EMNG 3028 - Chapter 5: Periodic Functions & Fourier Series Notes

EMNG 3028 Power Quality & Distribution - Chapter 5: Periodic Functions & Fourier Series

Objectives

  • Understand periodic functions and their characteristics.
  • Understand Fourier Series Theory.
  • Calculate Fourier constants.

Definition of a Periodic Function

  • A function f(x)f(x) is periodic if and only if f(x+L)=f(x)f(x + L) = f(x) is true for some value of LL and for all values of xx.
  • The smallest value of LL for which the equation f(x+L)=f(x)f(x + L) = f(x) holds true for every value of xx is called the period of the function.
  • A graph of a periodic function f(x)f(x) with period LL exhibits the same pattern every LL units along the x-axis.
  • Knowing the function's behavior over one complete period allows us to sketch the graph over a wider interval containing multiple periods.
  • Examples: sinx\sin x and cosx\cos x are periodic functions with a period of 2π2\pi.

Fourier Series

  • Periodic functions frequently occur in engineering problems and can be complicated.
  • It is desirable to represent these functions in terms of simple periodic functions like sine and cosine.
  • Joseph Fourier (1768-1830) studied the development of a periodic function into a series of sines and cosines.
  • The series of sines and cosines is named after him: Fourier Series.
  • If f(x)f(x) is a periodic function with period 2π2\pi defined in (c,c+2π)(c, c + 2\pi) and satisfies Dirichlet's conditions, it can be expanded as a Fourier series.

Dirichlet Conditions

  • Dirichlet conditions (also known as the Dirichlet-Jordan test) provide sufficient conditions for a periodic function to be equal to the sum of its Fourier series.
  • These conditions ensure the convergence of the Fourier series to the original function.
Three Dirichlet Conditions:
  1. Absolute Integrability: The function f(t)f(t) must be absolutely integrable over one period. This means that the integral of the absolute value of the function over a period is finite.
  2. Bounded Variation: Within any finite interval, the function must have a finite number of maxima and minima. The function's variation over the interval is bounded.
  3. Finite Discontinuities: The function can have a finite number of discontinuities in any finite interval, but each discontinuity must be finite (not infinite).

Fourier Series Coefficients

  • The coefficients are calculated using the following formulas:
    • a<em>0=1π</em>cc+2πf(x)dxa<em>0 = \frac{1}{\pi} \int</em>{c}^{c+2\pi} f(x) dx
    • a<em>n=1π</em>cc+2πf(x)cos(nx)dxa<em>n = \frac{1}{\pi} \int</em>{c}^{c+2\pi} f(x) \cos(nx) dx
    • b<em>n=1π</em>cc+2πf(x)sin(nx)dxb<em>n = \frac{1}{\pi} \int</em>{c}^{c+2\pi} f(x) \sin(nx) dx

General Form of Fourier Series

  • f(t)=a<em>0+</em>n=1(a<em>ncos(nω</em>0t)+b<em>nsin(nω</em>0t))f(t) = a<em>0 + \sum</em>{n=1}^{\infty} (a<em>n \cos(n \omega</em>0 t) + b<em>n \sin(n \omega</em>0 t))
  • ω0=2πT\omega_0 = \frac{2\pi}{T} is the fundamental frequency in radians per second.
  • The Fourier series resolves the function into a DC component (a0a_0) and an AC component (the summation).
  • The constants a<em>0a<em>0, a</em>na</em>n, and bnb_n are called the Fourier coefficients.

Periodic Functions - Cosine and Sine

  • Cosine Function:
    • cos(nπ)={(1)namp;for all n 1amp;,n=0,4,8, 1amp;,n=2,6,10,\cos(n\pi) = \begin{cases} (-1)^n &amp; \text{for all n} \ 1 &amp; , n = 0, 4, 8, … \ -1 &amp; , n = 2, 6, 10, … \end{cases}
    • cos(nπ2)={0amp;, n odd 1amp;,n=0,4,8, 1amp;,n=2,6,10,\cos(n\frac{\pi}{2}) = \begin{cases} 0 &amp; \text{, n odd} \ 1 &amp; , n = 0, 4, 8, … \ -1 &amp; , n = 2, 6, 10, … \end{cases}
  • Sine Function:
    • sin(nπ)=0 for all n\sin(n\pi) = 0 \text{ for all n}
    • sin(nπ2)={0amp;, n even 1amp;,n=1,5,9, 1amp;,n=3,7,11,\sin(n\frac{\pi}{2}) = \begin{cases} 0 &amp; \text{, n even} \ 1 &amp; , n = 1, 5, 9, … \ -1 &amp; , n = 3, 7, 11, … \end{cases}

