基于自校正模型的非线性系统多模型预测控制

Multi-model predictive control of nonlinear system based on self-tuning model

关键词:  非线性系统  多模型预测控制  线性化  自校正模型  泰勒展开  pH值控制

Key words:  nonlinear system  multi-model predictive control  linearization  self-tuning model  Taylor expansion  pH control

摘要:

针对化工过程某些非线性系统的不对称动态特性，提出了一种基于自校正模型的多模型预测控制算法。在平 衡点附近建立线性模型，利用当前工作点，通过二阶泰勒展开校正模型参数,补偿非线性不对称动态特性，形成了非 线性系统的自校正多模型描述。以基于模型输出偏差的切换指标函数作为模型切换准则，结合状态反馈预测控制， 构成了多模型预测控制器。pH值控制的仿真结果验证了该算法的有效性。

Abstract:

To handle the unsymmetrical dynamic characteristics of some nonlinear systems in chemical process, a multi-model predictive control method was proposed based on self-tuning model. Through second order Taylor expansion, the current working point was used to modify the local linear models at equilibrium points to form the multiple self-tuning linear models of nonlinear system. And by the integration with state feedback predictive control and the employment of a switching function based on output errors, the multi-model predictive controller was composed. The simulated results of pH control show the efficiency of the method.