title: Development of soft sensor for neural network based control of distillation column.
abstract: 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.
authors: Instrumentation and Control Engineering Division, Netaji Subhas Institute of Technology, New Delhi, University of Delhi, Delhi. ashansit@gmail.com
authors: Asha
authors: A
authors: Rani
authors: Vijander
authors: V
authors: Singh
authors: J R P
authors: JR
authors: Gupta
mesh_terms: D000465:Algorithms; D003198:Computer Simulation; D017076:Computer-Aided Design; D057168:Distillation / Q000295:instrumentation* / Q000379:methods; D004867:Equipment Design; D019544:Equipment Failure Analysis; D005246:Feedback; D008962:Models, Theoretical; D016571:Neural Networks, Computer; D012984:Software; D012985:Software Design; D014159:Transducers