Parameter Tuning of Barrier Lyapunov Function-Based Controllers in Electric Drive Systems

This paper refers to fast and accurate electric servo control in the presence of position and velocity constraints. This problem, one of the most common nowadays in industrial automation, is often addressed by controllers derived using barrier Lyapunov functions (BLFs). This popular and effective technique is burdened with several difficulties, such as complex feasibility conditions and the inapplicability of the derived controller because of control constraints. In this contribution, we propose a novel, BLF-based, adaptive controller for an electric servo (linear or rotational) with modeling uncertainties, solving a tracking problem. The controller derivation is completed by the tuning procedure, which enables safe system operation in the presence of active control constraints, measurement errors, and noise. The selection of the best combination of BLFs is a part of this procedure. Also, all feasibility issues are solved by the proposed approach. The derivation is completed by extensive numerical simulations and real-life implementation using two different servo systems—the first with a linear permanent magnet motor and the second with a rotational PMSM.