The active power-decoupling (APD) method is an effective solution to handle the inherent double-line frequency ripple power in single-phase power systems. It removes the bulky passive devices and facilitates the improvement of the system power density and even the reliability. This article provides a comprehensive review of the prior-art and state-of-the-art control strategies in APD. They are categorized into four groups according to the basic control ideas of “power balance,” “harmonic suppression,” “volt-second balance/charge balance,” and “virtual impedance.” And the specific control strategies under each control idea are discussed and compared. The pros and cons of each control idea are also presented . Finally, this article draws a sketch of the global trends in APD control.

In practice, sensor precision degradation is ubiquitous and early detection of such a degradation is important for monitoring task. In this paper, a cumulative canonical correlation analysis (CCA) based sensor precision degradation detection method is presented in the Gaussian and non-Gaussian cases. At first, the fault sensitivity of the original CCA method to sensor precision degradation is theoretically analyzed. Then, the cumulative CCA-based method is proposed and delivers better fault detectability than the corresponding standard CCA-based method with respect to fault detection rate. For the non-Gaussian case, an efficient and practical applicable approach, referred as threshold learning approach, is proposed to set appropriate threshold based on available historical measurements. Finally, with the application to a real laboratorial continuous stirred tank heater plant, the feasibility and superiority of the proposed method are demonstrated by a comparison with the standard CCA-based and principal component analysis-based methods.

In this paper, a novel finite control set model predictive control (FCS-MPC)-based solution is proposed to eliminate the common-mode voltage (CMV) in matrix converters. Different from the existing MPC-based CMV reduction methods, which usually utilize all the possible switching configurations, in the proposed method, only the six rotating vectors, which produce no CMV, are included in the FCS to synthesize the output voltage and the input current. Therefore, zero CMV can be achieved naturally and no CMV related term needs to be included in the cost function. In addition, compared with other zero CMV methods, e.g., the enhanced space-vector modulation using rotating vectors, the proposed MPC-based method can significantly reduce the computational complexity without detracting the CMV elimination performance. Moreover, a modified four-step commutation strategy is proposed to effectively mitigate the CMV spikes due to the dead time, which usually exists when using the conventional current-based four-step commutation strategy. Finally, the feasibility and effectiveness of the proposed method are validated by using experimental studies.

Reliable fault diagnosis and identification are essential for permanent magnet synchronous motor (PMSM) drive systems with high-reliability requirements. Since open-switch fault and output current sensor fault both affect the residual of output phase current, it is difficult to identify them apart from each other. Thus, this article proposes an open-switch fault and output current sensor fault diagnosis and identification method for the matrix converter (MC)-based PMSM drive system. The finite control set-model predictive control (FCS-MPC) method is applied in the MC-based PMSM drive system. The fault identification method is proposed based on the extracted different faulty features of the open-switch fault and the output current sensor fault. After the open-switch fault is separated from the current sensor fault, an error-voltage-based open-switch fault diagnosis strategy is applied to locate the faulty switch. Hardware-in-the-loop tests are carried out to verify the effectiveness of the proposed method.

Brushless doubly fed induction machines (BDFIMs) feature some important advantages, such as high reliability and low maintenance cost, over alternative solutions for brushless machine applications. This paper proposes a modulated model predictive control (MPC) algorithm for BDFIMs, which achieves a fixed switching frequency and superior system performance. An improvement of power quality is shown in this paper when compared to the conventional finite-control set-MPC. This paper examines the design and implementation of the modulation technique as well as presenting the simulation and experimental results to verify the technique's operation.