An asymptotically optimal indirect approach to continuous-time system identification
For control engineers and system identification practitioners, this provides a theoretically grounded and practically effective solution to a known limitation of indirect continuous-time identification.
The paper addresses the issue that indirect continuous-time system identification via zero-order hold sampling yields transfer function estimates with incorrect relative degree. The proposed method enforces a fixed relative degree, achieving consistency and asymptotic efficiency, with simulations demonstrating superior performance over existing methods.
The indirect approach to continuous-time system identification consists in estimating continuous-time models by first determining an appropriate discrete-time model. For a zero-order hold sampling mechanism, this approach usually leads to a transfer function estimate with relative degree 1, independent of the relative degree of the strictly proper real system. In this paper, a refinement of these methods is developed. Inspired by indirect PEM, we propose a method that enforces a fixed relative degree in the continuous-time transfer function estimate, and show that the resulting estimator is consistent and asymptotically efficient. Extensive numerical simulations are put forward to show the performance of this estimator when contrasted with other indirect and direct methods for continuous-time system identification.