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This paper presents a novel safety filter framework based on Control Barrier Functions (CBFs) and Control Lyapunov-like Functions (CLFs). The CBF guarantees forward invariance of the safe set, constraining system trajectories within state constraints, while the CLF guides the system away from unsafe states towards a nominal region, preserving the performance of a nominal controller. The first part of this work focuses on determining compatible CBF and CLF in the presence of linear or quadratic input constraints. This is achieved by formulating the CBF and CLF conditions, along with the input constraints, as Sum of Squares (SOS) constraints using Putinar's Positivstellensatz. For solving the resulting SOS optimization problem, we employ an alternating algorithm that simultaneously searches for a feasible controller in the class of rational functions of the state. The second part of this work details the implementation of the safety filter as a Quadratically Constrained Quadratic Program (QCQP), whose constraints encode the CBF and CLF conditions as well as the input constraints. To avoid the chattering effect and guarantee the uniqueness and Lipschitz continuity of solutions, the state-dependent inequality constraints of the QCQP are selected to be sufficiently regular. Finally, we demonstrate the method on a detailed case study involving the control of a three-phase ac/dc power converter connected to an infinite bus., Comment: 15 pages, 11 figures, submitted to IEEE Transactions on Control Systems Technology

This paper introduces an automatic control method designed to enhance the operation of electric vehicles, besides the speed tracking objectives, by including reliability and lifetime requirements. The research considers an automotive power converter which supplies electric power to a permanent magnet synchronous motor (PMSM). The primary control objective is to mitigate the thermal stress on the power electronic Insulate Gate Bipolar Transistors (IGBTs), while simultaneously ensuring effective speed tracking performance. To achieve these goals, we propose an extended H-inf design framework, which includes reliability models. The method is tested in two distinct scenarios: reliability-aware, and reliability-free cases. Furthermore, the paper conducts a lifetime analysis of the IGBTs, leveraging the Rainflow algorithm and temperature data., Comment: Submitted to ECC 20204 conference

In this paper, we introduce an Adjustable Switch Hybrid (ASH) converter concept. The ASH targets the optimization of the electrical performance of high-powered automotive drive-trains depending on the different load conditions during drive cycles. The new concept employs in principle the previously reported Cross Switch (XS) Hybrid having a parallel arrangement of bipolar Silicon IGBTs and unipolar SiC MOSFETs for benefiting from the different electrical characteristics of each paralleled device. However, the ASH relies on a computational approach for the continuous and dynamic adjustments of the Si-IGBT to the SiC MOSFET area ratio through the gate units depending on the load conditions. In practical terms, changes in the loading conditions can be sensed and data will then be sent back to the ASH gate drive unit for the optimum device ratio selection. In other words, the ASH provides the drivetrain with an Electronic Transmission System or Gear type functionality., Accepted Author Manuscript, DC systems, Energy conversion & Storage