States based iterative parameter estimation for a state space model with multi-state delays using decomposition

This paper is concerned with the parameter estimation of a class of time-delay systems in the state space form. By using the hierarchical identification principle, a gradient based and a least squares based iterative identification algorithms are developed to compute these parameter estimates. The basic idea is to decompose a state space system into two subsystems, one containing a parameter vector and the other containing a parameter matrix. The simulation example demonstrates the efficacy of the proposed theory. HighlightsConsider estimation problems of a class of time-delay state space systems.Use the hierarchical identification principle and the iterative technique.Present a gradient based and a least squares based iterative estimation algorithms.

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