Stochastic gradient algorithm for state space system with d-step delay

This paper researches parameter and state estimation problems for linear systems with d-step delay. Combining the linear transformation and the property of the shift operator, the canonical state space model with d-step delay is transformed into an identification model. The stochastic gradient algorithm is raised to identify the parameter vectors. Finally, an example is presented to validate the given algorithms.