It is promising but challenging to design flocking control for a robot swarm to autonomously follow changing patterns or shapes in a optimal distributed manner. The optimal flocking control with dynamic pattern formation is, therefore, investigated in this paper. A predictive flocking control algorithm is proposed based on a Gibbs random field (GRF), where bio-inspired potential energies are used to charaterize "robot-robot" and "robot-environment" interactions. Specialized performance-related energies, e.g., motion smoothness, are introduced in the proposed design to improve the flocking behaviors. The optimal control is obtained by maximizing a posterior distribution of a GRF. A region-based shape control is accomplished for pattern formation in light of a mean shift technique. The proposed algorithm is evaluated via the comparison with two state-of-the-art flocking control methods in an environment with obstacles. Both numerical simulations and real-world experiments are conducted to demonstrate the efficiency of the proposed design.

As one of the most important parts of the future smart grid system, the three-phase cascaded multilevel converter based power electronic transformer (PET) is mainly composed of three parts: the three-phase input rectifier, middle dual active bridges (DAB) and output inverter. The three-phase input rectifier stage adopts pulse width modulation (PWM) rectifier. But there exists harmonic power in the power grid under unbalanced voltages which can affect the grid power quality seriously. Positive and negative sequence separating method is presented to solve the issue. The current references under positive and negative sequence d-q axis are obtained by using the relation of voltage, current and power, through which the control method is improved and simulation model is set up. Phase shifting control is adopted in DAB stage of three-phase PET. The result shows that the new method can control the input current, decrease the harmonic power, keep the DC voltage of rectifier stage steady and ensure that the whole system runs at unity power factor under unbalanced grid voltages.

As one of the most important parts of the future smart grid system, the three-phase cascaded multilevel converter based power electronic transformer (PET) mainly consists of three parts, the three-phase input rectifier, middle dual-active bridges (DAB) dc-dc converter and output inverter. For cascaded multilevel converter based PET, due to unbalanced issue of DC output voltage of each rectifier module or transmitted power in each DAB module, switches in PET often suffers uneven voltage or current stresses. This paper presents a voltage balance control strategy in multilevel rectifier stage and a sensorless power balance control strategy for the modular DAB converter to solve voltage unbalance issue and the power unbalance issue caused by mismatch of the parameters of each DAB module. The voltage balance of the three-phase rectifier is achieved by the combination of a primary voltage loop and an auxiliary voltage loop. The active power component of the duty cycle in the rectifier stage is used as power feedback to adjust the duty cycle of each DAB module to realize power balance. Furthermore, there is no current sensor used in this power balance control algorithm. Finally the proposed strategy is verified through simulation.