【摘要】 PID的参数优化是应用工程中非常关键的一个问题。针对PID的参数优化，分析了两种最常用、经典的群智能算法——粒子群算法和蚁群算法在PID参数优化中的应用。两种群智能算法与PID控制器的结合适用于不同场合，各有优势和不足。两种群智能算法都能够有效地对PID参数进行整定，使得系统得到更好的鲁棒性和精确度。更多还原

【Abstract】 PID parameter optimization is a very key problem in application engineering. Aiming at PID parameter optimization, this paper analyzes the application of two most commonly used and classical swarm intelligence algorithms: particle swarm optimization algorithm and ant colony algorithm in PID parameter optimization. The combination of two population intelligent algorithm and PID controller is suitable for different occasions, and each has its advantages and disadvantages. The two population intelligent algorithms can effectively adjust the PID parameters in real time, so that the system has better robustness and accuracy.更多还原