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Merged
merged 2 commits into from
Feb 7, 2022
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make numbers and matrices work as systems in freqresp and friends #630

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3f89cb0
make numbers and matrices work as systems for freqresp
baggepinnen Feb 7, 2022
de41625
Update freqresp.jl
baggepinnen Feb 7, 2022
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1 change: 1 addition & 0 deletions src/analysis.jl
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Expand Up @@ -101,6 +101,7 @@ the stability region of the complex plane.
function dcgain(sys::LTISystem, ϵ=0)
return iscontinuous(sys) ? evalfr(sys, -ϵ) : evalfr(sys, exp(-ϵ*sys.Ts))
end
dcgain(G::Union{UniformScaling, Number, AbstractMatrix}) = G

"""
markovparam(sys, n)
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14 changes: 13 additions & 1 deletion src/freqresp.jl
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Expand Up @@ -8,12 +8,14 @@ function freqresp(sys::LTISystem, w::Real)
evalfr(sys, s)
end

freqresp(G::Union{UniformScaling, AbstractMatrix, Number}, w::Real) = G

"""
sys_fr = freqresp(sys, w)

Evaluate the frequency response of a linear system

`w -> C*((iw*im -A)^-1)*B + D`
`w -> C*((iw*im*I - A)^-1)*B + D`
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@albheim albheim Feb 7, 2022

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I was more thinking of the w -> ... iw ... in my comment, I assume this should be w->...w...? I added the I since I thought maybe that is where the iw came from?

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@albheim albheim Feb 7, 2022

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But yeah, not really related (and not very important) so can fix it some other time.


of system `sys` over the frequency vector `w`.
"""
Expand All @@ -23,6 +25,14 @@ of system `sys` over the frequency vector `w`.
[evalfr(sys[i,j], _freq(w, te))[] for w in w_vec, i in 1:ny, j in 1:nu]
end

@autovec () function freqresp(G::AbstractMatrix, w_vec::AbstractVector{<:Real})
repeat(G, 1, 1, length(w_vec))
end

@autovec () function freqresp(G::Number, w_vec::AbstractVector{<:Real})
fill(G, 1, 1, length(w_vec))
end

_freq(w, ::Continuous) = complex(0, w)
_freq(w, te::Discrete) = cis(w*te.Ts)

Expand Down Expand Up @@ -121,6 +131,8 @@ function evalfr(G::TransferFunction{<:TimeEvolution,<:SisoTf}, s::Number)
map(m -> evalfr(m,s), G.matrix)
end

evalfr(G::Union{UniformScaling, AbstractMatrix, Number}, s) = G

"""
`F(s)`, `F(omega, true)`, `F(z, false)`

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2 changes: 1 addition & 1 deletion src/matrix_comps.jl
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Expand Up @@ -637,7 +637,7 @@ end
Return the observer_predictor system
x̂' = (A - KC)x̂ + (B-KD)u + Ky
ŷ = Cx + Du
with the input equation [B K] * [u; y]
with the input equation [B-KD K] * [u; y]

If covariance matrices `R1, R2` are given, the kalman gain `K` is calculaded.

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7 changes: 7 additions & 0 deletions test/test_freqresp.jl
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Expand Up @@ -34,6 +34,13 @@ resp1 = ones(ComplexF64, length(w), 1, 1)
@test freqresp(G1, w) == resp1
@test freqresp(H1, w) == resp1

for G in [2, 2I, 2I(2), randn(2,2)]
@test dcgain(G) == G
!(G isa UniformScaling) && @test freqresp(G, [1,2]) == cat(G,G, dims=3) # I does not have size
@test freqresp(G, 1) == G
@test evalfr(G, 1im) == G
end

## First order system

sys2 = ss(-1, 1, 1, 1)
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