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Pulsewidth modulated (PWM) current-source converters (CSCs) have been attractive for high-power adjustable-speed machine systems with low carrier ratios. However, the high-order nonlinear model of CSC-fed machine systems, the distinct digital delay from the low carrier ratios, and the cross-coupling caused by coordinate transformation bring great challenges to design of high-performance stator current controller for such kind of machine systems. Firstly, this article derives the discrete-time complex-vector model for the CSC-fed permanent-magnet ac (PMAC) machine system with low carrier ratios considering the distinct digital delay and cross-coupling effect mentioned above. On that basis, the stator current controller is proposed with the modified controller parameters and the compensation technique to improve both dynamic performance and stability of the CSC-fed PMAC machine systems with low carrier ratios. The theoretical analysis and controller design process have been presented in detail to provide a guide for the model derivation and controller design. The experiments on a laboratory prototype are conducted to verify the effectiveness of the developed modeling and controller. [ABSTRACT FROM AUTHOR]

For the silicon photonics integrated circuits, the optical switch plays a vital role in many applications. Large scale integration requires low switching power and fast switching speed. However the switching time and switching power of silicon thermo-optic switch are typically limited to tens of micro-seconds and tens of milli-watts, respectively. In this paper, we designed and fabricated a silicon thermo-optic switch with spiral optical phase shifters, which can reduce the switching power from 21.5 mW to 8.73 mW compared to the optical switch with straight phase shifters. Furthermore, we optimized the pulse driving, we proposed the calculation formula of the pulse voltage, and the overall quantitative scheme of the pulse voltage and pulse width. By adopting the optimized pulse driving, the switching time is reduced from 27 μs to 4 μs. The proposed silicon thermo-optic switch unit with optimized pulse driving is very promising for the applications where large scale integration of optical switches is needed. [ABSTRACT FROM AUTHOR]

The grid inverters play an important role in renewable energy systems, transferring the dc power to the ac grid. Galvanic isolation is usually needed between the dc source and the grid due to safety reasons and grounding leakage current mitigation. In this article, a soft-switching isolated grid inverter is proposed based on the current-fed matrix-type configuration. The topology of this converter is composed of a current-fed H-bridge on the side of dc source and a direct matrix converter on the grid side, which are linked by a high-frequency transformer. The current-fed H-bridge on the primary-side can smooth the dc-source current and control the dc-source current directly. The avoidance of dc-link energy-storage element in the single-stage matrix converter can prolong the system's life. A space-vector-modulation-based soft-switching scheme is proposed for the matrix converter on the grid side and a model-based commutation method is adopted in the current-fed H-bridge on the dc side. With the proposed modulation methods, the soft switching can be realized for all devices in the converter. Finally, a laboratory prototype of the proposed converter has been built to verify the effectiveness of the proposed method experimentally. [ABSTRACT FROM AUTHOR]

Pulsewidth-modulated (PWM) current-source converters (CSCs) have the features of simple configuration, reliable short-circuit protection, and sinusoidal ac output voltages. The conventional space-vector modulation (SVM) scheme usually generates high-magnitude low-order harmonics in CSCs with low switching frequency. In this article, two modified SVM schemes, namely MSVM1 and MSVM2, are proposed to improve the harmonic performance for PWM CSCs in the high-power applications with low switching frequencies. The MSVM1 scheme focuses on eliminating the average dwell-time error of current vectors within each sampling period, while the MSVM2 scheme is targeted to achieve the accurate dwell time of current vectors as that of the natural sampling-based SVM scheme. The theoretical analysis and the calculation equations of dwell time are derived for both MSVM1 and MSVM2. The experiments are given to verify the effectiveness of the two modified SVM schemes in improving the harmonic performance of high-power CSCs with low switching frequencies. [ABSTRACT FROM AUTHOR]

This article proposes an integrated high-sensitivity temperature sensor based on SiO2-asymmetric Mach–Zehnder interferometer (AMZI) and thermal-expansion-induced stress of aluminum-SiO2. Mechanical analysis of this structure is carried out. The result shows that the SiO2 chip is compressed, and the waveguide length is decreased, leading to the central wavelength shift of the sensor. The sensitivity of the sensor can be customized by different arm lengths of the AMZI. The chip is fabricated using a standard planar lightwave circuit (PLC), and the aluminum alloy plate is glued to the chip using $\alpha $ -cyanaloc acrylic resin adhesive. The sensitivities of two sensors with different arm lengths are tested. The test results show the sensitivity reaches 6.86 and 54.2 nm $\cdot \text{K}^{-1}$ , respectively, which coincides with the theoretical analysis. With low cost and customizable sensitivity, this new device is applicable in many fields. [ABSTRACT FROM AUTHOR]

This article proposes an improved space vector modulation (SVM) for the current-source rectifier (CSR). Due to the overlap time during commutations of power switches, the pulsewidth-modulation (PWM) currents of CSR may suffer from a number of low-order (mainly fifth and seventh) harmonics, which seriously degrade the harmonic performance of currents and voltages on the grid side. Especially, the overlap-time effect becomes an important issue when the increased switching frequency is applied to CSR. To mitigate these low-order harmonics of the PWM converter currents resulted from the overlap-time effect, the relationship between the overlap time and the low-order harmonics in PWM currents and grid currents are analyzed at first. Then, the design process of the LC filter and the proposed SVM with optimal overlap-time distribution is presented in details. Finally, experimental results are conducted on a low power laboratory prototype to verify the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

