基于免疫遗传算法优化的汽温系统变参数PID控制

VARIABLE ARGUMENTS PID CONTROL FOR MAIN STEAM TEMPERATURE SYSTEM BASED ON IMMUNE GENETIC OPTIMIZATION

针对工程实际应用,提出了一种改进的变参数PID控制策略,新的控制策略不论对于调节还是设定值跟踪,均具有很好的控制效果,对于工业实际中常见的大滞后对象也有很好的抗干扰性能和较强的鲁棒性。为了使变参数PID控制取得更好的性能,提出了鲁棒整定的思想,并采用免疫遗传算法进行设计参数的鲁棒优化调整。通过对具有严重参数不确定性、多扰动以及大迟延的电厂主蒸汽温度被控对象进行的仿真研究结果表明,基于免疫反馈和遗传机制的免疫遗传算法具有全局优化的能力,对变参数PID控制的参数优化设计是成功和有效的,使得具有多模型特性的汽温控制系统在不同的负荷下均获得很好的调节品质。同时也表明,免疫遗传算法和变参数PID控制均具有较好的发展前景,可用于某些多模型系统的同时整定设计。

Aiming at engineering application, the paper put forward a new control strategy of improved Variable Arguments Proportional-Integral-Derivative(VAPID),which has a good control effect on both regulating and set-point following. For the common large time-delay object happen frequently in the industrial practice, it has a quite good disturbance resistance and a strong robustness. In order to get a better performance for the variable-parameter PID control, a concept of robust tuning is put forward, meanwhile an immune genetic algorithm is also applied to robust optimal tuning of VAPID. Simulation is proceeded for the steam temperature system in a plant under such a control which has a severe uncertainty of parameters and multi-disturbance, as well as a large time-delay. The results show that the immune genetic algorithm is capable to complete a global optimization due to its immune feedback and genetic mechanism that is successful and effective for optimizing VAPID controller. The simulation results also demonstrate that the multi-model main steam temperature control system has an excellent regulation performance under different steam loads, and the optimization by using immune genetic algorithm and VAPID has a perfectible application future to the initial ones.