Robust Iterative Feedback Tuning Control of a Permanent Magnet Synchronous Motor with Repetitive Constraints: A Udwadia–Kalaba Approach

Purpose: This paper proposes a novel optimal robust trajectory tracking controller for a permanent magnet synchronous motor (PMSM). Methods: The robust controller is built on the frame of the Udwadia–Kalaba fundamental equation, which makes no linearization or nonlinear cancellation for nonlinear PMSM systems. As for the uncertainty of PMSM, which is assumed to be bound while the bound is unknown. The proposed tracking controller is designed using only nominal parameters of the PMSM model and the tracking error. A Lyapunov proof is provided for validating the deterministic performance of the robust controller. Assuming the trajectories to track are periodic, we transform the controlled PMSM. And then, an iterative feedback tuning (IFT) is employed for the optimization of the proposed model-based controller. Results: The Lyapunov proof and experimental results show that the PMSM can reach deterministic performances under the proposed robust control. After ten iterations of the IFT algorithm, the tracking error of the experimental PMSM decreases significantly. And both the tuning criterion and control gains converge to roughly stable values. Conclusions: The proposed optimal robust controller provides an efficient scheme for repetitive trajectory tracking of uncertain PMSM systems. Suggestions of future work are presented.