bandPassReturn band pass filter roots as needed for block for given cut-off frequency |
This information is part of the Modelica Standard Library maintained by the Modelica Association.
The goal is to implement the filter in the following form:
// complex conjugate poles: der(x1) = a*x1 - b*x2 + ku*u; der(x2) = b*x1 + a*x2; y = k1*x1 + k2*x2; ku = (a^2 + b^2)/b k1 = cn/ku k2 = cn*a/(b*ku)
This representation has the following transfer function:
// complex conjugate poles s*x2 = a*x2 + b*x1 s*x1 = -b*x2 + a*x1 + ku*u or (s-a)*x2 = b*x1 -> x2 = b/(s-a)*x1 (s + b^2/(s-a) - a)*x1 = ku*u -> (s(s-a) + b^2 - a*(s-a))*x1 = ku*(s-a)*u -> (s^2 - 2*a*s + a^2 + b^2)*x1 = ku*(s-a)*u or x1 = ku*(s-a)/(s^2 - 2*a*s + a^2 + b^2)*u x2 = b/(s-a)*ku*(s-a)/(s^2 - 2*a*s + a^2 + b^2)*u = b*ku/(s^2 - 2*a*s + a^2 + b^2)*u y = k1*x1 + k2*x2 = (k1*ku*(s-a) + k2*b*ku) / (s^2 - 2*a*s + a^2 + b^2)*u = (k1*ku*s + k2*b*ku - k1*ku*a) / (s^2 - 2*a*s + a^2 + b^2)*u = (cn*s + cn*a - cn*a) / (s^2 - 2*a*s + a^2 + b^2)*u = cn*s / (s^2 - 2*a*s + a^2 + b^2)*u comparing coefficients with y = cn*s / (s^2 + c1*s + c0)*u -> a = -c1/2 b = sqrt(c0 - a^2) comparing with eigenvalue representation: (s - (a+jb))*(s - (a-jb)) = s^2 -2*a*s + a^2 + b^2 shows that: a: real part of eigenvalue b: imaginary part of eigenvalue
cr_in |
Type: Real[:] Description: Coefficients of real poles of base filter |
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c0_in |
Type: Real[:] Description: Coefficients of s^0 term of base filter if conjugate complex pole |
c1_in |
Type: Real[size(c0_in, 1)] Description: Coefficients of s^1 term of base filter if conjugate complex pole |
f_min |
Type: Frequency (Hz) Description: Band of band pass filter is f_min (A=-3db) .. f_max (A=-3db) |
f_max |
Type: Frequency (Hz) Description: Upper band frequency |
a |
Type: Real[size(cr_in, 1) + 2 * size(c0_in, 1)] Description: Real parts of complex conjugate eigenvalues |
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b |
Type: Real[size(cr_in, 1) + 2 * size(c0_in, 1)] Description: Imaginary parts of complex conjugate eigenvalues |
ku |
Type: Real[size(cr_in, 1) + 2 * size(c0_in, 1)] Description: Gains of input terms |
k1 |
Type: Real[size(cr_in, 1) + 2 * size(c0_in, 1)] Description: Gains of y = k1*x1 + k2*x |
k2 |
Type: Real[size(cr_in, 1) + 2 * size(c0_in, 1)] Description: Gains of y = k1*x1 + k2*x |