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发表于 2019-8-2 11:35:57
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正向/正向运动学的困难。
目标是在给定液压缸延伸部的情况下计算x,y,z,α,β,γ。使用的方法需要尝试x,y,z,α,β,γ的新值。然后计算顶部平台上六个连接之间的距离,并将这些距离与液压缸的延伸进行比较。计算出的距离和气缸延伸之间会有误差。每个柱面的误差是平方的,六个平方误差的总和加在一起。对六个参数中的每一个进行一次小的改变,一次一个。每次更改后计算误差平方和。这决定了必须改变六个参数中的每一个。新位置应该具有较低的平方误差总和。如果平方误差之和小于x,y,z的新值,则α,β,γ优于旧值。重复该过程,直到误差平方和接近零。
随机改变x,y,z,α,β,γ的值需要极其好运才能使平方误差之和接近于0.有一种更好的方法。 Newton-Raphson有一种简单的方法来最小化误差,但它需要找到导数或斜率。这很容易在课堂上进行。当误差平方和非常小时,误差平方和的导数也很小。位置反馈产生的一点噪音可能导致计算不稳定。我仍在尝试不同的方法来避免噪音而不牺牲准确性。此时,我可以计算x,y,z,α,β,γ,因此平方误差之和小于0.0001。
课堂与现实之间存在很大差异。
Difficulties with forward / positive kinematics.
The goal is to compute the x, y, z, α, β, γ given the hydraulic cylinder extension. The method used requires trying a new value of x, y, z, α, β, γ. Then calculate the distance between the six connections on the top platform and compare these distances with the extension of the hydraulic cylinders. There will be errors between the computed distance and the cylinder extensions. The error for each cylinder is squared and the sum of the six squared errors is added together. A small change is made in for each of the six parameters, one at a time. The sum of squared errors is calculated after each change. This determines how much each of the six parameters must be changed. The new position should have a lower sum of squared errors. If the sum of squared errors is getting smaller than the new value for x, y, z, α, β, γ is better than the old values. This procedure is repeated until the sum of squared errors is close to zero.
Changing the values of x, y, z, α, β, γ randomly would require extreme luck to get the sum of squared errors close to 0. There is a better way. Newton-Raphson have a simple way to minimize the error, but it requires finding the derivative or slope. This is easy to do in the classroom. When the sum of squared errors is very small, the derivative of the sum of squared errors is also small. A little noise from the position feedback can cause the calculations to be unstable. I am still trying different ways of avoiding the noise without sacrificing accuracy. At this time, I can calculate the x, y, z, α, β, γ so the sum of squared errors is less than 0.0001.
There is a big difference between the classroom and reality.
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