基于遗传模糊免疫算法的PID参数整定优化研究

针对工业过程中的PID参数整定较难的问题,在分析模糊免疫算法的基础上,提出了一种遗传模糊免疫算法,用于在线整定PID参数。该算法用免疫反馈机理在线调整比例系数,模糊算法在线整定积分系数和微分系数。同时,该算法引用具有全局寻优特性的遗传算法优化免疫参数,克服了免疫参数选取不当而导致系统超调量较大、响应速度过慢的问题。针对工业过程中的无时滞过程、一阶惯性加时滞过程、二阶惯性加时滞过程、高阶系统过程,将该算法用于PID参数整定优化,并与模糊免疫算法、免疫PID算法、常规PID算法整定结果进行对比分析。仿真实验结果表明,遗传模糊免疫算法整定出的PID参数具有超调量小、调节时间短、抗干扰性强、鲁棒性强等优点,取得了较好的控制效果。

Research on Parameters Optimization of PID Controller Based on Genetic Fuzzy Immune Algorithm

To solve the difficulty of PID controller parameters tuning in industrial processes, a genetic fuzzy immune algorithm is proposed for tuning of PID parameters on-line based on fuzzy immune algorithm. Proposed algorithm is to adjust proportional coefficient by immune feedback mechanism, and adjust integral and differential coefficients by fuzzy algorithm. At the same time, genetic algorithm of global optimization is applied to optimize immune parameters, which overcomes the problem of large overshoot and slow response speed caused by improper selection of immune parameters. Aiming at the no time-delay system, first-order inertia with time-delay system, second-order inertia with time-delay process and high-order system, proposed algorithm is applied to tune PID parameters and compared with fuzzy immune algorithm, immune PID algorithm and conventional PID algorithm. Simulation experimental results show that PID parameters obtained by genetic fuzzy immune algorithm make control system has the advantages of small overshoot, short adjustment time, strong anti-interference and strong robustness, which gains good control effect.