Parametric covariance assignment using reduced-order closed-form covariance model

In this paper, two novel closed-form covariance models using covariance matrix eigenvalues are presented for continue-time linear stochastic systems and discrete-time linear stochastic systems, respectively, which are subjected to Gaussian noises. Based on these model, the state and output covariance assignment algorithms have been developed with parametric state and output feedback. Due to the simple structure of this model, the low-order controller can be obtained following the proposed algorithms, which reduced computational complexity and the, extended free parameters of parametric feedback can supply flexibility to optimization.