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
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
|
// Estimates Discrete time estpoly model
// y(t) = [B(q)/F(q)]u(t) + [C(q)/D(q)]e(t)
// Current version uses random initial guess
// Need to get appropriate guess from OE and noise models
// Authors: Ashutosh,Harpreet,Inderpreet
// Updated(12-6-16)
//function [theta_estpoly,opt_err,resid] = estpoly(varargin)
function sys = estpoly(varargin)
[lhs , rhs] = argn();
if ( rhs < 2 ) then
errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 2"), "estpoly", rhs);
error(errmsg)
end
z = varargin(1)
if typeof(z) == 'iddata' then
Ts = z.Ts;unit = z.TimeUnit
z = [z.OutputData z.InputData]
elseif typeof(z) == 'constant' then
Ts = 1;unit = 'seconds'
end
if ((~size(z,2)==2) & (~size(z,1)==2)) then
errmsg = msprintf(gettext("%s: input and output data matrix should be of size (number of data)*2"), "estpoly");
error(errmsg);
end
if (~isreal(z)) then
errmsg = msprintf(gettext("%s: input and output data matrix should be a real matrix"), "estpoly");
error(errmsg);
end
n = varargin(2)
if (size(n,"*")<5| size(n,"*")>6) then
errmsg = msprintf(gettext("%s: The order and delay matrix [na nb nc nd nf nk] should be of size [5 6]"), "estpoly");
error(errmsg);
end
if (size(find(n<0),"*") | size(find(((n-floor(n))<%eps)== %f))) then
errmsg = msprintf(gettext("%s: values of order and delay matrix [nb nc nd nf nk] should be nonnegative integer number "), "estpoly");
error(errmsg);
end
na = n(1); nb = n(2); nc = n(3); nd = n(4);nf = n(5);
if (size(n,"*") == 5) then
nk = 1
else
nk = n(6);
end
// storing U(k) , y(k) and n data in UDATA,YDATA and NDATA respectively
YDATA = z(:,1);
UDATA = z(:,2);
NDATA = size(UDATA,"*");
function e = G(p,m)
e = YDATA - _oestpolyfun(UDATA,p,na,nb,nc,nd,nf,nk);//_oestpolyfun(UDATA,p,nd,nc,nf,nb,nk);
endfunction
tempSum = na+nb+nc+nd+nf
p0 = linspace(0.0001,0.001,tempSum)';
[var,errl] = lsqrsolve(p0,G,size(UDATA,"*"));
//disp(errl)
err = (norm(errl)^2);
//disp(err)
opt_err = err;
resid = G(var,[]);
x = var
// b = poly([repmat(0,nk,1);var(1:nb)]',"q","coeff");
// c = poly([1; var(nb+1:nb+nc)]',"q","coeff");
// d = poly([1; var(nb+nc+1:nb+nc+nd)]',"q","coeff");
// f = poly([1; var(nb+nd+nc+1:nd+nc+nf+nb)]',"q","coeff");
a = poly([1; x(1:na)]',"q","coeff");
b = poly([repmat(0,nk,1);x(na+1:na+nb)]',"q","coeff");
c = poly([1; x(na+nb+1:na+nb+nc)]',"q","coeff");
d = poly([1; x(na+nb+nc+1:na+nb+nc+nd)]',"q","coeff");
f = poly([1; x(na+nb+nd+nc+1:na+nd+nc+nf+nb)]',"q","coeff");
t = idpoly(coeff(a),coeff(b),coeff(c),coeff(d),coeff(f),Ts)
//t = sys;//idpoly(1,coeff(b),coeff(c),coeff(d),coeff(f),Ts)
// estimating the other parameters
[temp1,temp2,temp3] = predict(z,t)
[temp11,temp22,temp33] = pe(z,t)
//pause
estData = calModelPara(temp1,temp11,na+nb+nc+nd+nf)
//pause
t.Report.Fit.MSE = estData.MSE
t.Report.Fit.FPE = estData.FPE
t.Report.Fit.FitPer = estData.FitPer
t.Report.Fit.AIC = estData.AIC
t.Report.Fit.AICc = estData.AICc
t.Report.Fit.nAIC = estData.nAIC
t.Report.Fit.BIC = estData.BIC
t.TimeUnit = unit
sys = t
//sys.TimeUnit = unit
endfunction
function yhat = _oestpolyfun(UDATA,x,na,nb,nc,nd,nf,nk)//(UDATA,x,nd,nc,nf,nb,nk)
x=x(:)
q = poly(0,'q')
tempSum = na+nb+nc+nd+nf
// making polynomials
a = poly([1; x(1:na)]',"q","coeff");
b = poly([repmat(0,nk,1);x(na+1:na+nb)]',"q","coeff");
c = poly([1; x(na+nb+1:na+nb+nc)]',"q","coeff");
d = poly([1; x(na+nb+nc+1:na+nb+nc+nd)]',"q","coeff");
f = poly([1; x(na+nb+nd+nc+1:na+nd+nc+nf+nb)]',"q","coeff");
bd = coeff(b*d); cf = coeff(c*f); fc_d = coeff(f*(c-a*d));
if size(bd,"*") == 1 then
bd = repmat(0,nb+nd+1,1)
end
//pause
maxDelay = max([length(bd) length(cf) length(fc_d)])
yhat = [YDATA(1:maxDelay)]
for k=maxDelay+1:size(UDATA,"*")
bdadd = 0
for i = 1:size(bd,"*")
bdadd = bdadd + bd(i)*UDATA(k-i+1)
end
fc_dadd = 0
for i = 1:size(fc_d,"*")
fc_dadd = fc_dadd + fc_d(i)*YDATA(k-i+1)
end
cfadd = 0
for i = 2:size(cf,"*")
cfadd = cfadd + cf(i)*yhat(k-i+1)
end
//pause
yhat = [yhat; [ bdadd + fc_dadd - cfadd ]];
end
endfunction
|
