Identification of dynamic plants with the use of matrix square roots

Parametric identification of dynamic processes through nonlinear filtering is discussed. To make the identification stable, instead of a convariance estimation error matrix the procedure uses a matrix square root of the covariance matrix. Equations are obtained for continuous estimation of parameters with the use of a matrix root. The triangular form of identification equations is considered which reduces the labor consumed in using matrix square roots.