2.160 : Identification, Estimation, and Learning
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Spring 2006

Prerequisite                      2.151 or similar subject

Instructor in charge           Professor H. Harry Asada

Ford Professor of Mechanical Engineering

asada@mit.edu, Room 3-346, x3-6257

                                        Office Hours     Monday and Wednesday, 2:30 pm ~ 3:00 pm, Tuesday 4:00 pm ~ 5:00 pm

Course Secretary               Amy Shea, amyshea@mit.edu , Room 3-348, x3-2204

Class                                Monday and Wednesday, 1:00 pm ~ 2:30 pm, Room 1-273

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Course Materials

 Lecture1       Lecture2        Lecture3      Lecture4     Lecture5

 Lecture6       Lecture7       Lecture8        Lecture9    Lecture10

 Lecture11    Lecture12     Lecture13     Lecture14  Lecture15

 Lecture16      Lecture17     Lecture18    Lecture19  Lecture20

 Lecture21     Lecture22(complete)      Lecture23(complete)      Lecture24(complete)   Lecture25(complete)

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PS 1    (Solution)

Use the following data files for Problem 3

Data:  The true thetas are given so that you can compare your RLS results with the true values. 

1.Test data:   input   output  Theta=[5 -2 3]¡¯

  Test data is used for you to test your code.

2.Data for the questions

   a)  input(u)    output(y)  theta_1   theta_2  theta_3

b)      input(u)    output(y)  theta_1   theta_2  theta_3

PS 2   (Solution)

Use the following data files for Problem 3

-If you have any questions on how to use the files, please contact Levi Wood (woodl@mit.edu

Reference ¡°Good¡± Signal

Data Set 1

Corrupted Data      Noise Reference

Data Set 2

Corrupted Data       Noise Reference

Notes:

1) Relationship between file names and labels in Figure 2 of Problem Set 3 

        File Names           Figure 2 Labels

       ¡°GoodPPG¡±                            yo

       ¡°CorruptedPPG¡±                        y

       ¡°acceleration¡±                        a  

2) There is one ¡°GoodPPG¡± reference signal that can be used to compare your      

     ¡°recovered¡± signals, z, with for both data sets. 

3) One of the data sets is ¡°tricky.¡± Can you explain why you are getting strange results? 

4) How do you think you should choose the filter order? 

5) Levi Wood will be available to help you on Monday and Tuesday

       Office Hours: room 3-351  Monday, Feb 27th 4-5pm

                                   Tuesday, Feb 28th 4-5pm

                              By Appointment: woodl@mit.edu

                     Also feel free to ask questions by email.

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 PS 3    (Solution)

     At = [0.8500    0.1500    0.0500; 0.0500    0.7000     0; 0.0500   -0.0500    0.7500]

     Bt = [10.0000;0;14.2103]

     Gt = [1;1;1]

     Ht = [1 0 0]

     Rt = 2.9862

     Qt = 1.0129

     input(u)   output(y)

     The actual X1(dTe)   X2(dTw)   X3(dL2) are given for comparison with the results estimated from the Kalman Filter.

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PS 4    (Solution)

PS 5    (Solution)

   All the data was derived from a yorkshire swine using a sampling rate of 100 Hz.

   The input data (AorticFlowInput.txt) was measured in the root of the ascending aorta just outside the heart

   and the output blood pressure data (BloodPressureOutput.txt) was measure in the radial artery (in the lower arm).

   Standard units were used in collecting this physiological data.

   The units for aortic flow are liters/minute and for blood pressure are millimeters of mercury (mmHg).

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   PS 6    PS 7    PS 8