Output Capacitance Minimization for Converters in DC Microgrids via Multi-Objective Tuning of Droop-Based Controllers

This paper proposes a controller tuning methodology for voltage-current droop-based DC-DC converters in DC microgrids to reduce the output capacitance. This minimization is cost saving and implies lower fault currents. However, it leads to higher DC voltage variability during load transients, which requires an output impedance shaping by control means to reduce over or undershoot. The proposed control structure and problem definition simultaneously takes into account that the solution must achieve the impedance shaping, performance and stand-alone stability objectives. This comprises a multi-objective problem which is effectively formulated here and, then, solved by a non-smooth $\mathcal {H}_\infty$ optimization technique that tunes all free parameters. For comparison purposes, this tuning methodology is applied to several droop proposals, and the proposed droop is able to reduce the output capacitance of bidirectional buck-type and boost-type half-bridge converters by 37.5% and 23.08%, respectively, with respect to previous proposals. The designs are validated in time and frequency domains by means of theoretical analysis and experimental results on DC microgrid prototypes with bidirectional buck-type or boost-type half-bridge converters

Localization of Mobile Robots Using Odometry and an External Vision Sensor

This paper presents a sensor system for robot localization based on the information obtained from a single camera attached in a fixed place external to the robot. Our approach firstly obtains the 3D geometrical model of the robot based on the projection of its natural appearance in the camera while the robot performs an initialization trajectory. This paper proposes a structure-from-motion solution that uses the odometry sensors inside the robot as a metric reference. Secondly, an online localization method based on a sequential Bayesian inference is proposed, which uses the geometrical model of the robot as a link between image measurements and pose estimation. The online approach is resistant to hard occlusions and the experimental setup proposed in this paper shows its effectiveness in real situations. The proposed approach has many applications in both the industrial and service robot fields

Exact Linearization Nonlinear Neutral-Point Voltage Control for Single-Phase Three-Level NPC Converters

This letter proposes a new control scheme for the neutral-point (NP) balance in single-phase three-level NP-clamped converters. The control is addressed considering the plant under study, a nonlinear time-variant system. A quasi-exact linearization is applied allowing the application of classic control techniques. The described method is simple, general, and suitable for buck and boost topologies, as well as for inverter or rectifier operating modes under either linear or nonlinear loading. Correct operation is verified under simulated and experimental operation

Exact Linearization Nonlinear Neutral-Point Voltage Control for Single-Phase Three-Level NPC Converters

This letter proposes a new control scheme for the neutral-point (NP) balance in single-phase three-level NP-clamped converters. The control is addressed considering the plant under study, a nonlinear time-variant system. A quasi-exact linearization is applied allowing the application of classic control techniques. The described method is simple, general, and suitable for buck and boost topologies, as well as for inverter or rectifier operating modes under either linear or nonlinear loading. Correct operation is verified under simulated and experimental operation