An EM-based identification algorithm for a class of hybrid systems with application to power electronics

Abstract

In this paper we present an identification algorithm for a class of continuous-time hybrid systems. In such systems, both continuous-time and discrete-time dynamics are involved. We apply the expectation-maximisation algorithm to obtain the maximum likelihood estimate of the parameters of a discrete-time model expressed in incremental form. The main advantage of this approach is that the continuous-time parameters can directly be recovered. The technique is particularly well suited to fast-sampling rates. As an application, we focus on a standard identification problem in power electronics. In this field, our proposed algorithm is of importance since accurate modelling of power converters is required in high- performance applications and for fault diagnosis. As an illustrative example, and to verify the performance of our proposed algorithm, we apply our results to a flying capacitor multicell converter.

Keywords:

• system identification
• maximum likelihood
• power conversion

Notes

1. For simplicity of notation, we will omit the dependency on the parameter vector θ for the state-space matrices.

Additional information

Funding

This work is partially supported by the Australian Research Council through Discovery Projects DP 1095123 and DP 110103074, and by the Chilean Research Council (CONICYT) through grants Anillo [grant number ACT-53] and FONDECYT [grant number 1130861].