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Add optimal control problems - quadcopter #373
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Add optimal control problems - quadcopter #373
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Nice work thus far, this just needs some further refinements. Please refer to the existing examples as points of reference for the formatting and style.
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# # Quadcopter Trajectory and Set Point Tracking |
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Instead of "set point", please use "setpoint" through out.
# The quadcopter is an unmanned aerial vehicle with 4 propellors and in this case study, | ||
# we seek to determine an optimal control policy for the | ||
# 4 control inputs that must be adjusted over a specified time period to enable the | ||
# quadcopter to closely follow given set points/trajectory while minimizing the difference between | ||
# the set point and actual position and propellor input |
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I would clean up the grammar here a bit and be more succinct. This is a flight path tracking problem for a quadcopter UAV.
# ## Background | ||
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# Modelling the quadcopter trajectory is an infinite dimensional optimization problem. | ||
# The variables are dependent on time. |
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I would remove this.
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# Modelling the quadcopter trajectory is an infinite dimensional optimization problem. | ||
# The variables are dependent on time. | ||
# Using a sinusoidal setpoint trajectory and 5 minute time horizon, the problem formulation is as follows: |
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Move this to the formulation section
# ``` | ||
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# ## Model Definition | ||
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In all the sections below please reduce the number of spaces used. We shouldn't each line be orphaned by itself. Please refer to the other examples as a reference.
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Please add some discussion of the results at the end. Also, you need to had maintenance tests.
plot(p1, p2, p3, p4, layout = l) | ||
plot!(size=(800,600)) | ||
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savefig("Control Input (U).png") |
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Let's display the plot instead of saving it.
Created Issue #372
Motivation : Expands library of optimal control problems. Demonstrates usage of features such as parameter functions, multiple states and control inputs, trajectory tracking.
Example : The quadcopter is an unmanned aerial vehicle with 4 propellors and in this case study, we seek to determine an optimal control policy for the 4 control inputs that must be adjusted over a specified time period to enable the quadcopter to closely follow given set points/trajectory while minimizing the difference between the set point and actual position and propellor input.