Forms of Periodic Waves

  • Modulation:
    • Amplitude varies in a repeating manner: Amplitude Modulation (AM).
    • Frequency varies in a repeating manner: Frequency Modulation (FM).
    • Waveform shape varies in a repeating manner: Non-sinusoidal periodic wave.

Fourier Series Theory

  • A square-wave pattern can be approximated with a sum involving a fundamental sine-wave plus a combination of harmonics of this fundamental frequency.
  • This sum is called a Fourier series.

Harmonics

  • The sinusoid sin(nω<em>0t)\sin(n\omega<em>0 t) or cos(nω</em>0t)\cos(n\omega</em>0 t) is called the nthn^{th} harmonic of f(t)f(t).
    • If nn is odd, then it's called the odd harmonic.
    • If nn is even, then it's called the even harmonic.

Requirements for Fourier Series Representation

  1. f(t)f(t) must be single-valued everywhere.
  2. It must have a finite number of finite discontinuities per period.
  3. It must have a finite number of maxima and minima per period.

Integrals Useful for Evaluating Fourier Coefficients

  • cos(at)dt=1asin(at)\int \cos(at) dt = \frac{1}{a} \sin(at)
  • sin(at)dt=1acos(at)\int \sin(at) dt = -\frac{1}{a} \cos(at)
  • tcos(at)dt=1acos(at)+tasin(at)\int t \cos(at) dt = \frac{1}{a} \cos(at) + \frac{t}{a} \sin(at)
  • tsin(at)dt=1asin(at)tacos(at)\int t \sin(at) dt = \frac{1}{a} \sin(at) - \frac{t}{a} \cos(at)

Formulas

  • To find a<em>0a<em>0: a</em>0=2T0Tf(t)dta</em>0 = \frac{2}{T} \int_{0}^{T} f(t) dt
  • To find a<em>na<em>n: a</em>n=2T<em>0Tf(t)cos(nω</em>0t)dta</em>n = \frac{2}{T} \int<em>{0}^{T} f(t) \cos(n \omega</em>0 t) dt
  • To find b<em>nb<em>n: b</em>n=2T<em>0Tf(t)sin(nω</em>0t)dtb</em>n = \frac{2}{T} \int<em>{0}^{T} f(t) \sin(n \omega</em>0 t) dt

Integrals Table

  • xndx=xn+1n+1\int x^n dx = \frac{x^{n+1}}{n+1}
  • 1xdx=lnx\int \frac{1}{x} dx = \ln |x|
  • exdx=ex\int e^x dx = e^x
  • sinxdx=cosx\int \sin x dx = -\cos x
  • cosxdx=sinx\int \cos x dx = \sin x
  • [g(x)]ng(x)dx=[g(x)]n+1n+1\int [g(x)]^n g'(x) dx = \frac{[g(x)]^{n+1}}{n+1}
  • g(x)g(x)dx=lng(x)\int \frac{g'(x)}{g(x)} dx = \ln |g(x)|
  • axdx=axlna\int a^x dx = \frac{a^x}{\ln a}
  • coshxdx=sinhx\int \cosh x dx = \sinh x
  • sinhxdx=coshx\int \sinh x dx = \cosh x
  • tanhxdx=ln(coshx)\int \tanh x dx = \ln(\cosh x)
  • cothxdx=ln(sinhx)\int \coth x dx = \ln(\sinh x)
  • tanxdx=ln(cosx)\int \tan x dx = -\ln(\cos x)
  • cotxdx=ln(sinx)\int \cot x dx = \ln(\sin x)
  • dxa2+x2=1atan1(xa)\int \frac{dx}{a^2 + x^2} = \frac{1}{a} \tan^{-1}(\frac{x}{a})
  • dxa2x2=sin1(xa)\int \frac{dx}{\sqrt{a^2 - x^2}} = \sin^{-1}(\frac{x}{a})

