Abstract: In view of the advantage of PID controller, the application of PID controller in industrial control becomes wider and wider. Parameters design optimization of PID controller is important to PID controller. PID parameters optimization is always a conundrum. To solve the problem of PID parameters optimization, it proposes the wind driven optimization algorithm which is based on nature inspiration. The optimization algorithm for PID parameters is viewed as a search of search population in the search space, the integration for absolute error and the square of control input is used as optimization goal, optimal control quantity is calculated through iterative optimization. Compared with the genetic algorithm and particle swarm optimization algorithm, the simulation results show that the algorithm improves control precision, system response speed and robustness, and provides reference for PID parameters optimization for control system.

Key words: PID controller, wind driven optimization algorithm, genetic algorithm, particle swarm optimization algorithm, parameters optimization

摘要： 鉴于PID控制器的优越性，其在工业控制领域中的引用越来越广泛。PID控制器的性能主要在于其参数优化设计，PID参数优化问题一直是研究热点。为了解决PID参数优化问题，提出了一种基于自然启发的风驱动优化算法（WDO）的PID优化控制方法，该算法以PID三个参量为控制对象，以误差绝对值和控制输入平方项的时间积分作为优化目标，经过迭代寻优计算得到系统最优控制量。通过计算机仿真，并与遗传算法和粒子群算法PID参数优化相比，结果表明：该算法提高了系统的控制精度、响应速度和鲁棒性，为控制系统PID参数整定提供了参考。

关键词: PID控制器, 风驱动优化算法, 遗传算法, 粒子群算法, 参数优化