Automatic nonlinear auto-tuning method for Hammerstein modeling of electrical drives

Accurate modeling of electrical drives for online testing is a relevant problem, because of their nonlinear behavior. Efficient modeling for simulation, performance evaluation, and testing must consider accurate as well as simple models. This paper proposes the application of auto-tune methods to identify equivalent Hammerstein models, where the nonlinear process is approximated by a static nonlinear element followed by a linear dynamic second or third-order model. The effectiveness of the presented procedure is first verified by simulation results, showing that Hammerstein models overcome the limitations inherent to small-signal linearizations. A standard implementation of such technique considers a relay adjustment for attempts in a heuristic way. In this paper, two innovations are proposed: the relay adjustment is automatically shifted and the method is applied for complex electric drives. Experimental results are shown in the case of a drive constituted by a DC/AC inverter supplying a single-phase induction motor and of a step-down chopper.