Examples, if installed as Package

The example scripts can be copied to a local examples/ folder with:

using KiteControllers
KiteControllers.copy_examples()

Or install everything (examples + required packages) in one step:

KiteControllers.install_examples()

Examples, if installed using Git

Launch Julia with:

jl

Then you get the menu of the examples by typing:

menu()

autopilot.jl — Full Autopilot Simulation

The primary example demonstrating the complete control stack.

Features:

Loads a kite model (KPS4) and kite control unit (KCU)
Creates all settings (WCSettings, FPCSettings, FPPSettings)
Builds a SystemStateControl and connects it to the kite model
Runs a real-time simulation loop with a 3-D viewer

Screenshot:

Minimal usage pattern

You can select one of the four, pre-defined projects, run the simulation, and on the left you have menu options to print the statistics or show one of the many 2D plots, visualizing the results.

autopilot_matlab.jl — Autopilot with the Winch Model in Matlab

Runs autopilot.jl with the winch model implemented in Matlab instead of the winch model of the selected project. Needs a Matlab installation, see Winch Model in Matlab.

parking_4p.jl — Parking Controller

Demonstrates how to bring a four-line kite to a stable parking position at high elevation using on_parking.

using KiteControllers, KiteModels
# create ssc as above, then:
on_parking(ssc, tether_length=200.0)

parking_wind_dir.jl — Parking with Changing Wind Direction

Demonstrates parking control while the upwind direction changes over time. The script applies a gradual wind-direction shift during the simulation, uses the parking controller to maintain stable flight, and plots azimuth, heading, upwind direction, and steering for analysis.

minipilot.jl — Minimal Autopilot

A stripped-down autopilot without 2D plots for understanding how to build a GUI based simulator. Exposes the core control loop in ~50 lines.

batch_pilot.jl — Batch Simulation

Runs multiple simulations back-to-back over a range of wind speeds and records key statistics (mean power, reel-out speed, etc.) to an Apache Arrow file in the output/ folder.

Run from the command line:

bin/batch_pilot hydra20_426

Statistics are written to output/batch-<project>_stats.yaml and the full time-series log to output/batch-<project>.arrow.

batch_plot — Post-processing Viewer

Interactive command-line tool for visualizing the Arrow log files produced by batch_pilot. Backed by examples/batch_plot.jl and the launcher script bin/batch_plot.

Basic usage:

# Open the interactive plot-selection menu for a project
bin/batch_plot hydra20_426

# Run a specific plot directly (window stays open until closed)
bin/batch_plot hydra20_426 plot_main
bin/batch_plot hydra20_426 plot_elev_az

# List all projects that have a log file in output/
bin/batch_plot --list

# List all available plot commands
bin/batch_plot --list-commands

Available plot commands:

Command	Description
`statistics`	Print summary statistics to the terminal
`plot_main`	Height, elevation, azimuth, tether length, force, reel-out speed, cycle
`plot_power`	Force, reel-out speed, mechanical power, energy, acceleration
`plot_control`	Elevation, azimuth, heading, force, depower, steering, FPP state
`plot_control_II`	Azimuth, heading, steering, course, psi_dot, NDI gain
`plot_winch_control`	Elevation, azimuth, force, set-force, reel-out speed, winch state
`plot_aerodynamics`	Lift-to-drag ratio, angle of attack, steering, yaw rate, side-slip
`plot_elev_az`	Elevation vs. azimuth scatter
`plot_elev_az2`	Elevation vs. azimuth from cycle 2 onward
`plot_elev_az3`	Elevation vs. azimuth from cycle 3 onward
`plot_side_view`	Side view (height vs. x position)
`plot_side_view2`	Side view from cycle 2 onward
`plot_side_view3`	Side view from cycle 3 onward
`plot_front_view3`	Front view from cycle 3 onward

tune_4p.jl — Controller Tuning

Interactive script for tuning the flight path controller gains (p, i, d, gain) for a four-line kite. Changes gain values and immediately re-runs the simulation to visualize the effect.

joystick.jl — Manual Joystick Control

Allows manual steering via a gamepad or joystick while the winch is controlled automatically or half-automatically by the WinchController. Useful for learning how to steer a kite manually. Half-automatically means you provide a set point for the reel-out speed manually, but the WinchController ensures that the maximal and minimal force are respected.

Learning Resources

File	Purpose
`autopilot.jl`	Full autopilot — start running this as first step
`minipilot.jl`	Minimal autopilot without 2D plotting, good for understanding the code
`parking_4p.jl`	Parking of the 4 point kite with disturbance
`parking_wind_dir.jl`	Parking simulation with gradually changing upwind direction
`batch_pilot.jl`	Batch simulations of projects
`batch_plot`	Post-processing and interactive plotting of batch logs
`tune_4p.jl`	Gain tuning of the parking controller
`joystick.jl`	Manual steering with automated or half-automated winch control
`plots.jl`	Post-processing and plotting of Arrow log files, not to be executed on its own
`stats.jl`	Statistical analysis of batch results, not to be executed on its own

Configuration Files

All settings are stored as YAML files in the data/ folder.

File	Settings struct
`settings.yaml`	General kite / simulation settings (`KiteUtils.Settings`)
`system.yaml`	System-level parameters
`fpc_settings.yaml`	`FPCSettings` — flight path controller
`fpp_settings.yaml`	`FPPSettings` — flight path planner
`wc_settings.yaml`	`WCSettings` — winch controller

Copy the default configuration files with:

KiteControllers.copy_control_settings()