A nonlinear and linear model of a hybrid stepping motor

Intelligent drive methodologies typically require an accurate machine model. In this paper a state space model for hybrid stepping motors is derived. A hybrid stepping motor is a complex, nonlinear machine, characterized by position dependent parameters. The different, position dependent, parameters are measured, discussed and modeled. This leads to a highly nonlinear model, resulting in a high computational cost. However, when the motor is controlled by a vector-control algorithm, the position dependence of certain model parameters can be eliminated. If common assumptions are made, and reluctance effects are neglected, the motor model can be transformed into a linear model. This linear model is verified by simulations and measurements. A profound sensitivity analysis proves the robustness of the model.Intelligent drive methodologies typically require an accurate machine model. In this paper a state space model for hybrid stepping motors is derived. A hybrid stepping motor is a complex, nonlinear machine, characterized by position dependent parameters. The different, position dependent, parameters are measured, discussed and modeled. This leads to a highly nonlinear model, resulting in a high computational cost. However, when the motor is controlled by a vector-control algorithm, the position dependence of certain model parameters can be eliminated. If common assumptions are made, and reluctance effects are neglected, the motor model can be transformed into a linear model. This linear model is verified by simulations and measurements. A profound sensitivity analysis proves the robustness of the model.C