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Droop control is broadly used in dc power distribution systems, e.g., dc microgrids. Implementing droop control for switch mode power supplies requires the measurement of average current. Synchronous sampling is used in digital control systems to obtain the average of a triangular inductor waveform. However, the dead time, semiconductor turn-on and turn-off delays, and signal conditioning delays shift the sensed waveform and change the effective duty cycle, resulting in a misalignment and measurement error from the average value. This paper proposes a duty cycle weighted averaging method based on double sampling. By sampling twice per switching period and averaging the results using duty cycle as the weighting factor, the error due to waveform misalignment is theoretically eliminated. The result always equals the average value of the triangle. This method does not rely on the knowledge of circuit delays, making it easy to implement and robust to parameter variations. Simulations and experimental measurements validate the superior performance compared with conventional single and double sampling methods. The experiment on a droop-controlled dc–dc converter demonstrates a more accurate droop characteristic. [ABSTRACT FROM AUTHOR]

Polynomial interpolation is widely used in channel modeling for aerospace tracking, telemetry, and command channel simulators, to accurately regenerate the satellite motion parameters with a high sampling rate from the available low sampling rate motion data. In this paper, a novel piecewise osculating interpolation approach is proposed to improve modeling precision. It uses the available distance and its higher-order derivatives at each pair of adjacent knots to construct the piecewise interpolation polynomial, thus achieving a better precision and continuity of the resulting motion parameters. Moreover, it is efficiently implemented with an interpolation filter based on a modified Farrow structure, and the designed filter can interpolate the motion data obtained both through uniform or nonuniform sampling. Additionally, a sampling optimization algorithm is proposed. It optimizes the motion data sampling by minimizing the maximum interpolation error given the average sampling interval and interpolation polynomial order, and therefore, improves the precision further without increasing the costs. The validity of the proposed approach is verified by numerical simulation, and its advantages are demonstrated by comparison with existing methods. [ABSTRACT FROM AUTHOR]

This paper investigates the distributed federated Tobit Kalman filter fusion problem for a class of discrete-time systems subject to measurement censoring and packet delays. The censored measurement is characterized by the Tobit measurement model and the packet delay obeys the Poisson distribution. At the input terminal of each local estimator, a censoring detection device and a buffer with finite length are exploited to tackle the censored/delayed measurements. The filtering fusion is carried out in two steps: in the first step, every sensor in the network collects and sends its measurements to the corresponding local estimator via an unreliable network with probabilistic packet delays and, in the second step, the estimates from local estimators are further collected by the fusion center to form a fused estimate. The local estimator runs a modified Tobit Kalman filtering algorithm, which is designed based on the modified Tobit regression model, while the fusion center performs a distributed federated modified Tobit Kalman filtering algorithm, which is devised on the basis of the federated Kalman fusion rule. Given the buffer length, the prescribed bound on the estimation error covariance and the probability distribution of the packet delay, the stability performance of the proposed filtering fusion algorithm is evaluated via a probabilistic approach. Simulation results are provided to show the feasibility of the proposed filter. [ABSTRACT FROM AUTHOR]

Deadbeat control (DBC) is developed based on the system model, which is commonly used to achieve good control performance for a three-phase grid connected converter (GCC). Unbalanced grid voltage is a common phenomenon in power systems. In this study, an improved DBC based on current predictive correction (CPC_DBC) is used to control GCC under an unbalanced grid voltage. The main purposes of CPC_DBC are to reduce the adverse effects due to random sampling error to improve current control performance, and to enhance the interference rejection capability of the control system. Then, the characteristics of CPC_DBC and the conventional DBC (Con_DBC) are analyzed by transfer functions in the discrete time domain. Several common control objectives under an unbalanced grid voltage are used to demonstrate the superiority of CPC_DBC. Finally, the experimental results indicate that CPC_DBC can effectively reduce the adverse effects of random sampling error; the robustness of system due to the uncertain value of the filter inductance is improved as well. [ABSTRACT FROM PUBLISHER]

Traditionally, scheduling policies have been optimized to perform well on metrics, such as throughput, delay, and fairness. In the context of shared event schedulers, where a common processor is shared among multiple users, one also has to consider the privacy offered by the scheduling policy. The privacy offered by a scheduling policy measures how much information about the usage pattern of one user of the system can be learned by another as a consequence of sharing the scheduler. We introduced an estimation error-based metric to quantify this privacy. We showed that the most commonly deployed scheduling policy, the first-come-first-served offers very little privacy to its users. We also proposed a parametric nonwork conserving policy, which traded off delay for improved privacy. In this paper, we ask the question, is a tradeoff between delay and privacy fundamental to the design to scheduling policies? In particular, is there a work conserving, possibly randomized, and scheduling policy that scores high on the privacy metric? Answering the first question, we show that there does exist a fundamental limit on the privacy performance of a work-conserving scheduling policy. We quantify this limit. Furthermore, answering the second question, we demonstrate that the round-robin scheduling policy (deterministic policy) is privacy optimal within the class of work-conserving policies. [ABSTRACT FROM AUTHOR]

In this paper, we study the distributed blind equalization of networked single-input multi-output (SIMO) systems. An indirect distributed equalization framework is presented, which estimates the transfer functions followed by the associated equalizers. Two distributed indirect equalization algorithms are proposed: one depends on multiple average consensus operations, and the other relies on the combination of innovation and one average consensus operation. The former generates an approximate equalizer for which the associated estimation error is determined by the number of average consensus operations, while the latter can provide an accurate equalizer estimation under some mild conditions. The proposed algorithms estimate the desired equalizer recursively and recover the source signal in real time. Furthermore, the distributed equalization under a time-varying topology is investigated as well. Convergence properties of the proposed algorithms are established and numerical simulations are carried out to show the performances of the proposed algorithms. [ABSTRACT FROM PUBLISHER]