A Summary of PID Control Algorithms Based on AI-Enabled Embedded Systems

• Published in: Security and communication networks Vol. 2022; pp. 1 - 7
• Main Author: Zhou, Yi
• Format: Journal Article
• Language: English
• Published: London Hindawi 23.04.2022; John Wiley & Sons, Inc
• Subjects: Adaptive control; Ant colony optimization; Artificial intelligence; Control algorithms; Controllers; Embedded systems; Fuzzy control; Fuzzy logic; Fuzzy sets; Genetic algorithms; Mathematical models; Neural networks; Parameter estimation; Predictive control; Principles; Process controls; Proportional integral derivative; Systems stability
• ISSN: 1939-0114; 1939-0122; 1939-0122
• DOI: 10.1155/2022/7156713

Proportional-integral-derivative (PID) controllers are extensively used in engineering practices for their simple structures, robustness to model errors, and easy operations. At present, there is a great variety of PID controllers. Companies have developed intelligent regulators with functions for automatically tuning PID parameters. For present PID controllers, strategies such as intelligence, self-adaptation, and self-correction are extended to transmission PID. PID controllers and corresponding improved ones are utilized in 90% of industrial control processes. In this paper, PID control algorithms are summarized. This paper focuses on advanced control strategies such as PID control, predictive PID control, adaptive PID control, fuzzy PID control, neural network PID control, expert intelligent PID control, PID control based on genetic algorithms, and PID control based on ant colony algorithms. Besides, these kinds of algorithms are compared, and prospects of PID algorithms are forecast at the end of this paper.