采用Hammerstein模型的非线性预测控制

Nonlinear Predictive Control Based on Hammerstein Models

对于象ｐＨ中和，高纯度分离以及化学反应等过程的控制，由于其过程本身的严重非线性而变得十分困难．本文提出了一种采用Ｈａｍｍｅｒｓｔｅｉｎ模型的预测控制方法来控制诸如上述的非线性过程．Ｈａｍｍｅｒｓｔｅｉｎ模型用两种方法进行辨识：联立辨识法与序贯辨识法．特别地，本文提示了一种改进型Ｈａｍｍｅｒｓｔｅｉｎ模型用于克服常规Ｈａｍｍｅｒｓｔｅｉｎ模型在控制器设计时的不足之处．对一ｐＨ中和过程的仿真结果表明，基于上述两种Ｈａｍｍｅｒｓｔｅｉｎ模型的预测控制在定值与随动系统情况下均得到了比常规ＰＩＤ调节器要好得多的控制交果．

The control of processes such as processes such as pH neutralization, high purity separaqtions and some chemical reactors can be very difficult due to their highly nonlinear nature. In this peper, a predictive control strategy based on the Hammerstein model is proposed and evaluated for such processes. The Hammerstein models are identified by two approaches, simultaneous identification and sequential identification. In particular, a modified Hammerstein model is proposed to overcome the disadvantages of the standard model for controller design. Simulation studies for a pH neutration process indicate that predictive control based on either Hammerstein model can provide much better setpoint tracking and disturbance rejection than well-tuned PID controllers.