Abstract: Aiming at the problem that the classical intelligent optimization algorithm has premature convergence and ineffective loop in PID parameter tuning, an improved bacterial colony optimization algorithm is proposed. The shrinkage factor and the guided random search strategy are introduced in the individual location update to balance the global search ability and local search ability of the algorithm, and the dynamic random search is performed near the global optimal position to improve the local convergence precision of the algorithm. The ITAE indicator is selected as the optimization target to build the objective function and constraints. The nonlinear hysteresis PID controller with time-delay is taken as an example. The simulation results show that the proposed algorithm has the ability to self-end while improving the convergence accuracy, which can effectively suppress the overshoot.

Key words: PID parameter tuning, bacterial colony optimization algorithm, intelligent optimization algorithm, delay systems

摘要： 针对经典智能优化算法在PID参数整定时存在早熟收敛及陷入无效循环的问题，提出一种改进细菌菌落优化算法。在个体位置更新时引入收缩因子和有指导的随机搜索策略，以平衡算法的全局搜索能力和局部搜索能力，在全局最优位置附近进行动态随机搜索，以提高算法的局部收敛精度。选取ITAE指标作为优化目标构建目标函数和约束条件。以时滞非线性湿度PID控制器为例，仿真结果表明，该算法在提高收敛精度的同时具有自我结束的能力，能够有效抑制超调量。

关键词: PID参数整定, 细菌菌落优化算法, 智能优化算法, 时滞系统