article
- Field-Weighted Citation Impact
- 4.86
Funders
- National Natural Science Foundation of China