强制循环蒸发系统的多模型预测解耦控制

Multiple models decoupling predictive control of forced-circulation evaporation system

以实际的具有多变量、强耦合、强非线性特性的氧化铝强制循环蒸发系统为例,将一类多变量非线性系统分为线性模型和非线性未建模动态两部分,提出了由线性预测解耦控制器,神经网络非线性预测解耦控制器和切换机制组成的多模型预测解耦控制方法,并且证明了闭环系统的稳定性.最后,通过对强制循环蒸发系统的仿真实验,验证了所提方法的有效性.

A forced-circulation evaporation process of an alumina plant, which has multivariable, strong couplings between loops and high nonlinearities, is presented as an example. Firstly, the multivariable nonlinear system is treated into a linear part plus a nonlinear unmodeled dynamics part. And a multiple models decoupling predictive control design method has been developed. The proposed control approach is composed of a linear decoupling predictive controller, a neural network nonlinear decoupling predictive controller and a switching mechanism. Furthermore, the stability of the closed-loop system is proved. Finally, the simulation results of the forced-circulation evaporation system show the effectiveness of the proposed approach.