空气压缩机的模糊预测控制

The Fuzzy Predictive Control of Air Compressor System

空气压缩机的工艺流程和工作过程复杂,是空气分离工艺过程中高能耗设备之一。作为被控对象的空气压缩机系统具有滞后、非线性等特点,常规的PID控制难以达到高品质的生产要求。为提高生产效率,降低能耗,构建空压机控制系统,提出了基于模糊预测控制,利用出口压力作为模糊前提变量,选取4个工况点,通过工程整定法,构建广义对象有限冲激响应滤波器(FIR)模型。最后通过4个工况点进行阶跃扰动实验,仿真结果表明控制算法具有良好的负荷适应性,实现简单且参数易于在线调整等优点。

The process of air compressor system is not only complex, but it is one of high energy consumption equipments. Conventional PID control is difficult to satisfy the high quality requirement on an air compressor system as controlled object because of its delay and nonlinear features. To improve the production efficiency and reduce energy consumption, the FIR model of air compressor system is built based on fuzzy predictive control theory, which selects the outlet pressure as a fuzzy premise variable and tuned by the operating rules. The result of step disturbance simulation experiments at 4 operation points showed that it has advantages as good adaptability for different loads and adjusting parameters online easily.