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

2016 ◽  
Author(s):  
Ana M. Lugo ◽  
Cinthia Audivet Durán ◽  
Marco E. Sanjuán

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.

Processes ◽  
2019 ◽  
Vol 7 (10) ◽  
pp. 758 ◽  
Author(s):  
Debaprasad Dutta ◽  
Simant Ranjan Upreti

In this work, an optimal state feedback control strategy is proposed for non-linear, distributed-parameter processes. For different values of a given parameter susceptible to upsets, the strategy involves off-line computation of a repository of optimal open-loop states and gains needed for the feedback adjustment of control. A gain is determined by minimizing the perturbation of the objective functional about the new optimal state and control corresponding to a process upset. When an upset is encountered in a running process, the repository is utilized to obtain the control adjustment required to steer the process to the new optimal state. The strategy is successfully applied to a highly non-linear, gas-based heavy oil recovery process controlled by the gas temperature with the state depending non-linearly on time and two spatial directions inside a moving boundary, and subject to pressure upsets. The results demonstrate that when the process has a pressure upset, the proposed strategy is able to determine control adjustments with negligible time delays and to navigate the process to the new optimal state.


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