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--- simulink_quadcopter_simulation [2025/04/26 21:50] – yehyun
+++ simulink_quadcopter_simulation [2025/04/26 22:21] (current) – yehyun
@@ Line 22: / Line 22: @@
   * Deploy algorithms to a real Parrot Minidrone
   * Validate the results using motion capture data
-  * Modify the simulation for new drone specifications
 \\
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@@ Line 310: / Line 309: @@
 The following video shows the experimental setup. The Parrot Mambo drone, loaded with the deployed controller, was flown in the motion capture space while the flight data was simultaneously collected using mocap tracking:
-[[https://www.youtube.com/shorts/ya10C-6nGKU?feature=share]]
 {{youtube>ya10C-6nGKU?large}}
+In this experiment, a step input was applied to the Z-axis command to observe the altitude control performance. Two different scenarios were tested:
+**Scenario 1: Default Drone Weight**
+\\ A step input commanding a rise from approximately 0.6 meters to 1.1 meters was given. The comparison between the simulation and real flight data is shown below:
+{{ :simulator_part5_8.jpg?nolink&800 |}}
+The blue solid and dashed lines represent the simulator and real-world Z positions, respectively. The results demonstrate that the real drone altitude closely followed the simulation prediction, validating the accuracy of the simulated model under nominal conditions.
+**Scenario 2: Additional Payload**
+\\ In this test, a 5g weight was attached to the drone to assess the robustness of the controller and the simulator under additional load conditions. The results are shown below:
+Despite the added weight, the actual drone flight trajectory remained highly consistent with the simulator's prediction, especially in the Z-axis control. This suggests that the Simulink-based model maintains its reliability even under moderate payload variations.
+Overall, the close match between the simulated and actual flight data confirms the effectiveness and credibility of the developed quadcopter simulator. This validation provides confidence that the simulation environment can be used to predict real-world quadcopter behavior accurately.