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Unformatted text preview: MIT OpenCourseWare http://ocw.mit.edu 2.161 Signal Processing: Continuous and Discrete
Fall Term 2008 Lecture 21
Reading: Class handout: Convolution Class handout: Sinusoidal Frequency Response 1 Continuous LTI System Time-Domain Response A continuous linear filter is a LTI dynamical system (described by an ODE with constant coefficients). We are interested in the input-output relationships and seek a method of determining the response y(t) to a given input u(t).
u (t) t u (t) in p u t L T I F ilte r y (t) = ? o u tp u t s y s te m is a t r e s t a t t= 0 The relationship is developed as follows (see the handout for a detailed explanation) The input u(t) is approximated as a zero-order (staircase) waveform uT (t) with intervals ~ T. uT (t) = u(nT ) ~ for nT t < (n + 1)T. The approximation uT (t) is written as a superposition of non-overlapping pulses ~ uT (t) = ~
1 pn (t) copyright c D.Rowell 2008 21 where pn (t) = u(nT ) 0 nT t < (n + 1)T otherwise For example, p3 (t) is shown cross-hatched in the figure above. Each component pulse pn (t) is written in terms of a delayed unit pulse T (t), of width T and amplitude 1/T that is: pn (t) = u(nT )T (t - nT )T so that uT (t) = ~
n=- u(nT )T (t - nT )T. Assume that the system response to an input T (t) is a known function, and is desig nated hT (t) as shown below. If the system is linear and time-invariant, the response to a delayed unit pulse, occurring at time nT is simply a delayed version of the pulse response: yn (t) = hT (t - nT )
@ T( t- n T ) 1 / T y n ( t )
@ T( t- n T ) s y s te m y n ( t ) 0 t 0 0 n T ( n + 1 ) T t 0 n T (n + 1 )T The principle of superposition allows the total system response to uT (t) to be written ~ as the sum of the responses to all of the component weighted pulses: yT (t) = ~
n=- u(nT )hT (t - nT )T For causal systems the pulse response hT (t) is zero for time t < 0, and future com ponents of the input do not contribute to the sum, so that the upper limit of the summation may be rewritten:
N yT (t) = ~
n=- u(nT )hT (t - nT )T for N T t < (N + 1)T. 22 We now let the pulse width T become very small, and write nT = , T = d , and note that limT 0 T (t) = (t). As T 0 the summation becomes an integral and
N y(t) = lim
t T 0 u(nT )hT (t - nT )T
- u( )h(t - )d (1) where h(t) is defined to be the system impulse response, h(t) = lim hT (t).
T 0 Equation (??) is an important integral in the study of linear systems and is known as the convolution or superposition integral. It states that the system is entirely characterized by its response to an impulse function (t), in the sense that the forced response to any arbitrary input u(t) may be computed from knowledge of the impulse response alone. The convolution operation is often written using the symbol : y(t) = u(t) h(t) =
t - u( )h(t - )d. (2) Equation (??) is in the form of a linear operator, in that it transforms, or maps, an input function to an output function through a linear operation.
