CAJ | 학술논문

针对复杂工业非线性系统建模难度大、精度低等问题，基于多模型插值的变参数线性( LPV)模型辨识算法，提出双工作点变量条件下的带约束多项式权重函数结构及其参数寻优策略，以有效降低非线性系统辨识的难度并充分保证所建模型的全局稳定性。以高纯度分馏塔这一典型非线性工业过程为研究对象进行LPV模型建模与仿真，获得了较好的输出和阶跃响应曲线拟合结果，验证了LPV模型能够充分反映非线性系统的运行特性以及所提算法的有效性和实用性。
침대복잡공업비선성계통건모난도대、정도저등문제，기우다모형삽치적변삼수선성( LPV)모형변식산법，제출쌍공작점변량조건하적대약속다항식권중함수결구급기삼수심우책략，이유효강저비선성계통변식적난도병충분보증소건모형적전국은정성。이고순도분류탑저일전형비선성공업과정위연구대상진행LPV모형건모여방진，획득료교호적수출화계약향응곡선의합결과，험증료LPV모형능구충분반영비선성계통적운행특성이급소제산법적유효성화실용성。
In order to better handle the complex nonlinear industrial processes and improve model accuracy, this paper studied the identification algorithm for LPV ( linear parameter varying) models based on multi-model interpolation. The structure and the corresponding optimization strategy of two-scheduling-variables-based polynomial weighting function with constrains were proposed, which can effectively reduce the difficulty of nonlinear model identification and guarantee the model’s global stability. The accuracy and effectiveness of the developed LPV model were verified by simulating a typical industrial process, namely a high purity distillation column. Both the LPV model outputs and step responses fit the real process well.