Recursive and iterative least squares parameter estimation algorithms for observability canonical state space systems

This paper considers parameter identification problems for the observability canonical state space systems, and a state observer based recursive least squares identification algorithm and a Kalman filter based least squares iterative identification algorithm are proposed for estimating the system parameters and states. A numerical example is provided to confirm the effectiveness of the proposed algorithms.