Parameterizing positive-definite penalty matrices through eigenvalues and rotation angles and optimizing them with particle swarm optimization reduced control cost by up to 65% versus diagonal matrices in tested aerospace examples.
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Eigendecomposition Parameterization of Penalty Matrices for Enhanced Control Design: Aerospace Applications
Parameterizing positive-definite penalty matrices through eigenvalues and rotation angles and optimizing them with particle swarm optimization reduced control cost by up to 65% versus diagonal matrices in tested aerospace examples.