.Modelica_LinearSystems2.WorkInProgress.DiscreteStateSpace.Design.sr_kfStepMatrices

Information

One step, i.e. prediction and update of a kalman filter iteration for discrete systems

Interface

function sr_kfStepMatrices
  extends Modelica.Icons.Function;
  import Modelica;
  import Modelica_LinearSystems2;
  import Modelica_LinearSystems2.Math.Matrices.LAPACK;
  import Modelica_LinearSystems2.Math.Matrices;
  input Real A[:, size(A, 1)] "Transition matrix of the discrete system";
  input Real C[:, size(A, 1)] "Output matrix of the discrete system";
  input Real S[size(A, 1), size(A, 1)] "Cholesky factor of the state covariance matrix of the previous instant";
  input Real wB[size(A, 1), :] "Weighting matrix of the input noise covariance matrix of the previous instant";
  input Real Cq[size(wB, 2), size(wB, 2)] "Cholesky factor of input or process noise covariance matrix of the previous instant";
  input Real Cr[size(C, 1), size(C, 1)] "Cholesky factor or measurement noise covariance matrix of the previous instant";
  output Real K[size(A, 1), size(C, 1)] "Kalman filter gain matrix";
  output Real S_new[size(A, 1), size(A, 1)] "Updated state covariance matrix";
  output Real Cr_new[size(C, 1), size(C, 1)] "Modified Cholesky output or measurement noise covariance matrix";
  output Real M[size(C, 1) + size(A, 1), 2*size(C, 1) + size(A, 1)];
end sr_kfStepMatrices;