diff options
Diffstat (limited to 'rarx.sci')
| -rw-r--r-- | rarx.sci | 40 |
1 files changed, 38 insertions, 2 deletions
@@ -1,6 +1,42 @@ function varargout = rarx(varargin) + +// Parameters Estimation of ARX model by recursive method +// +// Calling Sequence +// sys = rarx(ioData,[na nb nk],lambda) +// 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 +// lambda : Forgetting factor,Default value is 0.95 +// sys : idpoly type polynomial have estimated coefficients of A(z^-1) and B(z^-1) polynomials +// +// Description +// Fit RARX model on given input output data +// RARX model is SISO type model. It uses recursive weighted least-squares algorithm to estimate the coefficient of ARX model +// sys is a struct type variable output contains data about theta and yhat. +// +// 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 = rarx(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 = rarx(ioData,[2,2,1]) +// +// Authors +// Ashutosh Kumar Bhargava, Bhushan Manjarekar + [lhs,rhs] = argn(0) -// plantData = varargin(1) orderData = varargin(2) na = orderData(1);nb = orderData(2) @@ -44,7 +80,7 @@ function varargout = rarx(varargin) for ii = 1:nb tempData(ii+nk:ii+N+nk-1,ii+na) = plantData(:,2) end - //tempData = [zeros(1,na+nb);tempData] + // tempData = [zeros(1,na+nb);tempData] tempData = tempData(1:N+1,:) for ii = 1:N |