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Fix: scale the matrices in tests/riccatiupdate.m to control the size of errors

unit-tests
NormannR 2022-11-22 13:32:36 +01:00
parent dbdda7bf93
commit 93a2a097c6
1 changed files with 9 additions and 6 deletions
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15
tests/riccatiupdate.m
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@ -42,12 +42,17 @@ tol = 1e-15;
% Set the input arguments
% P, Q: use the fact that for any real matrix A, A'*A is positive semidefinite
P = rand(n,r);
P = P'*P;
P = P'*P;
Q = rand(n,r);
Q = Q'*Q;
K = rand(r,n);
Z = rand(n,r);
T = rand(r,r);
% Computing an upperbound for the norm the updated variance-covariance matrix
ub = norm(T,1)^2*norm(P,1)*(1+norm(K*Z,1))+norm(Q,1);
% Weighting the P and Q matrices to keep the norm of the variance-covariance matrix below 1
P = 0.5*P/ub;
Q = 0.5*Q/ub;
% 1. Update the state vairance-covariance matrix with Matlab
tElapsed1 = 0.;
@ -100,12 +105,10 @@ end
N = 50;
disp(['After 1 update using the Riccati formula, the norm-1 discrepancy is ' num2str(norm(Ptmp_fortran-Ptmp_matlab,1)) '.']);
for i=2:N
Ptmp_matlab_ini = Ptmp_matlab;
Ptmp_fortran_ini = Ptmp_fortran;
Ptmp_matlab = T*(Ptmp_matlab_ini-K*Z*Ptmp_matlab_ini)*transpose(T)+Q;
Ptmp_fortran = riccati_update(Ptmp_fortran_ini, T, K, Z, Q);
Ptmp_matlab = T*(Ptmp_matlab-K*Z*Ptmp_matlab)*transpose(T)+Q;
Ptmp_fortran = riccati_update(Ptmp_fortran, T, K, Z, Q);
disp(['After ' int2str(i) ' updates using the Riccati formula, the norm-1 discrepancy is ' num2str(norm(Ptmp_fortran-Ptmp_matlab,1)) '.'])
end
disp(['After ' int2str(N) ' updates using the Riccati formula, the norm-1 discrepancy is ' num2str(norm(Ptmp_fortran-Ptmp_matlab,1)) '.'])
t1 = clock;