Iterative tuning algorithm for feedforward parameter identification of a 2-mass motor system

This paper proposes an algorithm for iteratively identifying the physical parameters of an elastically coupled two-mass torsional system directly from input-output data. The identification process is conducted under close-loop conditions with a 2-degree-of-freedom controller that incorporates a suitable reference model. It is shown that with convergence of the output error to zero, the controller parameters give a precise estimate of the true physical parameters. The tuning of controller parameters is accomplished in an iterative manner similar to the iterative feedback tuning (IFT), utilizing a linearized plant transfer function obtained through direct closed-loop identification based on the output over-sampling approach. By calculating the Vinnicombe distance, the proposed algorithm guarantees convergence and stability of controller parameters to the optimal values. A simulation is, conducted to demonstrate the effectiveness of this method in identifying the physical parameters of a two-mass motor system with different inertia ratio.