PROJECT TITLE :

Deadbeat Control for Electrical Drives: A Robust and Performant Design Based on Differential Flatness

ABSTRACT:

This contribution introduces a brand new deadbeat controller design that increases robustness without compromising performance. In conventional deadbeat management, feedback linearization is applied, and the feedback gains are set terribly high to obtain the minimum-step reference response. This makes the management technique highly sensitive to parametric uncertainties. To date, the sole remedies are to tune the deadbeat controller settling time higher and also the according disturbance estimator a lot of slowly. Recently proposed remedies primarily based on on-line parameter estimators show either moderate performance or higher demands on hardware. Thus, 1st a feedforward linearization-based controller is introduced to obtain the desired reference response via open-loop control. Thereby, the parametric sensitivity is considerably improved. Then, the new generalized flatness-based controller, a combine between feedback and feedforward linearization, is proposed. The result is a deadbeat controller with high dynamic performance and high robustness with respect to each parameter uncertainties and disturbances. The experimental results on an induction machine demonstrate very quick reference tracking, high robustness to typical parameter uncertainties, and active compensation of your time-varying disturbances. The results on a synchronous reluctance machine show that even terribly massive inductance uncertainties can be handled.