Druppel 15-2 - Dispuut Watermanagement

Water Resource Management
Willem Malda has finished his studies in februari 2005. His graduationwork
dealed with a WM-canal and it’s control techniques. Therefor he visited the
Water Conservation Laboratory in Phoenix (Arizona, United States).
Masterthesis Waterresource Management
Model Predictive Control on Irrigation Canals,
"Application on the WM-Canal"
In March last year I started to look for a
master thesis research topic. My goal in
this search was to find a challenging
assignment. During the search I joined
the class of Operational Water
Management, which I found very interesting.
Especially the mixture between
water management and system control I
found interesting. Part of my graduation
period I spend at the United States
Water Conservation Laboratory (USWCL)
in Phoenix, Arizona. Here I studied the
WM-Canal and the control techniques
that are used to control this canal.
A lot of research that is done on controlling
irrigation canals is done on this
particular canal in Arizona. Most of the
controllers studied before use control
techniques that do not take the constraints
of the irrigation system into
account. To take these constraints into
account during control a control technique
called Model Predictive Control
can be used.
Model Predictive Control (MPC) is a control
methodology that can efficiently
control systems taking into account various
types of constraints. It originates
from the chemical process industry. In
the 70s the search for optimization
changed from supply driven production
to a production based on the prediction
of the demand. MPC uses all relevant
measurements and predictions within an
optimization to calculate the optimal
control action taking into account the
physical and operational constraints.
Because MPC is able to use an internal
model to minimize an objective function
this method of control is promising for
application in irrigation systems.
Therefore research is done on the application
of MPC on irrigation systems.
Cost Function Constraints Future Disturbance
Present and Future
Setpoints
-
+
-
Present and Future
Errors
Optimization
Present and Future
Inputs
Internal Model
Present and Future
Outputs
Open Loop
Output
Future Output
Controller
Real System
Present Input
Actuators
Real System
Canals
Present Output
Closed Loop
Output
Present Output
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