1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
|
function varargout = stepest(varargin)
// Estimate step response and plot of idpoly type model
//
// Calling Sequence
// stepest(sys)
// stepData = stepest(sys,flag)
// Parameters
// sys : idpoly type polynomial
// flag : boolean type variable,default value is false(%F)
// stepData : stores step response if the flag value is true
// Description
// stepest function estimate and plot the impulse response of idpoly type function.
// Examples
// a = [1 0.2];b = [0 0.2 0.3];
// sys = idpoly(a,b,'Ts',0.1)
// stepest(sys);
//
// Examples
// a = [1 0.2];b = [0 0.2 0.3];
// sys = idpoly(a,b,'Ts',0.1)
// flag = %T
// stepData = stepest(sys,flag)
// Authors
// Ashutosh Kumar Bhargava
[lhs,rhs] = argn(0)
// checking the number of inputs
if rhs > 2 then
error(msprintf(gettext("%s: Unexpected number of input arguments "),"stepest"))
end
modelData = varargin(1)
if typeof(modelData) <> "idpoly" then
error(msprintf(gettext("%s: Plant model must be ""idpoly"" type. "),"stepest"))
end
// adding noise
if rhs == 2 then
noiseFlag = varargin(2)
if typeof(noiseFlag) <> 'boolean' then
error(msprintf(gettext("%s: Last input data must be ""boolean"".type "),"stepest"))
end
else
noiseFlag = %F
end
z = poly(0,'z')
aPoly = poly(modelData.a(length(modelData.a):-1:1),'z','coeff')
bPoly = poly(modelData.b,'z','coeff')
fPoly = poly(modelData.f(length(modelData.f):-1:1),'z','coeff')
afPoly = aPoly*fPoly
bCoeff = modelData.b
extra = 1
if ~bCoeff(1,1) then
afCoeff = coeff(afPoly)
bLength = length(bCoeff);afLength = length(afCoeff)
if bLength == afLength then
extra = 1
else
extra = z^-(bLength-afLength)
end
end
bPoly = poly(modelData.b(length(modelData.b):-1:1),'z','coeff')
sys = syslin('d',bPoly,afPoly)*extra
if size(find(gsort(abs(roots(sys.den)))>1),'*') then
tempRoot = clean(roots(sys.den))
[sorted index] = gsort(abs(real(tempRoot)))
tempRoot = tempRoot(index)
n = 26/log10(abs(real(tempRoot(1))))
else
finalValue = horner(sys,1)*1
n = 10
tempValue = sum(ldiv(sys.num,sys.den,n))
if finalValue >= 0 then
while finalValue*0.99 >= tempValue || n >=1000
n = n+10
tempValue = sum(ldiv(sys.num,sys.den,n))
end
elseif finalValue < 0 then
while finalValue*0.99 <tempValue || n >=1000
n = n+10
tempValue = sum(ldiv(sys.num,sys.den,n))
end
end
end
uData = ones(1,n)
yData = flts(uData,sys)
timeData = (0:(n-1))*modelData.Ts
if noiseFlag then
varargout(1) = yData'
else
plot2d2(timeData,yData,2)
varargout(1) = []
end
endfunction
|