u (t) c o n v o lu tio n t u (t) in p u t L T I F ilte r h (t) y ( t ) = u ( t ) OX h ( t ) o u tp u t The form of the integral in Eq. (??) is difficult to interpret because it contains the term h(t - ) in which the variable of integration has been negated. The steps implicitly involved in computing the convolution integral may be demonstrated graphically below. The impulse response h( ) is reflected about the origin to create h(- ), and then shifted to the right by t to form h(t - ). The product u(t)h(t - ) is then evaluated and integrated to find the response. This graphical representation is useful for defining the limits necessary in the integration. For example, since for a physical system the impulse response h(t) is zero for all t < 0, the reflected and shifted impulse response h(t - ) will be zero for all time > t. The upper limit in the integral is then at most t. If in addition the input u(t) is time limited, that is u(t) 0 for t < t1 and t > t2 , the limits are: t u( )h(t - )d for t < t2 t1 yf (t) = (3) t2 u( )h(t - )d for t t2
t1 23 See the class handout for further details and examples. 24 2 Sinusoidal Response of LTI Continuous Systems Of particular interest is the response of an LTI continuous system to sinusoidal inputs of the form u(t) = A sin(t + ), where A is the amplitude, is the angular frequency (rad/s), and is a phase angle (rad). (We note that we can also write u(t) = A sin(2F t + ), where F is the frequency in Hz.) We begin by noting that a sinusoid may be expressed in terms of complex exponentials through the Euler formulas: 1 jt e - e-jt 2j 1 jt e + e-jt cos(t) = 2 sin(t) = and first finding the steady-state solution to inputs of the form u(t) = ejt . Let the LTI system be described by an ODE of the form an dn y dn-1 y dy dm u dm-1 u du + an-1 n-1 + + a1 + a0 y = bm n + bm-1 m-1 + + b1 + b0 u. n dt dt dt dt dt dt The steady-state response of the system (after all initial condition transients have decayed) may be found using the method of undetermined coefficients, in which a form of the solution is assumed and solved for a set of coefficients. In particular, if the input is u(t) = ejt , assume that y(t) = Bejt . Substitution into the differential equation gives an (j)n + an-1 (j)n-1 + + a1 (j) + a0 Bejt = bm (j)m + bn-1 (j)m-1 + + b1 (j) + b0 ejt and solving for B B= so that where H(j) = an (j)n + an-1 (j)n-1 + + a1 (j) + a0 bm (j)m + bn-1 (j)m-1 + + b1 (j) + b0 y(t) = H(j)ejt N (j) an (j)n + an-1 (j)n-1 + + a1 (j) + a0 = D(j) bm (j)m + bn-1 (j)m-1 + + b1 (j) + b0 H(j) is defined to be the frequency response function, and N (j) and D(j) are the numerator and denominator polynomials respectively. We note the following: The output y(t) is simply a (multiplicatively) weighted version of the input. H(j) is a property of the system. It is defined entirely by the describing differential equation. 25 H(j) is, in general, complex. Even powers of n and m in N (s) and D(s) will generate real terms in the polynomials, while odd powers will generate imaginary terms. |H(j)| = |N (j)| |D(j)| H(j) = N (j) - D(j) H(-j) = H(j), where H(j) is the complex conjugate. The response to the real sinusoid u(t) = A sin (t + ) = A j(t+) - e-j(t+) e 2j may be found from the principle of superposition by summing the response to each compo nent: y(t) = A 2j A = 2j H(j)ej(t+) - H(-j)e-j(t+) H(j)ej(t+) - H(j)e-j(t+) Combining the real and imaginary parts gives the result y(t) = A |H(j)| sin (t + + H(j)) where |H(j)| is the magnitude of the frequency response function, and H(j) is the phase response. The response to a real sinusoid is therefore a sinusoid of the same frequency as the input. The amplitude of the response at an input frequency of has been modified by a factor |H(j)|. If |H(j)| > 1 the input has been amplified by the system, if |H(j)| < 1, the signal has been attenuated. The system has imposed a frequency dependent phase shift H(j) on the response. Example 1
A first-order passive RC filter with the following circuit diagram
R + V
in (t) - C v
o (t) 26 is described by the differential equation dvo + vo = Vin (t) dt Find the frequency response function. RC By inspection H(j) = and |H(j)| = H(j) = |1| = |1 + jRC| 1 (RC)2 + 1 (1) - (1 + jRC) = 0 - tan-1 (RC) 1 jRC + 1 Clearly, as 0, |H(j)| 1, and H(j) 0 rad. As , |H(j)| 0, and H(j) -/2 rad (-90 ). This is a low-pass filter, in that it passes low frequency sinusoids while attenuating high frequencies. Example 2
A new first-order passive RC filter is formed by exchanging the resistor and capacitor in the previous example:
C + V
in (t) - R v
o (t) and is now described by the differential equation dvo dVin + vo = RC dt dt Find the frequency response function. RC By inspection H(j) = and |H(j)| = H(j) = |jRC| = |1 + jRC| RC (RC)2 + 1 (jRC) - (1 + jRC) = - tan-1 (RC) 2 27 jRC jRC + 1 Clearly, as 0, |H(j)| 0, and H(j) /2 rad (90 ). As , |H(j)| 1, and H(j) 0 rad (0 ). This is a high-pass filter, in that it attenuates low frequency sinusoids while passing high frequencies. 28 ...
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This note was uploaded on 02/27/2012 for the course MECHANICAL 2.161 taught by Professor Derekrowell during the Fall '08 term at MIT.
- Fall '08