双线性工业过程稳态模型辨识新方法

A New Identification Technique of Steady-State Models for Bilinear Industrial Processes

针对双线性模型描述的工业过程的优化控制的稳态模型建立须在人为干扰很小的条件下进行,提出了利用优化过程中设定点的阶跃信号作为输入信息,在Fi为可逆矩阵的假设下,获取其稳态模型的辨识方法。该方法新颖、简洁、精度高、对生产过程干扰少,仿真结果显示了方法的有效性和实用性。

It is very key to build the steady-state models of the industrial processes. Using the step signals of set-points changes in the course of optimizing control as the input signals to identifying the steady-state models is good identification technique and reduces the disturbed to the processes. In this paper, a new identification technique to obtain the steady-state models is presented for the bilinear industrial processes. which uses the step signals of set-points changes in the course of optimizing control as the input step signals to identifying the steady-state models of industrial processes described by bilinear models ,is presented .The novel technique is simple ,high identification accurate and less disturb to the industrial processes .Finally ,the simulation results show that the new approach is very efficient and practical.