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Manually Installing Intel's Graphics Drivers in Ubuntu 13.04

Intel’s graphics installer didn’t work for me in 13.04 (as shown below)... However I was able to find out how to install these same drivers from the command line.  
Install the Intel Driver Update Utility Run the utility and you’ll get the error. The utility loads a file that defines the packages that need to be installed in the home directory. Open the file named “.ilg-config” in a text editor . Scroll until you find the most recent distribution.. in my case 12.10.  We see this file gives the source and all of the packages to be installed. So now we have to add the source either by adding it to /etc/apt/sources.list or from the gui add it like so:
Then do an update of the sources (sudo apt-get update) Now install all of the packages listed, for me it was:
sudo apt-get install libcairo2 libcairo-gobject2 libcairo-script-interpreter2 libdrm2 libdrm-intel1 libkms1 libva1 libva-x11-1 libva-glx1 libva-tpi1 libva-egl1 vainfo libxatracker1 libgbm1 libegl1-mesa libegl1-mesa-drivers libopenvg1-mesa…

Control Systems in Python - Phase Lag Compensator Design

Here's a problem I had to do for homework. Some of the equation formatting didn't copy over, sorry...

Given an system G(s) = 10/(s(s+4)) and it’s open loop bode plots, design an appropriate compensator so that the closed loop phase margin is at least 45o and the velocity constant is 50. The bode plot shows that the PM for the open loop system is 64.2o at ω = 1.931rad/s, at the same frequency, we see that the P.M. of the closed loop system is 129o. The velocity constant indicates the steady state error to a ramp input must be ess =1/Kv = 1/50 = 0.02.  First, the velocity constant of the uncompensated system is:
Kv=limit as s->0 of sG(s) =limit as s->0 of s10/s(s+4)=10/4=2.5
since we want Kv  50, the compensator must have a gain of at least 50/2.5 = 20.  
If our compensator Gc(s) = Kc = 20, we get the following new responses by simply shifting the open loop bode up by about 26dB. Thus the new open loop 0dB crossing is at  ω = 13.83 rad/s and the open and closed loop phase mar…

Control Systems in Python - Part 3 - Root Locus Plots

In this post we can see how to make root locus plots in python. This requires the setup from part 1.

The problem is from Dorf's modern control systems AP 10.1. A three-axis pick-and-place application requires the precise movement of a robotic arm in three-dimensional space. The overshoot for a step input should be less than 13%.
a) Let Gc(s) = K, and determine the gain K that satisfies the requirement. Determine the resulting settling time (with a 2% criterion). First we compute the Routh Hurwitz table to determine the valid
range of K.

We see 0<K<20 so If we let K = 2, then the step response becomes:
which shows the settling time is 8.68 seconds and overshoot is less than 13%.

b) Use a lead network and reduce the settling time to less than 3 seconds. Since we are dealing with time response parameters the root-locus method will be used.

The new controller is:

the overshoot and settling time criteria lead to a damping ratio of 0.545 or more and the real part of the dominant pole…

Fix Pithos not playing an not showing any error

So for some reason my Pithos wasn't working for the past two weeks, it would simply open and not load any songs, show a blank window, and not give any errors. This is how I *fixed* it:

1. Remove it and purge all user settings

sudo apt-get purge pithos

2. Reinstall

sudo apt-get install pithos


And wala!

I'm not sure why, but it worked!

Control Systems in Python - Part 2 - Routh Hurwitz

In my last post Control Systems in Python Part 1, i described how to setup and use Python for doing some basic plotting of transfer functions. One of the biggest benefits of using sympy vs numeric packages like matlab/numpy/scipy is the fact that you can use symbolic variables. This post includes a function for computing the Routh Hurwitz table (Note: It does not work for row's of zeros).


Lets do my control systems design homework problem together :) (Warning: I have not verified if this answer is right so please correct me if it’s not!)

The Problem

The problem is DP 9.11 from Dorf & Bishop’s Modern Control Systems. ISBN 0136024580. Basically we have to design a controller to compensate for a system with a time delay.
The controller is:


And the system is:



First we approximate the exponential term with a 2nd order polynomial using pade(0.4,2) such that:

Thus the approximated system is:



Using frequency response methods, design the controller so that the overshoot of the sy…

Control Systems in Python - Part 1 - Bode and Step Response

I hate matlab with passion, yet sadly, nearly everyone uses it.  I'm a fan of Python and open source stuff so here's a simple article on how to do some common control systems stuff in Python.

First we need to make sure the environment is setup.
Install IPython (or you can use any other python shell, but a unicode supported shell is preferred)Install python-control (numpy, scipy)Install sympy
These should do if your on Ubuntu/debian:

sudo apt-get install python-sympy python-numpy python-scipy python-matplotlib ipython
Then you need to install python control, see How to download and install python-control
Intro to using SympyOpen ipython and run the following:

import sympy from sympy import * sympy.init_printing() s = Symbol('s')

Now we can do things like define transfer functions using the symbolic variable s.


We can expand the bottom using the .simplify() method

and we can do something more complex like...
which is really nice because it does all the multiplication for us... and it’…