"新型PID控制技术的MATLAB仿真研究及应用"

The PID control is one of the earliest developed control strategies, and it is widely used in industrial process control due to its simple algorithm, good robustness, and high reliability, especially in deterministic control systems with established precise mathematical models. However, actual production processes often exhibit nonlinearity, time-varying uncertainty, making it difficult to establish accurate mathematical models. Conventional PID controllers cannot achieve ideal control effects in such scenarios. In order to adapt PID control to complex working conditions and high-performance control requirements, various advanced PID controllers have been developed, which far surpass the conventional PID control in controlling complex objects. This paper mainly focuses on five advanced adaptive PID control algorithms: expert PID control algorithm, fuzzy self-tuning PID control algorithm, single neuron adaptive PID control, grey PID control, and PID control based on genetic algorithm tuning, and conducts MATLAB simulation studies on them. The simulation results show that parameter self-tuning methods outperform general control methods in terms of adjustment time, overshoot suppression, and stability, making them suitable for industrial applications. Key words PID control; simple structure; adaptive; control algorithm; parameter tuning.