diff options
Diffstat (limited to 'iv.sci')
| -rw-r--r-- | iv.sci | 61 |
1 files changed, 53 insertions, 8 deletions
@@ -1,5 +1,50 @@ function varargout = iv(varargin) +// Parameters Estimation of IV model by arbitrary instrumental variable method +// +// Calling Sequence +// sys = iv(ioData,[na nb nk]) +// sys = iv(ioData,[na nb nk],instData) +// Parameters +// ioData : iddata or [outputData inputData] ,matrix of nx2 dimensions, type plant data +// na : non-negative integer number specified as order of the polynomial A(z^-1) +// nb : non-negative integer number specified as order of the polynomial B(z^-1)+1 +// nk : non-negative integer number specified as input output delay, Default value is 1 +// instData : arbitrary instrument variable matrix. The size of instriment variable must be equal to the size of outputData +// sys : idpoly type polynomial have estimated coefficients of A(z^-1) and B(z^-1) polynomials +// +// Description +// Fit IV model on given input output data +// The mathematical equation of the IV model +// <latex> +// begin{eqnarray} +// A(q)y(n) = B(q)u(n-k) + e(t) +// end{eqnarray} +// </latex> +// It is SISO type model. Instrument variable method is use to estimate the cofficients. If user does not provide the arbitrary instrument variable matrix +// then the program extracte it by using ARX method. +// +// sys ,an idpoly type class, have different fields that contains estimated coefficients, sampling time, time unit and other estimated data in Report object. +// +// Examples +// u = idinput(1024,'PRBS',[0 1/20],[-1 1]) +// a = [1 0.2];b = [0 0.2 0.3]; +// model = idpoly(a,b,'Ts',0.1) +// y = sim(u,model) + rand(length(u),1) +// ioData = iddata(y,u,0.1) +// sys = arx(ioData,[2,2,1]) +// +// Examples +// u = idinput(1024,'PRBS',[0 1/20],[-1 1]) +// a = [1 0.2];b = [0 0.2 0.3]; +// model = idpoly(a,b,'Ts',0.1) +// y = sim(u,model) + rand(length(u),1) +// ioData = [y,u] +// sys = iv(ioData,[2,2,1]) +// +// Authors +// Ashutosh Kumar Bhargava, Bhushan Manjarekar + [lhs , rhs] = argn(0); if ( rhs < 2 || rhs > 3) then errmsg = msprintf(gettext("%s: Unexpected number of input arguments : %d provided while should be 2 or 3"), "iv", rhs); @@ -58,19 +103,19 @@ function varargout = iv(varargin) end phif = zeros(noOfSample,na+nb) psif = zeros(noOfSample,na+nb) - // arranging samples of y matrix + // arranging samples of y matrix for ii = 1:na phif(ii+1:ii+noOfSample,ii) = yData psif(ii+1:ii+noOfSample,ii) = x end - // arranging samples of u matrix + // arranging samples of u matrix for ii = 1:nb phif(ii+nk:ii+noOfSample+nk-1,ii+na) = uData psif(ii+nk:ii+noOfSample+nk-1,ii+na) = uData end lhs = psif'*phif lhsinv = pinv(lhs) - //pause + // pause theta = lhsinv * (psif)' * [yData;zeros(n,1)] ypred = (phif * theta) ypred = ypred(1:size(yData,'r')) @@ -79,12 +124,12 @@ function varargout = iv(varargin) vcov = sigma2 * pinv((phif)' * phif) t = idpoly([1; -theta(1:na)],[zeros(nk,1); theta(na+1:$)],1,1,1,1) - // estimating the other parameters - [temp1,temp2,temp3] = predict(z,t) - [temp11,temp22,temp33] = pe(z,t) + // estimating the other parameters + [temp1,temp2,temp3] = predict(plantData,t) + [temp11,temp22,temp33] = pe(plantData,t) estData = calModelPara(temp1,temp11,na+nb) - //pause + // pause t.Report.Fit.MSE = estData.MSE t.Report.Fit.FPE = estData.FPE t.Report.Fit.FitPer = estData.FitPer @@ -93,6 +138,6 @@ function varargout = iv(varargin) t.Report.Fit.nAIC = estData.nAIC t.Report.Fit.BIC = estData.BIC t.TimeUnit = unit - //sys = t + // sys = t varargout(1) = t endfunction |