Mercurial > hg > ltpda
diff m-toolbox/classes/+utils/@math/vcfit.m @ 0:f0afece42f48
Import.
author | Daniele Nicolodi <nicolodi@science.unitn.it> |
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date | Wed, 23 Nov 2011 19:22:13 +0100 |
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--- /dev/null Thu Jan 01 00:00:00 1970 +0000 +++ b/m-toolbox/classes/+utils/@math/vcfit.m Wed Nov 23 19:22:13 2011 +0100 @@ -0,0 +1,622 @@ +% VCFIT Fits continuous models to frequency responses +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% DESCRIPTION: +% +% Fits a continuous model to a frequency response using relaxed +% s-domain vector fitting algorithm [1, 2]. The function is able to fit more +% than one frequency response per time. In case that more than one +% frequency response is passed as input, they are fitted with a set of +% common poles. Model functions are expanded in partial fractions: +% +% r1 rN +% f(s) = ------- + ... + ------- + d +% s - p1 s - pN +% +% CALL: +% +% [res,poles,dterm,mresp,rdl] = vcfit(y,f,poles,weight,fitin) +% +% INPUTS: +% +% - y: Is a vector wuth the frequency response data. +% - f: Is the frequency vector in Hz. +% - poles: are a set of starting poles. +% - weight: are a set of weights used in the fitting procedure. +% - fitin: is a struct containing fitting options and parameters. fitin +% fields are: +% - fitin.stable = 0; fit without forcing poles to be stable. +% - fitin.stable = 1; force poles to be stable flipping unstable +% poles in the left side of the complex plane. s -> s - 2*conj(s). +% - fitin.dterm = 0; fit with d = 0. +% - fitin.dterm = 1; fit with d different from 0. +% - fitin.polt = 0; fit without plotting results. +% - fitin.plot = 1; plot fit results in loglog scale. +% - fitin.plot = 2; plot fit results in semilogx scale. +% - fitin.plot = 3; plot fit results in semilogy scale. +% - fitin.plot = 4; plot fit results in linear xy scale. +% - fitin.ploth = #; a plot handle to define the figure target for +% plotting. Default: [1] +% +% OUTPUT: +% +% - res: vector or residues. +% - poles: vector of poles. +% - dterm: direct term d. +% - mresp: frequency response of the fitted model +% - rdl: residuals y - mresp +% - mse: normalized mean squared error +% +% EXAMPLES: +% +% - Fit on a single transfer function: +% +% INPUT +% y is a (Nx1) or (1xN) vector +% f is a (Nx1) or (1xN) vector +% poles is a (Npx1) or (1xNp) vector +% weight is a (Nx1) or (1xN) vector +% +% OUTPUT +% res is a (Npx1) vector +% poles is a (Npx1) vector +% dterm is a constant +% mresp is a (Nx1) vector +% rdl is a (Nx1) vector +% mse is a constant +% +% - Fit Nt transfer function at the same time: +% +% INPUT +% y is a (NxNt) or (NtxN) vector +% f is a (Nx1) or (1xN) vector +% poles is a (Npx1) or (1xNp) vector +% weight is a (NxNt) or (NtxN) vector +% +% OUTPUT +% res is a (NpxNt) vector +% poles is a (Npx1) vector +% dterm is a (1xNt) vector +% mresp is a (NxNt) vector +% rdl is a (NxNt) vector +% mse is a (1xNt) vector +% +% REFERENCES: +% +% [1] B. Gustavsen and A. Semlyen, "Rational approximation of frequency +% domain responses by Vector Fitting", IEEE Trans. Power Delivery +% vol. 14, no. 3, pp. 1052-1061, July 1999. +% [2] B. Gustavsen, "Improving the Pole Relocating Properties of Vector +% Fitting", IEEE Trans. Power Delivery vol. 21, no. 3, pp. +% 1587-1592, July 2006. +% +% NOTE: +% +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% HISTORY: 12-09-2008 L Ferraioli +% Creation +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +% VERSION: '$Id: vcfit.m,v 1.11 2010/02/08 19:05:59 luigi Exp $'; +% +%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% +function [res,poles,dterm,mresp,rdl,mse] = vcfit(y,f,poles,weight,fitin) + + warning off all + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Collecting inputs + + % Default input struct + defaultparams = struct('stable',0, 'dterm',0, 'plot',0, 'ploth', 1); + + names = {'stable','dterm','plot','ploth'}; + + % collecting input and default params + if ~isempty(fitin) + for jj=1:length(names) + if isfield(fitin, names(jj)) && ~isempty(fitin.