Analysis of Error in a Model
Predictive Irrigation Controller
Name
ingersoll-saming-meng-eecs-2023-thesis.pdf
Description
Thesis PDF
Size
4.88 MB
Format
Adobe PDF
Checksum (MD5)
175766ee77691c7e5609256096c557ea
Author(s)
Ingersoll, Samuel
Advisor(s)
Winter V., Amos G.
Date Issued
September 2023
Publisher
Massachusetts Institute of Technology
Abstract
Significant portions of the world’s agricultural land are vulnerable to desertification, leading to water shortages and changing climate conditions. Smart irrigation controllers could be part of the solution by helping farmers save water and adapt to changing climate without sacrificing yield. This thesis presents an analysis of sensitivity to crop model parameters in the MIT GEAR Lab’s new POWEIr irrigation controller with the goal of making it cheaper and easier to deploy and therefore more accessible. The analysis shows that, of the four crop parameters, the controller is most sensitive to the crop coefficient (K subscript c), moderately sensitive to the maximum rooting depth (Zᵣ), less sensitive to depletion fraction (f subscript d), and almost completely independent of the the yield response factor (K subscript y). This result is potentially useful for designing calibration procedures for the deployment of the POWEIr Controller, especially where there may be limited ability to calibrate the controller.
MIT Department
Massachusetts Institute of Technology. Department of Electrical Engineering and Computer Science
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