A Review of PID Controller Implementation Methods: From Analog Computers to Digital Systems

Abstract

With the rapid advancement of industrial automation, PID control systems have become essential tools in industrial control, prized for their simplicity and robustness. This paper examines six classic methods for implementing PID controllers: analog computers, digital systems, embedded systems, FPGAs, PLCs, and intelligent hardware. It compares their technical characteristics in terms of real-time performance, accuracy, flexibility, and cost, while also highlighting their evolution trends and application limitations. The results reveal that while analog computers offer millisecond-level response times in high-speed scenarios, their performance is limited by parameter fixation and insufficient accuracy. Digital controllers provide ±0.05% accuracy through discrete calculations, although their performance is constrained by sampling cycle delays. Embedded systems dominate the Internet of Things with their 10μW ultra-low power consumption and modular architecture, but face computing bottlenecks in multivariable control. FPGAs offer 99.999% reliability in applications such as lithography positioning, thanks to their nanosecond parallel processing capabilities, though their development cost is high. PLCs, with an MTBF of 500,000 hours, have become the preferred choice for harsh industrial environments, but are limited in terms of algorithm innovation. Intelligent hardware enhances parameter self-tuning efficiency by 60% using AI, but still faces bottlenecks in data quality and computing power. The study outlines key PID challenges: balancing accuracy, adaptability, and intelligence with system constraints. Major advances are anticipated in meta-learning-based tuning, heterogeneous computing, and digital twin verification.