基于操作轨迹模型的非线性预测控制算法

Nonlinear model predictive control based on operating-trajectory model

针对工业过程的非线性,本文首先提出了一种操作轨迹非线性模型的辨识方法:根据调度变量的操作轨迹,选取若干个典型工作点;在各个典型工作点,辨识各自的线性模型;根据测试数据以及过渡数据,得到全局插值非线性模型。在此基础上,本文进一步提出一种基于操作轨迹模型的非线性预测控制算法,并采用多步线性化方法进行问题求解。由于仅需要在典型工作点上进行测试,降低了全局建模的辨识成本,而且控制品质好,仿真结果表明了该算法的有效性。

Nonlinear model predictive control based on operating-trajectory model is proposed. In nonlinear process identification, the so-called operating-trajectory model approach is used. Firstly, typical working-points are selected based on operating-trajectory of scheduling variable; Secondly, linear models are identified using data sets at various working-points exclusive transition data; Finally, the LPV model is identified by interpolating the linear models using total data. Further, nonlinear model predictive control based on operating-trajectory model is proposed. The control action is computed via multi-step linearization method of nonlinear optimization problem. The method uses low cost tests and keeps better control performance. Simulation verifies the effectiveness of the method.