NDLI: Tuning and Implementation of a Feedback Control Strategy for Drying Process Based on IAE Minimization

Content Provider	The American Society of Mechanical Engineers (ASME) Digital Collection
Author	Ana, M. Lugo Durán, Cinthia Audivet Sanjuán, Marco E.
Copyright Year	2016
Abstract	Agricultural products contain a significant amount of moisture during the harvesting stage. The presence of this moisture increases the deterioration rate of the products during storage, handling, and processing periods; drying is one of the most suitable processes that can be applied to these by-products before using them as cattle feed or soil conditioner. This process is certainly one of the most energy consuming found in industry. The selection of an appropriate process control strategies can minimize production and maintenance cost, maximize product quality and reduce environmental pollution. Rotary dryers are normally employed to dry agricultural products because it can give high production rate and high drying uniformity. The aim of this research is to improve the performance of a feedback control strategy for a drying process, based on the implementation design of experiment; this approach allows finding specifics tuning parameters and potential operation conditions that will traduce in a more robust process. The selected criterion to evaluate the performance of the strategy is the integral absolute of the error (IAE) and the analysis is based on a dynamic model of a rotary dryer. The objective of the process improvement is to find an operation region, function of the controller gain, the integral time and derivative time, in which IAE parameter is minimized, this will lead to enhancement of equipment performance and reduction of the wear of the final control element. Once the controlled strategy is described, the methodology states an exploratory stage, for process characterization, establishment of a regression model, to describe the relation between experiment significant factors and response variable, maximum ascent route, exploration of a possible curvature, definition of a new regression model and finally determination of a new optimum operating point.
File Format	PDF
ISBN	9780791850596
DOI	10.1115/IMECE2016-67291
Volume Number	Volume 6B: Energy
Conference Proceedings	ASME 2016 International Mechanical Engineering Congress and Exposition
Language	English
Publisher Date	2016-11-11
Publisher Place	Phoenix, Arizona, USA
Access Restriction	Subscribed
Subject Keyword	Product quality Equipment performance Process control Control equipment Maintenance Design Errors Regression models Pollution Dryers Storage Feedback Wear Soil Dynamic models Drying
Content Type	Text
Resource Type	Article

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