How to ensure Matrixes are matching size
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I am doing a recursive least squares model to try and reduce sensor error for a project, but I keep getting the error that the left and right matrixes in the for loop are mismatched- the left is 4- by 1 and the right is 4 by four, and I'm not sure where it's going wrong, or how to fix it.
function [Qhat]= RLS_estimation(Z,Unite,T) %
% Call A matrix from gen sate, final matrix
n=0;
P(:,:,1)=eye(4);
R=fixed.forgettingFactor(Z);
A=[1,T,0,0;0,1,0,0;0,0,1,T;0,0,0,1];
K = zeros(4, 1,n);
% AT is otranspose A, transpose A here
% Call matrix R with 'forgetting factors"
Qhat(:,:,1)=Unite;
for n= 2:Z
K(:,:,n)=P(:,:,n-1)*A.'*inv(A*P(:,:,n-1)*A.'+R);
P(:,:,n)=inv(R)-K(:,:,n)*A*inv(R)*P(:,:,n-1);
Qhat(:,:,n)=Qhat(:,:,n-1)+K(:,:,n)*(Unite(n)-A*Qhat(:,:,n-1));
end
2 Kommentare
Walter Roberson
am 1 Mai 2025
We do not know the size of Z or Unite or T (though we can deduce that T must be scalar)
You did not indicate which line the problem is occuring on.
Antworten (1)
Walter Roberson
am 1 Mai 2025
K = zeros(4, 1,n);
K is initialized to 4 x 1 by something.
K(:,:,n)=P(:,:,n-1)*A.'*inv(A*P(:,:,n-1)*A.'+R);
P is 4 x 4 by something.
A is 4 x 4.
P(:,:,n-1) * A.' is 4 x 4 x 1 mtimes transpose(4 x 4) so that part is (4 x 4) * (4 x 4) which gives a 4 x 4 result.
inv(A etc) is inv() of 4 x 4, so is 4 x 4 itself.
(4 x 4) * (4 x 4) gives a 4 x 4 result.
So the right hand side is 4 x 4.
You are attempting to store the 4 x 4 into a space that has been declared to be 4 x 1 x (1) . It is not going to fit.
Everything appears to work out if you initialized
K = zeros(4, 4,n);
2 Kommentare
Walter Roberson
am 2 Mai 2025
Unite is a four by Z matrix
But your code has
Qhat(:,:,n)=Qhat(:,:,n-1)+K(:,:,n)*(Unite(n)-A*Qhat(:,:,n-1));
which uses Unite as if it is a vector.
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