(names{1,jj})) + defaultparams.(names{1,jj}) = fitin.(names{1,jj}); + end + end + end + + stab = defaultparams.stable; % Enforce pole stability is is 1 + dt = defaultparams.dterm; % 1 to fit with direct term + plotting = defaultparams.plot; % set to 1 if plotting is required + plth = defaultparams.ploth; % set the figure target + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Inputs in row vectors + + [a,b] = size(y); + if a > b % shifting to row + y = y.'; + end + + [a,b] = size(f); + if a > b % shifting to row + f = f.'; + end + + [a,b] = size(poles); + if a > b % shifting to row + poles = poles.'; + end + + clear w + w = weight; + [a,b] = size(w); + if a > b % shifting to row + w = w.'; + end + + N = length(poles); % Model order + + if dt + dl = 1; % Fit with direct term + else + dl = 0; % Fit without direct term + end + + % definition of s + s = 1i.*2.*pi.*f; + + Nz = length(s); + [Nc,Ny] = size(y); + if Ny ~= Nz + error(' Number of data points different from number of frequency points! ') + end + + %Tolerances used by relaxed version of vector fitting + TOLlow=1e-8; + TOLhigh=1e8; + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Marking complex and real poles + + % cindex = 1; pole is complex, next conjugate pole is marked with cindex + % = 2. cindex = 0; pole is real + cindex=zeros(1,N); + for m=1:N + if imag(poles(m))~=0 + if m==1 + cindex(m)=1; + else + if cindex(m-1)==0 || cindex(m-1)==2 + cindex(m)=1; cindex(m+1)=2; + else + cindex(m)=2; + end + end + end + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Augmented problem + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Matrix initialinzation + BA = zeros(Nc*Nz+1,1); + Ak=zeros(Nz,N+1); + AA=zeros(Nz*Nc+1,(N+dl)*Nc+N+1); + nf = zeros(1,Nc*(N+dl)+N+1); % Normalization factor + + % Defining Ak + for jj = 1:N + if cindex(jj) == 1 % conjugate complex couple of poles + Ak(:,jj) = 1./(s-poles(jj)) + 1./(s-conj(poles(jj))); + Ak(:,jj+1) = 1i./(s-poles(jj)) - 1i./(s-conj(poles(jj))); + elseif cindex(jj) == 0 % real pole + Ak(:,jj) = 1./(s-poles(jj)); + end + end + + Ak(1:Nz,N+1) = 1; + + % Scaling factor + sc = 0; + for mm = 1:Nc + sc = sc + (norm(w(mm,:).*y(mm,:)))^2; + end + sc=sqrt(sc)/Nz; + + for nn = 1:Nc + + wg = w(nn,:).'; % Weights + + ida=(nn-1)*Nz+1; + idb=nn*Nz; + idc=(nn-1)*(N+dl)+1; + + for mm =1:N+dl % Diagonal blocks + AA(ida:idb,idc-1+mm) = wg.*Ak(1:Nz,mm); + end + for mm =1:N+1 % Last right blocks + AA(ida:idb,Nc*(N+dl)+mm) = -wg.*(Ak(1:Nz,mm).*y(nn,1:Nz).'); + end + + end + + % setting the last row of AA and BA for the relaxion condition + for qq = 1:N+1 + AA(Nc*Nz+1,Nc*(N+dl)+qq) = real(sc*sum(Ak(:,qq))); + end + + AA = [real(AA);imag(AA)]; + + % Last element of the solution vector + BA(Nc*Nz+1) = Nz*sc; + + xBA = real(BA); + xxBA = imag(BA); + + Nrow = Nz*Nc+1; + + BA = zeros(2*Nrow,1); + + BA(1:Nrow,1) = xBA; + BA(Nrow+1:2*Nrow,1) = xxBA; + + % Normalization factor + % nf = zeros(2*N+dl+1,1); + for pp = 1:length(AA(1,:)) + nf(pp) = norm(AA(:,pp),2); % Euclidean norm + AA(:,pp) = AA(:,pp)./nf(pp); % Normalization + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Solving augmented problem + +% XA = pinv(AA)*BA; + % XA = inv((AA.')*AA)*(AA.')*BA; + + % XA = AA.'*AA\AA.'