Handling Rotational Degrees of Freedom in Coordinate Transformations

AI Thread Summary
The discussion focuses on the challenge of analyzing the response of a dynamic system when transforming between two coordinate systems with rotational degrees of freedom. While transforming x and y coordinates is straightforward using a transformation matrix, handling rotation, particularly with angles like theta and phi, complicates the process. The conversion attempts using spherical to Cartesian coordinates and back are deemed tedious. It is suggested that if some transformations are constant, they could be combined into a single transformation matrix. Caution is advised regarding gimbal lock when using Euler angles, which may necessitate the use of quaternions, although this adds complexity.
chinmay
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I am trying to analyse response of a dynamic system. The source disturbance is about x,y,theta (rotation about x ) & Phi of one coordinate system (red coloured coordinate system in the attached figure).

I need to get the response in another coordinate system ( green coloured coordinate system in the attached figure), whose all three axis is inclined to initial coordinate system.

In case of only x & y,it can be easily done using transformation matrix, but how to handle the transformation of rotational dof.

I tried to convert the source disturbance in spherical coordinate system , then cartesian, then transformation and finally again to (X, Y, Z, THETA, PHI, PSI,) new coordinate system; but this process is to tedious.

Is there any better alternative is available ?
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There is probably no easier way. If some of the transformations are constant, they can probably be combined into a consolidated transformation matrix. When using phi, psi, theta Euler angles, you need to be careful about "gimbol lock", where the angles are not well defined and it is hard to represent motion continuously. That can force you to use quaternions, which is a can of worms. Hopefully, you will not need to use quaternions.
 
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