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Introduction
Here is the final result, the quadrotor takes off from the ground to a height of 2 meters, then flies to a new point, controlled by PI in a multi-level setup that we wrote ourselves. We also see its shortcomings, overshoot and large tilt angles. Let's start. Hello, welcome to episode two of the quadrotor control series with sliding mode control. The quadrotor only has four inputs, total thrust and three moments, although its position is three-dimensional. Therefore, the control is made in layers, the outer loop controls the position by determining the tilt angle, and the inner loop controls that angle. Today we are building it with PID.
Step 1: Reference angle & six-channel PID
Create a control.py file. The reference angle function converts the desired horizontal acceleration into roll and pitch angles, using a small angle approach. To move forward, the drone must pitch proportionally to its acceleration divided by gravity. The PI control class has six channels, three for position and three for angles, each with proportional, integral, and derivative gains.
Step 2: Nested loop & simulation function
In each step, the position loop calculates the reference acceleration from the position error and velocity, then converts it into reference roll and pitch. Total thrust is calculated so that the vertical component keeps holding the weight even when the drone is tilted, so it is divided by the cosine of roll and pitch. The attitude loop generates moments to achieve the reference angle. The simulation function runs any control on the quadrotor model with adjustable references and wind.
Step 3: Takeoff & movement
Create a fly underscore PID.py file. The quadrotor starts on the ground, rises to 2 meters, then at the fifth second moves to the point 2, 1, 2. Run The time to reach 90% of the height is about 1.2 seconds, but with an overshoot of 13.6%. When moving, the roll and pitch angles temporarily reach 37 degrees, and the final position is still off by about 10 cm.
Step 4: Position, attitude & thrust
Let's look at the graphs. The X, Y, and Z positions reach their targets with slight oscillations. The attitude graph shows the drone must tilt sharply to accelerate and then tilt in the opposite direction to brake. Thrust spikes up to 31 N during takeoff. PID is sufficient for basic flight, but it is not robust against disturbances like wind, and that is what sliding mode control will improve. Done
Done!
We have already built a PI controller for the quadrotor, position loop, attitude reference angle, compensated thrust, and attitude loop, then flew it. In the next episode, we will study the theory of sliding mode control. Currently working on a thesis, dissertation, or research in the field of control systems, drones, and UAVs. Cerdas Inovasi Digital helps implement control systems, from 6 degrees of freedom quadrotor modeling, hierarchical PI, sliding mode control, up to disturbance observer for wind, and also opens Python programming courses for electrical and mechatronics engineering. Want to master the entire series, from quadrotor models to 3D path testing with wind? All 6 episodes, complete with PDF step-by-step guides and source code, are available for premium tutorial subscribers. Subscribe starting at Rp69.000 per month, save 28% with the 12-month package, or one-time payment of Rp999.000 for lifetime access. Want just one class? Buy a single class with lifetime access. Subscribe now at the premium page cerdasinovasidigital.com Contact us via WhatsApp, or visit cerdasinovasidigital.com Thank you for watching, see you in the next episode.
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Cerdas Inovasi Digital Team
Software developers, BIM & 3D engineers, and AI practitioners
53 video classes1,286 episodes
We build software, BIM models, games and AI automations for clients every day, and turn that hands-on work into step-by-step classes: every step is shown on screen and comes with a PDF guide you can keep.