Example: Fourier Series Calculation

  • Function defined in (0,2π)(0, 2\pi).
  • f(x)={x,amp;0lt;xlt;π π,amp;πlt;xlt;2πf(x) = \begin{cases} x, &amp; 0 &lt; x &lt; \pi \ \pi, &amp; \pi &lt; x &lt; 2\pi \end{cases}
  1. Calculate a0a_0:
    • a<em>0=12π</em>02πf(x)dx=12π[<em>0πxdx+</em>π2ππdx]a<em>0 = \frac{1}{2\pi} \int</em>{0}^{2\pi} f(x) dx = \frac{1}{2\pi} \left[ \int<em>{0}^{\pi} x dx + \int</em>{\pi}^{2\pi} \pi dx \right]
    • a0=12π[π22+π2]=3π4a_0 = \frac{1}{2 \pi} \left[ \frac{\pi^2}{2} + \pi^2 \right] = \frac{3\pi}{4}
  2. Calculate ana_n:
    • a<em>n=1π</em>02πf(x)cos(nx)dx=1π[<em>0πxcos(nx)dx+</em>π2ππcos(nx)dx]a<em>n = \frac{1}{\pi} \int</em>{0}^{2\pi} f(x) \cos(nx) dx = \frac{1}{\pi} \left[ \int<em>{0}^{\pi} x \cos(nx) dx + \int</em>{\pi}^{2\pi} \pi \cos(nx) dx \right]
    • an=1π[cos(nπ)1n2+sin(2nπ)sin(nπ)n]=cos(nπ)1πn2a_n = \frac{1}{\pi} \left[ \frac{\cos(n \pi) - 1}{n^2} + \frac{\sin(2n\pi) - \sin(n\pi)}{n} \right] = \frac{\cos(n \pi) - 1}{\pi n^2}
    • an={0amp;, n even 2πn2amp;, n odda_n = \begin{cases} 0 &amp; \text{, n even} \ -\frac{2}{\pi n^2} &amp; \text{, n odd} \end{cases}
  3. Calculate bnb_n:
    • b<em>n=1π</em>02πf(x)sin(nx)dx=1π[<em>0πxsin(nx)dx+</em>π2ππsin(nx)dx]b<em>n = \frac{1}{\pi} \int</em>{0}^{2\pi} f(x) \sin(nx) dx = \frac{1}{\pi} \left[ \int<em>{0}^{\pi} x \sin(nx) dx + \int</em>{\pi}^{2\pi} \pi \sin(nx) dx \right]
    • b<em>n=1π[πcos(nπ)n+sin(nπ)n2(cos(2nπ)cos(nπ))πn]b<em>n = \frac{1}{\pi} \left[ \frac{\pi \cos(n \pi)}{n} + \frac{\sin(n\pi)}{n^2} - \frac{(\cos(2n\pi) - \cos(n\pi))\pi}{n} \right]b</em>n=1(1)nnb</em>n = \frac{1 - (-1)^n}{n}
  4. Final Fourier Series:
    • f(x)=3π4+<em>n=1[a</em>ncos(nx)+bnsin(nx)]f(x) = \frac{3\pi}{4} + \sum<em>{n=1}^{\infty} \left[ a</em>n \cos(nx) + b_n \sin(nx) \right]
    • Where a<em>0=3π2a<em>0 = \frac{3 \pi}{2}, a</em>n=0a</em>n = 0, (n even), a<em>n=2πn2a<em>n = -\frac{2}{\pi n^2}, (n odd), and b</em>n=1(1)nnb</em>n = \frac{1 - (-1)^n}{n}

Amplitude Modulation (AM)

  • Amplitude varies with time.
  • Includes a carrier frequency plus sidebands.

Frequency Modulation (FM)

  • Frequency varies with time.
  • Modulation determines the number of sidebands.

Non-sinusoidal Periodic Waves

  • Examples: Sawtooth wave, Square wave, Triangular wave.
  • Consist of harmonic series with varying amplitudes and frequencies.