Consider a feedback-based causal LTI system with input x(t) shown in Figure 6.41, where G(s) is the transfer function of a "loop filter" and 1/s is an integrator. The idea is to use the error e(t) to drive these, so as to make y(t) track x(t). (a) Find the transfer functions H(s) = X(s) and He(s): E(s) = X(s)* (b) Now set G(s) = 10. This is termed "proportional feedback," where the feedback is propor- tional to the error. (i) Find y(t) and e(t) for x(t) = sin 10t. (ii) How do your answers change (provide a qualitative discussion) for x(t): sin 100t? = sint and x(t): (iii) For x(t) = u(t) (unit step), find and sketch y(t) and e(t), and specify their asymptotic values as t∞. (iv) For x(t) = tu(t) (ramp starting at time zero), find the asymptotic value of the error e(t) as t → ∞. Hint: You can simply use the final value theorem in (iii). (c) Redo (b)(iv) for G(s) = 10+½½ ("proportional plus integral" feedback).

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x(t) —
e(t)
G(s)
y(t)
1/s
Transcribed Image Text:x(t) — e(t) G(s) y(t) 1/s
Consider a feedback-based causal LTI system with input x(t) shown in Figure
6.41, where G(s) is the transfer function of a "loop filter" and 1/s is an integrator. The idea is
to use the error e(t) to drive these, so as to make y(t) track x(t).
(a) Find the transfer functions H(s) =
Y(s)
X(s)
and He(s)
=
E(s)
X(s)*
(b) Now set G(s) = 10. This is termed "proportional feedback,” where the feedback is propor-
tional to the error.
(i) Find y(t) and e(t) for x(t) = sin 10t.
(ii) How do your answers change (provide a qualitative discussion) for x(t) = sint and x(t) =
sin 100t?
=
(iii) For x(t) = u(t) (unit step), find and sketch y(t) and e(t), and specify their asymptotic values
as t∞.
(iv) For x(t) = tu(t) (ramp starting at time zero), find the asymptotic value of the error e(t) as
t → ∞.
Hint: You can simply use the final value theorem in (iii).
(c) Redo (b)(iv) for G(s) = 10 + ½ (“proportional plus integral" feedback).
S
Transcribed Image Text:Consider a feedback-based causal LTI system with input x(t) shown in Figure 6.41, where G(s) is the transfer function of a "loop filter" and 1/s is an integrator. The idea is to use the error e(t) to drive these, so as to make y(t) track x(t). (a) Find the transfer functions H(s) = Y(s) X(s) and He(s) = E(s) X(s)* (b) Now set G(s) = 10. This is termed "proportional feedback,” where the feedback is propor- tional to the error. (i) Find y(t) and e(t) for x(t) = sin 10t. (ii) How do your answers change (provide a qualitative discussion) for x(t) = sint and x(t) = sin 100t? = (iii) For x(t) = u(t) (unit step), find and sketch y(t) and e(t), and specify their asymptotic values as t∞. (iv) For x(t) = tu(t) (ramp starting at time zero), find the asymptotic value of the error e(t) as t → ∞. Hint: You can simply use the final value theorem in (iii). (c) Redo (b)(iv) for G(s) = 10 + ½ (“proportional plus integral" feedback). S
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for your answer for part b ii what happened to x(j10)? sin10t should be equal to =10/s^2+100, since its the laplace transform. i need more explaination on the y(t) answer too. how did the angle become sin? i am so confused on your answer

Consider a feedback-based causal LTI system with input x(t) shown in Figure
6.41, where G(s) is the transfer function of a "loop filter" and 1/s is an integrator. The idea is
to use the error e(t) to drive these, so as to make y(t) track x(t).
(a) Find the transfer functions H(s) =
Y(s)
X(s)
and He(s) =
=
E(s)
X(s)*
(b) Now set G(s) = 10. This is termed “proportional feedback," where the feedback is propor-
tional to the error.
(i) Find y(t) and e(t) for x(t)
sin 10t.
(ii) How do your answers change (provide a qualitative discussion) for x(t)
sin 100t?
=
sint and x(t)
(iii) For x(t) = u(t) (unit step), find and sketch y(t) and e(t), and specify their asymptotic values
as t∞.
(iv) For x(t) = tu(t) (ramp starting at time zero), find the asymptotic value of the error e(t) as
t → ∞.
Hint: You can simply use the final value theorem in (iii).
(c) Redo (b)(iv) for G(s) = 10+ 2/3 ("proportional plus integral" feedback).
Transcribed Image Text:Consider a feedback-based causal LTI system with input x(t) shown in Figure 6.41, where G(s) is the transfer function of a "loop filter" and 1/s is an integrator. The idea is to use the error e(t) to drive these, so as to make y(t) track x(t). (a) Find the transfer functions H(s) = Y(s) X(s) and He(s) = = E(s) X(s)* (b) Now set G(s) = 10. This is termed “proportional feedback," where the feedback is propor- tional to the error. (i) Find y(t) and e(t) for x(t) sin 10t. (ii) How do your answers change (provide a qualitative discussion) for x(t) sin 100t? = sint and x(t) (iii) For x(t) = u(t) (unit step), find and sketch y(t) and e(t), and specify their asymptotic values as t∞. (iv) For x(t) = tu(t) (ramp starting at time zero), find the asymptotic value of the error e(t) as t → ∞. Hint: You can simply use the final value theorem in (iii). (c) Redo (b)(iv) for G(s) = 10+ 2/3 ("proportional plus integral" feedback).
The input signal is given by,
x(t)=sin(10t).
Its angular frequency is w = 10 rad/s.
The corresponding output and error signals in frequency domain are
Y(j10)=H(10) X(10)
1
=
Z-tan
1(100) × 1
×120°,
102+100
=
·Z-45°;
√2
E(j10) = H¸(j10)·X(j10)
1
√10²+100
1
= - 45°.
√2
In time-domain,
[90°-tan-1 (100)] × 120°,
1
y(t)=
sin(10t―45º),
√2
e(t) =
sin(10t+45°).
√2
Transcribed Image Text:The input signal is given by, x(t)=sin(10t). Its angular frequency is w = 10 rad/s. The corresponding output and error signals in frequency domain are Y(j10)=H(10) X(10) 1 = Z-tan 1(100) × 1 ×120°, 102+100 = ·Z-45°; √2 E(j10) = H¸(j10)·X(j10) 1 √10²+100 1 = - 45°. √2 In time-domain, [90°-tan-1 (100)] × 120°, 1 y(t)= sin(10t―45º), √2 e(t) = sin(10t+45°). √2
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