Closed-loop Irrigation Scheduling and Control

• Author / Creator

  Nahar, Jannatun

• The increasing population and adverse climate conditions are escalating fresh water
  scarcity globally. Since irrigation consumes a large portion of fresh water, it is very
  important to improve irrigation efficiency. One such method on improving irrigation
  efficiency is to use a closed-loop scheme instead of the traditional open-loop irrigation
  schemes. There are many challenges in implementing a closed-loop irrigation scheme.
  These challenges include soil moisture sensing, soil parameter and state estimation
  based on limited measurements, control-oriented model development, scheduler and
  controller designs that take into account various constraints in irrigation. In this
  thesis, rigorous methods are proposed to overcome some of these challenges.
  First, a systematic approach based on system observability analysis and state estimation is developed to estimate the soil moisture inside an agro-hydrological system
  where measurements are not easily available. A discrete-time state-space model based
  on Richards’ equation is used to describe the agro-hydrological system that considers
  water dynamics in the system and the interaction between the soil, the plant and the
  atmosphere. The nonlinear agro-hydrological system is linearized every sampling time
  and the observability of the overall system is determined based on locally linearized
  models at every sample instant. Based on the linearized models, we investigate how
  the number and location of output measurements affect the degree of observability of
  the system. To demonstrate the efficiency of the proposed approach, state estimation
  is performed using the extended Kalman filter on both simulated and real field data.
  The parameters of the model are estimated using prediction error method based on
  historical output measurements.
  Next, using the information from estimated states and measurements, we have performed a comparative study between closed-loop and open-loop irrigation scheduling
  and control. In agriculture irrigation management, irrigation scheduling is typically
  ii
  performed in an open-loop fashion and is done only once at the beginning of a growing
  season. In this work, we study whether closed-loop scheduling with closed-loop control can lead to improved performance in terms of crop yield and water conservation
  in agriculture irrigation. The interaction between the soil water, the crop (maize in
  this work) and the atmosphere is described by an agro-hydrological model, which is a
  partial differential equation. In the proposed scheduling and control scheme, both the
  scheduler and the controller are designed using model predictive control (MPC). The
  scheduler uses a long time horizon (with a sampling period of one day) that covers
  the entire crop growth season and the horizon shrinks as time moves. The primary
  objective of the scheduler is to maximize the crop yield. The controller uses a much
  shorter prediction horizon and a much finer sampling period. The primary objective
  of the controller is to track the soil moisture reference calculated by the scheduler. To
  alleviate the computational complexity of the scheduler and the controller, a linear
  parameter varying (LPV) model is identified for the scheduler and controller, respectively. The performance of the closed-loop scheduling scheme is evaluated against the
  traditional open-loop scheduling scheme under different scenarios.
  Furthermore, this thesis has extended research on closed-loop irrigation scheduling
  to a special case where irrigation is performed using storm water to irrigate recreational turfs. In this work, a modeling and scheduling approach for an integrated
  storm water management and irrigation problem is presented. The primary objective is to simultaneously ensure that the green space is irrigated appropriately and
  the level of the storm water pond is maintained adequately. It is proposed to use
  closed-loop irrigation scheduling to achieve this objective. A steady-state model is
  developed to calculate the soil water storage for different irrigation amounts. To
  handle the uncertainties, real-time feedback from the pond is used to re-evaluate
  the scheduling optimization problem every week. Simulation results show that the
  proposed closed-loop scheduling gives much improved control performance.

• Subjects / Keywords

  • mpc
  • Closed-loop
  • irrigation
  • storm water
  • scheduling,control

• Graduation date

  Fall 2019

• Type of Item

  Thesis

• Degree

  Doctor of Philosophy

• DOI

  https://doi.org/10.7939/r3-8mg8-d434

• License

  Permission is hereby granted to the University of Alberta Libraries to reproduce single copies of this thesis and to lend or sell such copies for private, scholarly or scientific research purposes only. Where the thesis is converted to, or otherwise made available in digital form, the University of Alberta will advise potential users of the thesis of these terms. The author reserves all other publication and other rights in association with the copyright in the thesis and, except as herein before provided, neither the thesis nor any substantial portion thereof may be printed or otherwise reproduced in any material form whatsoever without the author's prior written permission.