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In this paper, two novel approaches for identifying the synchronous generator (SG) parameters are presented. The proposed approaches use an experimentally obtained armature current during the short-circuit test as input data. Both approaches are simple, cost-effective, and practical since they do not require any additional equipment for signal generation nor applying any of the advanced control techniques. The first approach relies on fitting the analytical total armature current waveform with the experimental one, while the second approach relies on matching the observed waveform with an analytical waveform of asymmetrical and alternating components. Instead of traditional graphical methods typically used in standardized procedures, this paper also proposes a novel hybrid metaheuristic algorithm to identify the SGs parameters. The experimental verification of the proposed methods is carried out on 100 MVA SG at the Bajina Basta hydropower plant (HPP) in Serbia.

In this paper, a reduced order thermal observer with disturbance estimation is applied for temperature monitoring in a power electronics module. Although accurate thermal models of power electronics assemblies are widely available, based e.g. on computational fluid dynamics (CFD) solvers, their\ud computational complexity hinders the application in real-time temperature monitoring applications. This paper proposes a reduced order state space observer to provide a real-time estimation of temperature in power electronics modules. The observer is coupled with a disturbance estimator, to minimize the error caused by uncertainties in the model and unknown operating conditions.

Short-term household electricity load forecasting is important for utility companies to ensure reliable power supplies. Traditional methods for load forecasting relied on historical records from one single data source and have limitations with insufficient or missing data. Recently, an emerging family of machine learning algorithms, multitask learning (MTL), has been developed and has the potential for load forecasting. By MTL, the electricity consumption data from multiple communities can be fused to improve forecasting accuracy. However, appropriate modeling of the relatedness to enable the between-community knowledge transfer remains a challenge. This paper proposes an improved MTL algorithm for a Bayesian spatiotemporal Gaussian process model (BSGP) to characterize the relatedness among the different residential communities. It hypothesizes on the similar impacts of environmental and traffic conditions on electricity consumption in improving short-term load forecasting. Furthermore, this paper proposes a low-ranked dirty model along with an iterative algorithm to improve the learning of model parameters under an MTL framework. This paper uses a real-world case study from two residential communities in Tallahassee, Fl, USA, to demonstrate the method effectiveness. The proposed method significantly outperforms state-of-the-art forecasting methods and effectively captures the relatedness to provide between-community knowledge transfer compared with other MTL methods.

The concept of energy Internet (EI) is very promising due to its ability to integrate distributed generators and storage devices. Energy routers (ERs) enable highly efficient, reliable, and flexible power system operation. To dynamically control and optimize energy flow in EI, an extensive communication is required. Considering the diversity of generators and ERs, it is crucial that such communication is achieved in a standardized and interoperable way. In this paper, an improved energy routing algorithm and its impact in EI operation are demonstrated. Furthermore, a full communication solution is developed for ERs and their interaction with grid operator. This paper proposes an International Electrotechnical Commission (IEC) 61850 communication-based power routing algorithm in microgrids. Optimal selection of source and routing path is achieved according to the proposed algorithm and communicated to the ERs via IEC 61850 based communication. The effectiveness of the proposed IEC 61850 communication-based routing algorithm is verified on network emulation platform comprising of IEC 61850 emulator tools and network simulator tool.

Smart buildings form an integral part of the smart grid that lowers electricity cost. This objective can be achieved by using suitable enhanced algorithms and techniques. The motivation of this paper is the request for an economical decision-making system from a commercial company in Singapore. This paper presents an economical building management system (EBMS) concept inspired by the building management system and machine learning. EBMS improves the decision-making process through rule-based algorithm within the system. Machine learning algorithm is included as part of EBMS to enhance the computational calculation for the electricity distribution. It includes the function of self-making decision for purchasing electricity based on forecasting system for electricity price or real-time electricity price data when facility managers are not present. EBMS uses multiagent system to communicate, interact, and negotiate with multiple agents for energy supply and demand in the building. Simulation studies have shown the potential of EBMS concept to provide a cost reduction solution up to 61.42% savings for smart buildings. Better electricity purchasing contract option can be decided based on the forecasting system for building power consumption.

