摘要
分析转炉煤气回收过程工艺及炉口差压对煤气回收效果的影响,针对转炉炉口差压控制对象的非线性、时变和干扰大的特点,采用一种改进的粒子群优化算法(ISPO)优化转炉炉口差压控制器的PID参数,增强了PID控制器的自适应能力。采用非线性递减惯性权重,增加极值扰动算子,加速了对PID参数的优化,使搜索到最优值的概率更高。通过仿真分析和工程应用表明:与常规PID控制相比,改进粒子群优化算法控制的转炉微差压具有超调量小、调节时间短、稳定性能好、抗干扰能力强的优势。
The process of converter gas recovery process and the effect of differential pressure on the gas recovery were analyzed.Aiming at the characteristics of non-linearity,time-varying and large disturbance of the converter differential pressure control object,an improved particle swarm optimization algorithm(ISPO)is used to optimize the PID parameters of the converter differential pressure controller,which enhances the adaptive capabilities of PID controller.The nonlinear decreasing inertia weight is used,and the extreme value perturbation operator is added,which accelerates the optimization of the PID parameters and improves the probability of searching for the optimal value.
出处
《工业控制计算机》
2018年第12期8-10,共3页
Industrial Control Computer
基金
安徽省重点研究与开发计划项目(1804a09020094)
安徽高校自然科学重点研究项目(KJ2018A0054)
关键词
转炉煤气
微差压
粒子群算法
PID优化
converter gas
differential pressure
particle swarm optimization
PID optimization
