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Let s start with the number 10 This is 101 When we divide 10 by itself, we get 100, which is 1 When we divide 10 by itself twice, we get 10 1, which is 01 It goes on like this for negative integer powers: 10 divided by itself three times is 10 2, which is 1/102 or 001 10 divided by itself four times is 10 3, which is 1/103 or 0001 10 divided by itself five times is 10 4, which is 1/104 or 00001 and so on, as far as we want!

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the variance predicted by P Analysis of residual sequences is one of the best methods to detect model de ciencies In doing so, the analyst should keep in mind that Hk Pk Hk + Rk is predicting the variance of the residual rk over an ensemble of experiments Therefore, for example, the residual sequence of Figure 67 does indicate a model de ciency, but by itself does not indicate that the residual is biased If the experiment was repeated N times, with the residual sequence from the i-th trial run denoted by rki , and all residual sequences tended to drift in the same direction, then the analyst might reconsider the system model to nd the cause of and model the bias AlterN natively, if the average of the residual sequences rk = i=1 rki is essentially zero mean, but the ensemble of residual sequences is not well-modeled by the P , then the analyst must consider possible alternative explanations To illustrate the nature of a residual sequence for a lter designed with a correct model, Figure 68 shows the residual for the lter designed with Qh = 05 The residual is essentially zero mean, has no noticeable trends, and has steady-state variance that closely matches the P

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8

The main references for the presentation of this chapter were [58, 93]

CSGNetworkCom 6/4/92

Question 8-1

Figure 68: Residual sequence from a single trial for the lter designed with Qh = 05 The solid line with x s is the residual The solid lines without x s is the lters predicted values for r where r = H P H + R

Suppose we start with 7 and raise it to the 1st power, then the 2nd power, then the 3rd power, then the 4th power, then the 5th power, and so on, endlessly What happens to the result

Exercise 61 This example is intended to motivate the importance of having an accurate design model Let the actual system dynamics (ie, eqn (61)) be x y = = 0 2 n 1 0 1 0 x+ 0 1 nx

Value 15 pF 33 pF 10 pF 15 pF 20 pF 30 pF 33 pF 47 pF 56 pF 68 pF 75 pF 82 pF 91 pF 100 pF 120 pF 130 pF 150 pF 180 pF 220 pF 330 pF 470 pF 560 pF 680 pF 750 pF 820 pF

Answer 8-1

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We get a sequence of fractions that converges toward 0 It starts at 1/7, and then keeps getting 1/7 as large with each succeeding power Here s what happens: 7 1 = 1/7 7 2 = 1/72 = 1/49 7 3 = 1/73 = 1/343 7 4 = 1/74 = 1/2,401 7 5 = 1/75 = 1/16,807 and so on, forever

2 2 where nx N (0, x ), ny N (0, y ), and x(0) N (0, I) Assume that the estimator design model is based on the assumption that n is zero, so that eqn (63) is

164 Review Questions and Answers Question 8-2

Type Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic Ceramic

0 1 0 0 1 0

Answer 8-2

The aiding measurements y are available at 10 Hz Perform a covariance analysis using x = 001 and y = 100 1 For n = 0 (ie, the design model is correct), note the approximate time at which steady-state performance is achieved and the steadystate prior and posterior state estimation error standard deviation 2 Repeat the simulation for values of n [0, 01] Let the simulation run for approximately 1000 s Is a steady-state performance achieved

We must be sure that the expression is not equal to 0, and can never attain a value of 0 Otherwise, we ll end up dividing by 0 That s forbidden!

Value 1,000 pF /001 F 1,500 pF /0015 F 2,000 pF /002 F 2,200 pF /0022 F 4,700 pF /0047 F 5,000 pF /005 F 5,600 pF /0056 F 6,800 pF /0068 F 01 015 02 022 033

Question 8-3

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