Piezo-driven precision positioning platforms with large stroke are greatly demanded in both scientific research and industrial applications. Although various principles have been proposed to design piezo-driven positioning platforms, the problem of backward motion commonly exists, greatly hindering their applications. To suppress the backward motion, in this paper, an idea by generating a forward frictional force to balance the reversed frictional force was proposed. Correspondingly, a specific arc-shape flexure hinge was designed to generate the forward frictional force via its elastic recovery. To verify the feasibility of the proposed idea, a positioning platform with alterable initial gap between contact surfaces is designed by the parasitic motion principle (PMP). By measuring the output displacement under various initial gaps, a critical initial gap was identified, at which the positioning platform could output stepping displacement without backward motion. Under this critical initial gap, effects of driving voltage and frequency on the backward motion are further investigated. In addition, the natural frequency and loading capacity of the positioning platform are tested. This paper confirms that using PMP, it is feasible to design piezo-driven positioning platforms with completely suppressed backward motion, which would enhance the applications of the PMP and PMP positioning platforms.

The ability to monitor the quality of the metal forming process as well as the machine's condition is of significant importance in modern industrial processes. In the case where a physical device (i.e., sensor) cannot be deployed due to the characteristics of the system, models that rely on the estimation of both the applied force and the dynamic behavior of the machine (i.e., system) are adopted. The development of such models and the corresponding algorithms used to estimate the above-mentioned quantities has attracted the interest of the community. The main contribution of this paper is the estimation of a servo press force by employing a novel dual particle filter based algorithm, achieving a maximum relative error in the force estimation of 3.6%. Moreover, to address real-time performance requirements, this paper proposes a field programmable gate array based accelerator that improves the sampling rate by a factor of 200 compared to a processor-based solution, thus enabling the deployment of the system in many realistic scenarios.

In order to improve the performance of interior permanent magnet synchronous machine (IPMSM) based on space voltage vector modulation schemes, this paper presents a highly accurate online method to find the proper maximum-torque-per-ampere (MTPA) angles. This algorithm fully considers the nonlinear characteristics of the d -axis inductance, q -axis inductance, and permanent magnetic flux together. Additionally, the influences of temperature are taken into account. In this paper, the proposed method injects a small virtual angle signal into the current angle mathematically to track the stator current reference angle that is close to real MTPA points. Moreover, following a theoretical analysis method, the error of the virtual signal injection method is analyzed. Then, based on the results of error analysis, this paper proposes a compensation strategy that can significantly reduce the current angle error between the tracking point and real MTPA point. At last, various experiments on an IPMSM test bench verify the proposed control technique and overall performance.

The widespread application of nonlinear power electronic devices in residential loads has resulted in significant harmonic distortions. Harmonic source modeling is of great importance since it is a prerequisite to estimate the harmonic pollution. In this paper, a dynamic harmonic coupled matrix model (HCMM) is proposed for the nonlinear home appliances. This model is adaptive to the load supply voltage conditions; therefore, the dynamic harmonic generating characteristics of nonlinear home appliances can be demonstrated by the proposed HCMM. Moreover, the HCMM derivation process is based on measurement, independent of the load equivalent circuit, which makes the proposed method most suitable for nonlinear home appliances with unknown circuit topologies. The widely linear complex partial least squares method, which has a fast speed and high robustness, is used to estimate the HCMM. A procedure to establish the HCMM for multistate home appliances is also proposed in this paper. Lab experiments were performed to verify the accuracy and validity of the proposed methodology. The aggregate harmonics caused by multiple nonlinear residential loads have been analyzed based on the proposed HCMM.

In past years, LLC resonant converters have become a mainstream topology for dc–dc power conversion due to their advantages, such as the superior efficiency obtained with the soft switching of MOSFETs. In order to further improve the efficiency of the converter, synchronous rectification (SR) can be implemented as an alternative for diode rectification. As a result, the vast majority of the literature related to this field of study presents different LLC SR control algorithms, which aim to improve the operation of the rectification. Unlike prior work on SR controllers, this paper contributes to the area of power loss estimation using rectifier current equations (RCE). The developed method based on time-domain analysis of SR currents provides a new analytical framework to characterize the behavior of SR. Implications in SR power losses of different time delays are investigated using the developed loss estimation method. In addition, different converter design parameters, such as choice of inductance ratio, can be analyzed. The RCE captures the true discontinuous and complex behavior of SR, which is often oversimplified by the conventional first-harmonic approximation (FHA). As a result, the proposed method facilitates the design of LLC resonant converters and provides increased precision in SR power loss estimation when compared to FHA, and in a considerably faster fashion when compared with precise yet computationally intensive simulation software. This paper is validated with simulation and experimental results.

