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For boost power converter with Sensorless Current Mode (SCM) control, the inductor current is acquired by current estimator instead of current sensing. Without consideration of parasitics, the estimator is low-accurate, which affects system Small Signal Model (SSM) and degrades the control performance. In this paper, the issue is studied in frequency domain, and solved by a Corrective Frequency Compensation for Parasitics (CFCP) strategy. First, transfer functions for power converter, current estimator and current mode controller are given for frequency-domain analysis. Second, without consideration of parasitics, conventional proportional integral compensation is used to improve the system stability. Furthermore, with consideration of parasitics, converter main pole is replaced by two poles while a zero emerges at the origin. In order to cancel out the influence, the proposed CFCP strategy adopts a second-order transfer function to correct zero/pole variation induced by parasitics. Finally, steady state performance and transient response of the converter are improved, which are verified by simulations and experiments. [ABSTRACT FROM AUTHOR]

Abstract: This paper develops a novel dynamic framed slotted ALOHA (DFSA) algorithm based on Bayesian estimation to improve the throughput of the radio frequency identification (RFID) system. At first, four types of anti-collision algorithms for tag identification are analyzed. Then, the proposed DFSA based on Bayesian estimation is deduced and introduced. Compared with the conventional DFSA algorithms, this algorithm takes advantage of the evidence in previous frames as the a priori information of the current frame which can end up with more precise estimation of tag number and rational frame length adjustment. Finally, the common simulation tool from Matlab is used to demonstrate the effectiveness of the proposed new algorithm for the average throughput improvements of the RFID system. [Copyright &y& Elsevier]