摘要
焦炉是一个大惯性、纯滞后、非线性、时变和参数分布的系统,很难对其建立精确的数学模型。现有的线性系统控制方法对焦炉的温度控制存在精度不高、不能适应工况变化等问题。而模糊控制又因规则和隶属度函数的粗糙性导致系统在稳态时出现振颤,模型参考自适应控制需要对被控对象进行阶次辨识,而且算法复杂。针对上述问题,提出一种新的控制策略,使用模糊模型参考学习控制算法来对焦炉的温度进行控制,该方法结合模糊控制和自适应控制的优点,通过在线学习算法适应工况变化,提高了控制精度。对焦炉简化模型进行的仿真实验结果表明,系统具有良好的动态和稳态性能,有效减少了炉温波动,具有一定的推广应用价值。
Coke oven is a kind of nonlinear, time-varying and parameter-distributed system with great inertia and pure time-delay,whose model is difficult to be constructed. The coke oven＇ s temperature control based on linear system theory is lack of precision and couldn＇ t adapt to the change of operating conditions. The fuzzy controller may generate limit cycle on steady state due to the roughness of the fuzzy rules and the membership functions. A fuzzy model refer- ence learning control （FMRLC） was used to control the coke oven system,which avoided identifying the order of the coke oven system. The FMRLC incorporated the advantages of both fuzzy control and adaptive control, and it resolved those problems mentioned above through on-line learning algorithm. Simulation results are presented to illustrate that FMRLC has the good dynamic performances and steady state performances;furthermore, the temperature fluctuation is reduced. The successful simulation verifies the feasibility and validity of FMRLC in the coke oven system, and it is worthy of extension.
出处
《化工自动化及仪表》
CAS
2008年第3期23-27,共5页
Control and Instruments in Chemical Industry
基金
浙江省科技计划项目(2006C31016
021101039)
