This paper introduces a parameter estimation technique for power electronic inverter-based systems. Specific attention is given to the real-time parameter estimation of dc-ac switched-mode power converters; Nevertheless, the proposed method can be applied to many alternative applications where efficient and accurate parameter estimation is required. The proposed scheme is computationally efficient, based on a Kalman filter algorithm, and uses an infinite impulse response adaptive filter as the plant model. The system identification scheme reduces the complexity of computation of existing typical adaptive algorithms. Importantly, the proposed approach can also identify the parameters fast and accurately, thus providing an efficient hardware solution that is suitable for real-time applications. In doing so, the uncertainties of VSIs can be identified by estimated parameters changes. The analysis of simulation and verification based on experimental data from a prototype flexible dc-ac converter is presented. Results clearly demonstrate that the estimated parameters of the dc-ac converter are a high match to the real experimental system. The scheme can be directly employed on adaptive and self-tuning digital controllers to improve control performance of a wide range of renewable energy applications.

This paper presents an iterative decimation approach to significantly alleviate the computational burden of centralized controllers applying real-time recursive system identification algorithms in multi-rail power converters. The proposed approach uses an adaptive update rate as opposed to the fixed update rate used in conventional adaptive filters. Also, the step size/forgetting factors vary at different iteration stages. As a result, a reduced computational burden and faster model update can be achieved. Besides, recursive algorithms, such as Recursive Least Square (RLS), Fast Affine Projection (FAP) and Kalman Filter (KF), contain two important updates per iteration cycle; Covariance Matrix Approximation (CMA) update and Gradient Vector (GV) update. Usually, the CMA update requires the greater computational effort than the GV update. Therefore, in circumstances where the sampled data in the regressor does not experience significant fluctuations, re-using the CMA, calculated from the last iteration cycle for the current update can result in computational cost savings for real-time system identification. In this paper, both iteration rate adjustment and CMA re-cycling are combined and applied to simultaneously identify the power converter models in a three-rail power conversion architecture.

A new switching scheme, which combines conventional space vector modulation (SVM) and carrier-based pulse width modulation (CBPWM), is proposed for a three-phase four-leg voltage source inverter (VSI). The proposed algorithm is simpler than conventional three-dimensional space vector modulation (3-D SVM) and easy in implementation in a real-time DSP system, it avoids the selection of a prism and tetrahedron in a 3-D SVM, therefore alleviates the computation burden of the DSP. Also, the concept of near-state pulse width modulation (NSPWM) method, which is used in a three-phase three-leg inverter to reduce the common mode voltage (CMV) noises, can be adopted in this algorithm so as to reduce the common mode voltage for a three-phase four-leg VSI. The feasibility of the proposed modulation technique is verified by both computer simulation and experimental results.