Channel estimation is essential for millimeter-wave (mmWave) multiple-input multiple-output (MIMO) systems with hybrid precoding. However, accurate channel estimation is a challenging task as the number of antennas is huge, while the number of RF chains is limited. Traditional methods of compressed sensing for channel estimation lead to serious loss of accuracy due to channel angle quantization. In this brief, we propose a new iterative reweight-based log-sum constraint channel estimation scheme. Specifically, we exploit the structure sparsity of the mmWave channels by formulating the channel estimation problem as an objective optimization problem. We utilize the log-sum as a constraint, via optimizing an objective function through the gradient descent method, the proposed algorithm can iteratively move the channel estimated angle-of-arrivals (AOAs) and angle-of-departures (AODs) towards the optimal solutions, and finally improve the angle estimation performance significantly. In addition, to guarantee the accuracy of channel estimation, we introduce a dynamic regularization factor to leverage between the channel sparsity and the data fitting error. Numerical experiments demonstrate that the proposed algorithm achieves better convergence behavior than conventional sparse signal recovery approaches. [ABSTRACT FROM AUTHOR]

The silicon carbide (SiC) devices have attracted more and more attention due to the capability of withstanding higher blocking voltage, higher switching frequency, and higher temperature. However, challenges for SiC devices applied in voltage-source-inverter fed motor drives such as electromagnetic interference (EMI) issues and limited over-current capability still limit the further application of SiC devices. In this article, a novel SiC devices based zero-voltage-switching (ZVS) current-source-inverter (CSI) is proposed for permanent-magnet synchronous motor (PMSM) drive. The key is to propose an auxiliary resonant circuit, which achieves ZVS conditions for all switches in power circuits and reduces the dv/dt of high speed SiC devices. The resonant capacitor in the auxiliary circuit can clamp overvoltage caused by possible open-circuit faults. To further reduce the EMI, the random switching frequency pulsewidth modulation is designed for the proposed CSI motor drive. The system configuration, working principle, circuit design, and control schemes are described in detail. Both simulations and experiments are presented to verify the effectiveness of the proposed ZVS-CSI fed PMSM drive system. [ABSTRACT FROM AUTHOR]

In this article, the switching strategy and the remedial control scheme are studied for the cascaded current-source converters (CSCs) fed dual three-phase permanent-magnet synchronous motor (PMSM) variable-speed drives. An optimized space vector modulation (SVM) strategy is proposed to reduce the DC-link current ripple for the proposed drives system. In particular, this switching strategy can work effectively for motor drives under low speed with low back EMF, where there exists a large voltage difference between peak voltage values on the grid side and the motor side. Apart from that, a hybrid fault-tolerant control scheme is also designed for the open-phase fault in dual three-phase PMSM drives system, aiming at achieving small DC-link current ripple and torque ripple, low copper loss, and machine-friendly waveform quality. With the proposed optimized SVM and the hybrid fault-tolerant control strategy, the DC-link current ripple of the cascaded CSCs system can be effectively reduced and good operational performance can be obtained under both normal operation condition and open-phase fault condition. Experimental results are provided to verify the effectiveness of the proposed methods. [ABSTRACT FROM AUTHOR]

This paper addresses the problem of RGBD-based detection and categorization of waste objects for nuclear decommissioning. To enable autonomous robotic manipulation for nuclear decommissioning, nuclear waste objects must be detected and categorized. However, as a novel industrial application, large amounts of annotated waste object data are currently unavailable. To overcome this problem, we propose a weakly supervised learning approach which is able to learn a deep convolutional neural network from unlabeled RGBD videos while requiring very few annotations. The proposed method also has the potential to be applied to other household or industrial applications. We evaluate our approach on the Washington RGB-D object recognition benchmark, achieving the state-of-the-art performance among semi-supervised methods. More importantly, we introduce a novel dataset, i.e., Birmingham nuclear waste simulants dataset, and evaluate our proposed approach on this novel industrial object recognition challenge. We further propose a complete real-time pipeline for RGBD-based detection and categorization of nuclear waste simulants. Our weakly supervised approach has demonstrated to be highly effective in solving a novel RGB-D object detection and recognition application with limited human annotations. [ABSTRACT FROM AUTHOR]

In this paper, we are devoted to solving the problem of crossing surveillance and mobile phone visual location recognition, especially for the case that the query and reference images are captured by mobile phone and surveillance camera, respectively. Besides, we also study the influence of the environmental condition variations on this problem. To explore that problem, we first build a cross-device location recognition dataset, which includes images of 22 locations taken by mobile phones and surveillance cameras under different time and weather conditions. Then based on careful analysis of the problems existing in the data, we specifically design a method which unifies an unsupervised subspace alignment method and the semi-supervised Laplacian support vector machine. Experiments are performed on our dataset. Compared with several related methods, our method shows to be more efficient on the problem of crossing surveillance and mobile phone visual location recognition. Furthermore, the influence of several factors such as feature, time, and weather is studied. [ABSTRACT FROM PUBLISHER]

Occupancy awareness is important for appliance control, ubiquitous computing, and analytics for enterprize real estate. In this paper, a low-cost, battery-powered, wireless occupancy detector equipped with pyroelectric infrared sensor and wireless communication is presented with the aim of providing real-time and on-going occupancy estimation. The methodology adopted to detect occupancy status is based on the hidden Markov models (HMMs). HMMs are trained to statistically estimate the occupancy of a space through an expectation–maximization learning process. The advantage of this system is that the online algorithm reduces annoyance to the users by making it less likely to falsely switch OFF the appliances, and the offline algorithms improve the estimation of the total occupancy time. Simulation and experimental results were obtained to verify the proposed methods along with the limitations of the system. [ABSTRACT FROM PUBLISHER]