*BA; + + XA = AA\BA; + + XA = XA./nf.'; % renormalization + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Checking the tolerance + + if abs(XA(end))<TOLlow || abs(XA(end))>TOLhigh + + if XA(end)==0 + Dnew=1; + elseif abs(XA(end))<TOLlow + Dnew=sign(XA(end))*TOLlow; + elseif abs(XA(end))>TOLhigh + Dnew=sign(XA(end))*TOLhigh; + end + + for pp = 1:length(AA(1,:)) + AA(:,pp) = AA(:,pp).*nf(pp); %removing previous scaling + end + + ind=length(AA(:,1))/2; %index to additional row related to relaxation + + AA(ind,:)=[]; % removing relaxation term + + BA=-Dnew*AA(:,end); %new right side + + AA(:,end)=[]; + + nf(end)=[]; + + for pp = 1:length(AA(1,:)) + nf(pp) = norm(AA(:,pp),2); % Euclidean norm + AA(:,pp) = AA(:,pp)./nf(pp); % Normalization + end + + % XA=(AA.'*AA)\(AA.'*BA); % using normal equation + + XA=AA\BA; + + XA = XA./nf.'; % renormalization + + XA=[XA;Dnew]; + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Finding zeros of sigma + + lsr = XA((N+dl)*Nc+1:(N+dl)*Nc+N,1); % collect the least square results + + D = XA(end); % direct term of sigma + + CPOLES = diag(poles); + B = ones(N,1); + C = lsr.'; + + for kk = 1:N + if cindex(kk) == 1 + CPOLES(kk,kk)=real(poles(kk)); + CPOLES(kk,kk+1)=imag(poles(kk)); + CPOLES(kk+1,kk)=-1*imag(poles(kk)); + CPOLES(kk+1,kk+1)=real(poles(kk)); + B(kk,1) = 2; + B(kk+1,1) = 0; + end + end + + H = CPOLES-B*C/D; + + szeros=eig(H); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Ruling out unstable poles + + % This option force the poles of f to stay inside the left side of the + % complex plane + + if stab + unst = real(szeros)>0; + szeros(unst) = szeros(unst)-2*real(szeros(unst)); % Mirroring respect to the complex axes + end + szeros = sort(szeros); + N = length(szeros); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Separating complex poles from real poles and ordering + + rnpoles = []; + inpoles = []; + for tt = 1:N + if imag(szeros(tt)) == 0 + % collecting real poles + rnpoles = [rnpoles; szeros(tt)]; + else + % collecting complex poles + inpoles = [inpoles; szeros(tt)]; + end + end + + % Sorting complex poles in order to have them in the expected order a+jb + % and a-jb a>0 b>0 + inpoles = sort(inpoles); + npoles = [rnpoles;inpoles]; + npoles = npoles - 2.*1i.*imag(npoles); + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Marking complex and real poles + + cindex=zeros(N,1); + for m=1:N + if imag(npoles(m))~=0 + if m==1 + cindex(m)=1; + else + if cindex(m-1)==0 || cindex(m-1)==2 + cindex(m)=1; cindex(m+1)=2; + else + cindex(m)=2; + end + end + end + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Direct problem + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + + % Matrix initialinzation + nB(1:Nz,1:Nc) = real(w.*y).'; + nB(Nz+1:2*Nz,1:Nc) = imag(w.*y).'; + + B = zeros(2*Nz,1); + nAD = zeros(Nz,N+dl); + AD = zeros(2*Nz,N+dl); + Ak = zeros(Nz,N+dl); + + % Defining Ak + for jj = 1:N + if cindex(jj) == 1 % conjugate complex couple of poles + Ak(:,jj) = 1./(s-npoles(jj)) + 1./(s-npoles(jj+1)); + Ak(:,jj+1) = 1i./(s-npoles(jj)) - 1i./(s-npoles(jj+1)); + elseif cindex(jj) == 0 % real pole + Ak(:,jj) = 1./(s-npoles(jj)); + end + end + + if dt + Ak(1:Nz,N+dl) = ones(Nz,1); % considering the direct term + end + + XX = zeros(Nc,N+dl); + for nn = 1:Nc + + % Defining AD + for m=1:N+dl + nAD(1:Nz,m) = w(nn,:).'.*Ak(1:Nz,m); + end + + B(1:2*Nz,1) = nB(1:2*Nz,nn); + + AD(1:Nz,:) = real(nAD); + AD(Nz+1:2*Nz,:) = imag(nAD); + + % Normalization factor + nf = zeros(N+dl,1); + for pp = 1:N+dl + nf(pp,1) = norm(AD(:,pp),2); % Euclidean norm + AD(:,pp) = AD(:,pp)./nf(pp,1); % Normalization + end + + % Solving direct problem + + % XD = inv((AD.')*AD)*(AD.')*B; + % XD = AD.'*AD\AD.'