In multi-phase AC power systems, e.g. aircraft electric power systems (EPS), the proximity effect between the feeder cables can be severe and complex due to the tightly wired cable bundles. Simulation software is widely used to analyze such effects in order to guarantee proper system operation, but it is highly time consuming and requires extensive computational resources. Accordingly, this paper proposes an analytical calculation method for estimating the ac resistance of closely bundled power cables, namely multi-conductor cables. Simulation and experimental tests are performed to validate the effectiveness and accuracy of the method, showing that the algorithm developed in this paper is easy to implement with a minimum accuracy of 92% in all the tests. It allows online estimation of cable resistances, which can be beneficial for advanced system monitoring and management to enhance safety and reduce losses. Aircraft EPS and cables are used as the example in this paper, while the proposed method is also applicable for other applications, such as shipboard EPS, renewable energy parks, or microgrids where multi-conductor cables are used.

This paper presents an improved equivalent input disturbance (EID) approach to deal with exogenous disturbances and system nonlinearities. The disturbances and nonlinearities are regarded as a lumped disturbance on the control input channel. The EID approach, which has a state observer and an EID estimator, is used to estimate the lumped disturbance. There is a constraint between the observer and the estimator on the design of the control system for the conventional EID approach. A stable zero was added to the estimator to remove the constraint and to improve the stability of the system in this paper. This ensures that the observer and the estimator can be designed independently. An analysis of the improved EID approach explains the mechanism of disturbance rejection. The simulation and experimental results of position control of a ball-and-beam system demonstrate the validity of the method.

This paper addresses the problem of how to estimate the remaining useful life (RUL) for partially observed linear stochastic degrading systems with survival measurements. The motivation of this paper arises from two engineering facts—the measured degradation signals are taken from a survival degradation path and the degradation progression of the system is inevitably affected by multisource variability. To do so, we first revisit the linear degradation modeling framework driven by the Wiener process to account for the above two facts, and a new state-space model with non-Gaussian state transitions is constructed based on the constraint of survival measurements. Then, the particle filtering algorithm is applied to real-time estimate the non-Gaussian degradation state and random-effect parameter from measurements. Furthermore, we derive the probabilistic distribution of the RUL which can be real-time updated based on the available measurements. To apply the presented method, a two-stage estimation procedure based on particle expectation maximization algorithm is presented to determine and update the model parameters. The novelty of the presented method is to exclude the probability of failure before the current monitoring time and account for both impacts of the multisource variability and surviving degradation path on the RUL estimation. Finally, we demonstrate the proposed approach by a case study on gyros in the inertial platform.

This paper presents an integrated control strategy for a starter/generator (S/G) system based on five-phase dual-stator winding induction machine (FPDWIM). The FPDWIM has a cage-type rotor and two sets of stator windings. One is a five-phase control winding (CW), and the other is a five-phase power winding (PW). In the starting mode, the FPDWIM works as a motor. The CW provides both active power and reactive power to drive the engine. In the generating mode, the CW mainly handles reactive power while the PW outputs active power. To achieve the integration of the starting and generating controls, indirect CW-flux-oriented control (ICWFOC) to operate in both starting and generating modes is proposed in this paper. In starting mode, the CW current and flux are controlled to output a constant starting torque; while in the generating mode, both CW and PW dc bus voltages are regulated. In this way, the principles and structures of the control strategies in both modes are compatible, resulting in a simpler implementation and improved performance. With the proposed control strategy, the system can complete the starting–generating operation with a smoother transition process. Simulation and experimental results are compared to validate the proposed control strategy.

This paper investigates a controllable fluke's regulation effect on the gliding motion of a self-propelled robotic dolphin in both theory and practice. In theory, based on a dynamic model, the gliding equilibria is first analyzed. Through deriving the explicit expressions of the pitch angle, gliding angle, and velocities, we explore how the deflection angle of the controllable fluke changes the gliding performance. Then, aided by these theoretical analyses, a pitch control strategy relying on the fluke is constructed. In simulations, the robotic dolphin is able to track a given pitch angle during gliding, directly through adopting this control strategy to regulate the fluke's deflection angle. Furthermore, extensive gliding experiments in different fluke's deflection angles are carried out. From the statistical data, we further explore the remarkable effects of the controllable fluke on the gliding performance in practice. Besides, the other pitch control experiment is also executed to validate the effectiveness of the proposed control approach. The results of this paper shed light on improving the gliding performance of the robotic dolphin in future mechanical design and gliding control.

