Instrumentation and Control Engineering Division, Netaji Subhas Institute of Technology, New Delhi, University of Delhi, Delhi.
ISA Trans. 2013 May;52(3):438-49. doi: 10.1016/j.isatra.2012.12.009. Epub 2013 Jan 30.
The present work is aimed at the design of Levenberg-Marquardt (LM) and adaptive linear network (ADALINE) based soft sensors and their application in inferential control of a multicomponent distillation process. Further the ADALINE sensor is trained online using past measurements, to adapt the changes in the inputs and is termed as dynamic ADALINE (D-ADALINE) sensor. The soft sensors are then used in the control loop to obtain LM based inferential controller (LMIC), ADALINE based inferential controller (ADIC) and D-ADALINE based inferential controller (DADIC) for the process. The performance of dynamic controller is also analyzed for different inputs and sampling intervals. The comparison of results shows the efficient and robust prediction capability of D-ADALINE sensor and hence DADIC proves to be the best controller.
本工作旨在设计基于 Levenberg-Marquardt (LM) 和自适应线性网络 (ADALINE) 的软传感器，并将其应用于多组分蒸馏过程的推断控制中。进一步地，ADALINE 传感器使用过去的测量值进行在线训练，以适应输入的变化，因此被称为动态 ADALINE (D-ADALINE) 传感器。然后，软传感器用于控制回路中，以获得基于 LM 的推断控制器 (LMIC)、基于 ADALINE 的推断控制器 (ADIC) 和基于 D-ADALINE 的推断控制器 (DADIC) 用于该过程。还分析了动态控制器在不同输入和采样间隔下的性能。结果比较表明，D-ADALINE 传感器具有高效和鲁棒的预测能力，因此 DADIC 被证明是最佳控制器。