*B; +% XD = pinv(AD)*B; + XD = AD\B; + + XD = XD./nf; % Renormalization + + XX(nn,1:N) = XD(1:N).'; + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Final residues and poles of f + + lsr = XX(:,1:N); + + res = zeros(N,Nc); + % Real poles have real residues, complex poles have comples residues + for nn = 1:Nc + for tt = 1:N + if cindex(tt) == 1 % conjugate complex couple of poles + res(tt,nn) = lsr(nn,tt)+1i*lsr(nn,tt+1); + res(tt+1,nn) = lsr(nn,tt)-1i*lsr(nn,tt+1); + elseif cindex(tt) == 0 % real pole + res(tt,nn) = lsr(nn,tt); + end + end + end + + poles = npoles; + + if dt + dterm = XX(:,N+dl).'; + else + dterm = zeros(1,Nc); + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Calculating responses and residuals + + mresp = zeros(Nz,Nc); + rdl = zeros(Nz,Nc); + mse = zeros(1,Nc); + + for nn = 1:Nc + % freq resp of the fit model + r = res(:,nn); + p = poles; + d = dterm(:,nn); + + Nf = length(f); + N = length(p); + + rsp = zeros(Nf,1); + indx = (0:length(d)-1).'; + for ii = 1:Nf + for jj = 1:N + rsptemp = r(jj)/(1i*2*pi*f(ii)-p(jj)); + rsp(ii) = rsp(ii) + rsptemp; + end + % Direct terms response + rsp(ii) = rsp(ii) + sum((((1i*2*pi*f(ii))*ones(length(d),1)).^indx).*d); + end + + % Model response + mresp(:,nn) = rsp; + + % Residual + rdl(:,nn) = y(nn,:).' - rsp; + + % RMS error +% mse(:,nn) = sqrt(sum((abs(rdl(:,nn)./(y(nn,:).')).^2))/(Nf-N)); + % Chi Square or mean squared error + % Note that this error is normalized to the input data in order to + % comparable between different sets of data + mse(:,nn) = sum((rdl(:,nn)./y(nn,:).').*conj((rdl(:,nn)./y(nn,:).')))/(Nf-N); + + end + + %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%% + % Plotting response + + switch plotting + + case 0 + % No plot + + case 1 + % LogLog plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = loglog(f,abs(y.'),'k'); + hold on + p2 = loglog(f,abs(mresp),'r'); + p3 = loglog(f,abs(rdl),'b'); + xlabel('Frequency [Hz]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'VCFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogx(f,(180/pi).*unwrap(angle(y.')),'k'); + hold on + p5 = semilogx(f,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Frequency [Hz]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'VCFIT') + hold off + + case 2 + % Semilogx plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = semilogx(f,abs(y.'),'k'); + hold on + p2 = semilogx(f,abs(mresp),'r'); + p3 = semilogx(f,abs(rdl),'b'); + xlabel('Frequency [Hz]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'VCFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogx(f,(180/pi).*unwrap(angle(y.')),'k'); + hold on + p5 = semilogx(f,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Frequency [Hz]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'VCFIT') + hold off + + case 3 + % Semilogy plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = semilogy(f,abs(y.'),'k'); + hold on + p2 = semilogy(f,abs(mresp),'r'); + p3 = semilogy(f,abs(rdl),'b'); + xlabel('Frequency [Hz]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'VCFIT','Residual') + hold off + + subplot(2,1,2); + p4 = semilogy(f,(180/pi).*unwrap(angle(y.')),'k'); + hold on + p5 = semilogy(f,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Frequency [Hz]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'VCFIT') + hold off + + case 4 + % Linear plot for absolute value + figure(plth) + subplot(2,1,1); + p1 = plot(f,abs(y.'),'k'); + hold on + p2 = plot(f,abs(mresp),'r'); + p3 = plot(f,abs(rdl),'b'); + xlabel('Frequency [Hz]') + ylabel('Amplitude') + legend([p1(1) p2(1) p3(1)],'Original', 'VCFIT','Residual') + hold off + + subplot(2,1,2); + p4 = plot(f,(180/pi).*unwrap(angle(y.')),'k'); + hold on + p5 = plot(f,(180/pi).*unwrap(angle(mresp)),'r'); + xlabel('Frequency [Hz]') + ylabel('Phase [Deg]') + legend([p4(1) p5(1)],'Original', 'VCFIT') + hold off + + end