Minimum time control for multiphase buck converter: analysis and application

The combination of minimum time control and multiphase converter is a favorable option for dc-dc converters in applications where output voltage variation is required, such as RF amplifiers and dynamic voltage scaling in microprocessors, due to their advantage of fast dynamic response. In this paper, an improved minimum time control approach for multiphase buck converter that is based on charge balance technique, aiming at fast output voltage transition is presented. Compared with the traditional method, the proposed control takes into account the phase delay and current ripple in each phase. Therefore, by investigating the behavior of multiphase converter during voltage transition, it resolves the problem of current unbalance after the transient, which can lead to long settling time of the output voltage. The restriction of this control is that the output voltage that the converter can provide is related to the number of the phases, because only the duty cycles at which the multiphase converter has total ripple cancellation are used in this approach. The model of the proposed control is introduced, and the design constraints of the buck converters filter for this control are discussed. In order to prove the concept, a four-phase buck converter is implemented and the experimental results that validate the proposed control method are presented. The application of this control to RF envelope tracking is also presented in this paper.

A novel topology control approach to maintain the node degree in dynamic wireless sensor networks

Topology control is an important technique to improve the connectivity and the reliability of Wireless Sensor Networks (WSNs) by means of adjusting the communication range of wireless sensor nodes. In this paper, a novel Fuzzy-logic Topology Control (FTC) is proposed to achieve any desired average node degree by adaptively changing communication range, thus improving the network connectivity, which is the main target of FTC. FTC is a fully localized control algorithm, and does not rely on location information of neighbors. Instead of designing membership functions and if-then rules for fuzzy-logic controller, FTC is constructed from the training data set to facilitate the design process. FTC is proved to be accurate, stable and has short settling time. In order to compare it with other representative localized algorithms (NONE, FLSS, k-Neighbor and LTRT), FTC is evaluated through extensive simulations. The simulation results show that: firstly, similar to k-Neighbor algorithm, FTC is the best to achieve the desired average node degree as node density varies; secondly, FTC is comparable to FLSS and k-Neighbor in terms of energy-efficiency, but is better than LTRT and NONE; thirdly, FTC has the lowest average maximum communication range than other algorithms, which indicates that the most energy-consuming node in the network consumes the lowest power.