A Review on Intelligent Control Theory and Applications in Process Optimization and Smart Manufacturing

被引:1
|
作者
Lee, Min-Fan Ricky [1 ,2 ]
机构
[1] Natl Taiwan Univ Sci & Technol, Grad Inst Automat & Control, Taipei 106335, Taiwan
[2] Natl Taiwan Univ Sci & Technol, Intelligent Mfg Innovat Ctr, Taipei 106335, Taiwan
关键词
intelligent control; process optimization; smart manufacturing; soft computing; MACHINE LEARNING APPROACH; HYBRID GENETIC ALGORITHM; MODEL-PREDICTIVE CONTROL; DECISION-MAKING METHOD; FUZZY-LOGIC APPROACH; MULTIOBJECTIVE OPTIMIZATION; OPTIMAL OPERATION; NEURAL-NETWORKS; DEEP; SYSTEM;
D O I
10.3390/pr11113171
中图分类号
TQ [化学工业];
学科分类号
0817 ;
摘要
In the evolving landscape of manufacturing, the integration of intelligent control theory stands as a pivotal advancement, driving both process optimization and the paradigm of smart manufacturing. This review delves into the multifaceted applications of intelligent control theory, emphasizing its role in equipment, operations, and controls optimization. With a focus on three primary methodologies-fuzzy logic, neural networks, and genetic algorithms-the paper elucidates their biological parallels and their significance in simulation, modeling, and optimization. The transformative potential of smart manufacturing, synonymous with Industry 4.0, is also explored, highlighting its foundation in data, automation, and artificial intelligence. Drawing from a comprehensive analysis of recent literature, the review underscores the growing interest in this domain, as evidenced by the surge in publications and citations over the past decade. The overarching aim is to provide contemporary discourse on the applications and implications of intelligent control theory in the realms of process optimization and smart manufacturing.
引用
收藏
页数:33
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