Abstract: The optimization of PID parameters plays a decisive role in improving performance of PID control. In terms of the problem of PID parameters optimization, a flower pollination algorithm is applied. The algorithm is inspired by pollen migration, of which pollen position coordinates consist of three PID parameters, and the position is updated to optimal solution based on certain global pollination and local pollination rules. From the simulation experiment, compared with particle swarm optimization algorithm and seeker optimization algorithm, the system optimized by FPA possesses the characteristics of shorter system response time, higher control precision and better robustness, which provides a reference for PID parameters optimization for control system.

Key words: Proportion-Integration-Differentiation（PID） controller, parameter optimization, simulation, Flower Pollination Algorithm（FPA）, particle swarm optimization algorithm, seeker optimization algorithm

摘要： PID参数优化对PID控制性能起着决定性作用，针对PID参数寻优问题，提出运用一种花授粉算法（FPA）。该算法启发于自然界中花粉的传播授粉过程，以三个PID参数组成每个花粉单元的位置坐标，根据一定的全局授粉与局部授粉规则更新花粉单元的位置，使其向最优解迭代。仿真结果表明，与粒子群算法和人群搜索算法相比，花授粉算法优化参数使系统具备更短的响应时间、更高的系统控制精度以及更好的鲁棒性，为PID控制系统的参数整定提供了参考。

关键词: 比例积分微分控制器, 参数优化, 仿真, 花授粉算法, 粒子群算法, 人群搜索算法