Entries in a direction cosine matrix as derivatives

In summary, the conversation discusses the relationship between a transformation matrix and trigonometric identities, specifically those related to rotations. The speaker wonders why the entries in the 2nd column of the transformation matrix are equivalent to the derivatives of the entries in the 1st column and seeks an intuitive explanation. The responder suggests that these trig identities can be derived from simple matrix multiplication and shares a video that demonstrates this concept. They also mention that setting up the rotation matrix in a different way would contradict established trig identities.
  • #1
maxhersch
21
0
This is a somewhat vague question that stems from the entries in a directional cosine matrix and I believe the answer will either be much simpler or much more complicated than I expect.

So consider the transformation of an arbitrary vector, v, in ℝ2 from one frame f = {x1 , x2} to a primed frame
f' =
{x'1 , x'2} which is related to the non-primed frame by a rotation of angle γ.

The transformation matrix will look like this:
6qK2No7.png


So this matrix can be derived from some simple trigonometric identities, specifically
$$ cos( \frac {\pi}{2} + \gamma) = -sin(\gamma) $$ and $$ cos(\frac {\pi}{2} - \gamma) = sin(\gamma) $$
So my question is perhaps more related to these identities than the matrix. Nonetheless, why are the entries in the 2nd column of the transformation matrix equivalent to the derivative of the entries in the 1st column? Is there some intuitive explanation, perhaps related to the trig identities? Regardless of how simple or complex the reasoning may be, I would appreciate some insight just for the sake of my curiosity. Thanks.
 
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  • #2
maxhersch said:
The transformation matrix will look like this:
6qK2No7.png


So this matrix can be derived from some simple trigonometric identities, specifically
$$ cos( \frac {\pi}{2} + \gamma) = -sin(\gamma) $$ and $$ cos(\frac {\pi}{2} - \gamma) = sin(\gamma) $$
So my question is perhaps more related to these identities than the matrix

This may not be quite what you are looking for, but I'd point out that a decent chunk of what we call trig identities comes from symbol manipulation of Taylor Series of sine and cosine. Put differently, people use calculus to get these identities.

The idea, is that, if you are constructing your rotation matrices correctly, a lot of these trig identities must follow from simple matrix multiplication, which I find to be more intuitive, especially when people draw nice pictures to go along. Take a look at this video:

https://www.lem.ma/web/#/content/VQ7wysLCIGIM0Hd7

He shows how ##cos(\alpha +\beta) = cos(\alpha) cos(\beta) - sin(\alpha)sin(\beta)## (plus a similar identity for ##sin(\alpha + \beta)##) must follow if you've set up your rotation matrices correctly.

A different, perhaps less satisfying take, is to consider the converse -- if we set up the rotation matrix in another way, we'd be contradicting well know trig identities.

Hopefully this is close to what you are asking in your question.
 

1. What is a direction cosine matrix?

A direction cosine matrix is a mathematical representation of the orientation of a rigid body in three-dimensional space. It is a 3x3 matrix that contains the direction cosines of the three axes of the body with respect to a fixed reference frame.

2. How are the entries in a direction cosine matrix related to derivatives?

The entries in a direction cosine matrix are related to derivatives through the use of Euler angles. The direction cosines are calculated from the derivatives of the Euler angles, which describe the rotation of the body in three-dimensional space.

3. Why are direction cosine matrices important in scientific research?

Direction cosine matrices are important in scientific research because they provide a mathematical representation of the orientation of a rigid body, which is essential for understanding the dynamics of the body and how it moves in space. They are commonly used in fields such as robotics, aerospace engineering, and biomechanics.

4. How are direction cosine matrices used in navigation systems?

In navigation systems, direction cosine matrices are used to transform measurements from one coordinate system to another. This is important for accurately tracking the position and orientation of objects in motion, such as aircraft or spacecraft.

5. Are there any limitations to using direction cosine matrices?

Yes, there are some limitations to using direction cosine matrices. They assume that the rigid body is not undergoing any non-rigid deformations, and they can only represent rotations up to a certain degree. Additionally, singularities can occur when the body's orientation approaches certain values, which can lead to errors in calculations.

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