Linearizing a 2-D quadrotor dynamic model

In summary, the equations for linearized dynamics in a 2-D quadrotor model are derived using the equilibrium hover configuration. This means that the quadrotor is in a state of equilibrium, but is still experiencing gravitational and moment forces that keep it in this state.
  • #1
Michael Wu
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Hi all!

I am taking an online course on aerial robotics and am currently on the topic of linearizing a 2-D quadrotor dynamic model. See slide (link below):

5dUD5LB.png


The equations under "linearized dynamics" are derived using the equilibrium hover configuration (e.g. y = y0, z = z0, Φ0 = 0, u1,0 = mg, u2,0 = 0) and the fact that at hover, sin(Φ) ~ Φ and cos(Φ) ~ 1.

So, linearized

y_ddot = (-u1/m)*sin(Φ) = (-mg/m)*Φ = -gΦ

This makes sense to me. But how come z_ddot isn't 0? and Φ_ddot isn't 0? Shouldn't

z_ddot = -g + (mg)/m*(1) = 0?
Φ_ddot = (0)/I_xx = 0?

Thank you!
 
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  • #2


Hi there,

Thank you for your question! Linearizing a 2-D quadrotor dynamic model can be a complex topic, so I'm glad you're taking an online course to learn more about it. The equations under "linearized dynamics" are derived using the equilibrium hover configuration, as you mentioned. This means that the quadrotor is in a state of equilibrium, meaning that there are no external forces acting on it and it is not accelerating in any direction.

In the case of z_ddot, it is not 0 because there is a gravitational force acting on the quadrotor. This force is represented by the -mg term in the equation, which is why z_ddot is equal to -g. Even though the quadrotor is in equilibrium, it is still experiencing a downward force due to gravity.

Similarly, for Φ_ddot, it is not 0 because there is a moment acting on the quadrotor due to the thrust from the rotors. This moment is represented by the u2 term in the equation. While the quadrotor is not accelerating in the Φ direction, it is still experiencing a moment that keeps it in equilibrium.

I hope this helps clarify things for you. Keep up the good work in your course and don't hesitate to ask any further questions!
 

Related to Linearizing a 2-D quadrotor dynamic model

1. What is a 2-D quadrotor dynamic model?

A 2-D quadrotor dynamic model is a mathematical representation of the motion and behavior of a quadrotor, which is a type of unmanned aerial vehicle (UAV) that is propelled by four rotors. This model takes into account the forces, torques, and other physical factors that affect the quadrotor's movement in two dimensions.

2. Why is it important to linearize a 2-D quadrotor dynamic model?

Linearizing a 2-D quadrotor dynamic model allows us to simplify the complex nonlinear equations that describe the quadrotor's behavior, making it easier to analyze and control. This is important for developing accurate and efficient control algorithms for the quadrotor.

3. How is a 2-D quadrotor dynamic model linearized?

A 2-D quadrotor dynamic model can be linearized by taking the partial derivatives of the nonlinear equations with respect to each state variable, and then linearizing the resulting equations around a desired operating point. This results in a linear system that can be described by a state-space model.

4. What factors affect the accuracy of a linearized 2-D quadrotor dynamic model?

The accuracy of a linearized 2-D quadrotor dynamic model can be affected by several factors, including the chosen operating point, the accuracy of the nonlinear model, and the presence of disturbances or uncertainties in the system. It is important to validate the linearized model against the original nonlinear model to ensure its accuracy.

5. How can a linearized 2-D quadrotor dynamic model be used in practice?

A linearized 2-D quadrotor dynamic model can be used in practice for designing control algorithms, simulating the quadrotor's behavior, and predicting its response to different inputs and disturbances. It can also be used for system identification and parameter estimation, which can help improve the accuracy of the model and control performance.

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