基于APSO算法的双容水箱PID参数优化仿真

Optimization of PID Control of Liquid Level Control of Double-Tank Based on Improved Particle Swarm Optimization Algorithm

针对双容水箱液位控制系统中PID参数整定困难的问题,采用一种自适应的粒子群(APSO)算法来优化双容水箱液位控制系统中的PID参数。上述算法将PID的三个参数Kp、Ki、Kd作为粒子的三个维度,采用目标函数值自适应的惯性权重系数调整策略,结合德普施双容水箱液位控制系统进行仿真。通过仿真得到:APSO算法比常规PSO算法具有更好的控制品质,即超调量明显减少、调整过程稳定。实验结果表明,APSO算法能够在液位控制中获得良好的动态性能,具有重要的实用价值。

An adaptive particle swarm optimization （APSO） algorithm was used to optimize the PID parameters in the liquid level control system of the double tank for the problem of difficulty in setting PID parameters in the liquid level control of the double tank. Three parameters kp, ki, kd of the PID were used the as the three dimensions of the particle, and the adaptive function of the objective function was used to adjust the inertia weight coefficient adjustment strategy, and the Depushi double tank level control system was combined for the simulation experiment. The simulation results show that the APSO algorithm has better control quality than the conventional PSO algorithm, that is, the overshoot is obviously reduced and the adjustment process is stable. The experimental results show that the APSO algorithm can obtain good dynamic performance in liquid level control and has important practical value.