一种基于速率线性化的非线性预测控制算法

Nonlinear model predictive control algorithm using velocity-based linearization

提出了一种基于速率线性化方法的非线性预测控制算法。该算法采用速率线性化方法得到与原系统非线性模型相对应的线性变参数模型,这类变参数模型在结构上是线性的,而模型参数将随工作条件的变化而变化,在系统的整个工作区间内都能很好地逼近原非线性模型。在此模型的基础上设计了预测控制器,并利用基于置信域的Levenberg-Marquardt算法在线求得预测控制率。最后对连续搅拌反应釜进行了仿真研究,仿真结果表明了该算法的可行性和有效性。

A new nonlinear model predictive control algorithm using velocity-based linearization was presented. The model used in the derivation of the control algorithm was obtained by using a velocity-based linearization method, and had a linear structure with variable parameters. The model parameters were then determined by the operation conditions of the system. It was shown that the linearized model approximated well the original nonlinear one. The model predictive control algorithm presented in this paper was based on the Levenberg Marquardt algorithm, which is efficient in computation and provides a general framework for model predictive control design. A simulation study on a nonlinear continuous stirred tank reactor （CSTR） showed that the proposed control algorithm was effective and applicable to many nonlinear industrial systems.