Electro-hydrostatic actuator (EHA) is a highly integrated local hydraulic actuation system for more electric aircraft (MEA). However, the motor heating has always been the bottleneck in actual applications. In this paper, a novel energy-recovery EHA (ER-EHA) with specific hydraulic energy recovery unit is proposed to solve the problem. ER-EHA can reduce the heating of the motor, which is beneficial to improve the reliability and mean time before failure of the system. Besides, the power resistor is eliminated in the new system, so the volume of the system is reduced, and the power-to-weight ratio of the system is improved, which satisfies the needs of MEA. Simulations can prove the effect of energy recovery unit. To show the efficiency of our proposed structure, a specific test bench called redundant degree heterogeneous drives loads test bench is designed, and experiments are carried out in this paper. The results reflect its contribution to motor heating reduction.

Finite set model predictive torque control (FCSMPTC) of induction machines has received widespread attention in recent years due to its fast dynamic response, intuitive concept, and ability to handle nonlinear constraints. However, FCSMPTC essentially belongs to the open-loop control paradigm, and unmatched parameters inevitably cause electromagnetic torque tracking error. In addition, the outer loop (i.e., the speed loop) based on a proportional-integral (PI) regulator cannot achieve optimal control between speed dynamic response and torque tracking error compensation. The traditional control paradigm is abbreviated as PI-MPTC. In order to solve the aforementioned problem, this paper proposes active disturbance-rejection-based model predictive torque control (ADR-MPTC). First, the influence mechanism of mismatched parameters on torque prediction error in PI-MPTC is studied, and then the performance of a traditional PI regulator used to compensate for torque prediction error is analyzed. Second, this paper introduces several parts of the proposed ADR-MPTC, including the design of the torque prediction error observer, nonlinear prediction error compensation strategies, an enhanced predictive torque control, and a simplified full-order flux observer. Finally, PI-MPTC and ADR-MPTC are studied experimentally. The experimental results show that compared with PI-MPTC, ADR-MPTC performs better in dynamic and steady states, and has stronger robustness.

Series-connected-based offshore wind farms can eliminate bulky central offshore converters, transformers, and platforms. In a series-connected-based offshore wind farm, the dc voltage of the converters should be changed within a large range to control the dc-link voltage (grid side) and maximize wind power acquisition (generator side). In this paper, the full-bridge-based modular multilevel converter (FB-MMC) is proposed as grid- and generator-side converters. The dc voltage of the FB-MMC can vary in a large range because the full-bridge submodule (FBSM) is used. The control method of the FB-MMC in a series-connected-based offshore wind farm is different from those of traditional ones. The dc current control and capacitor voltage balance control are proposed in this paper, with which the FB-MMC can operate normally in the series-connected offshore wind farm. Moreover, the capacitor ripple voltage in the generator-side FB-MMC is studied. The result shows that the capacitor in the FBSM can be designed in rated power and frequency, and it will be feasible when the power and frequency decrease. Simulation and experiment results verify the feasibility of the proposed configuration and the corresponding control algorithm.

The randomly switching communication topologies are of particular interest for researchers in the field of consensus control since the communication connection among multiple agents can randomly change with time and space. Following this pattern, this paper models the communication topology with the Markovian randomly switching graphs, since the Markovian chain process is usually used to model the network with Rayleigh fading channel. In this stochastic framework, this paper focuses on the consensus control and performance improvement problems of grouped agents with linear or linearized nominal dynamics. To solve this problem, a class of state-feedback controllers is proposed under the assumption that all the state measurements are available. These controllers are intrinsically distributed since they solely require the relative information between neighboring agents. Moreover, the notion of $\mathcal {H}_{\infty }$ ( $\mathcal {H}_2$ ) stochastic consensus region integrated with transient performance is defined to measure the robustness of the proposed controllers with respect to the communication topologies. This paper theoretically shows that these controllers yield unbounded consensus region, which implies that they are well-designed. Furthermore, these controllers can improve the $\mathcal {H}_{\infty }$ , $\mathcal {H}_2$ consensus, and transient performances of agents subject to external and initial-state disturbances. At the end of this paper, numerical simulations and experiments are performed to verify the theoretical results.

In order to suppress the torque ripple of an open-end winding permanent-magnet synchronous machine (OEW-PMSM), a q -axis current injection method is typically employed but the disturbances caused by the third flux linkage parameter mismatch can augment the torque ripple. To solve this problem, in this paper, first, a zero-sequence current (ZSC) and zero-sequence back-EMF observer (ZCBO) are proposed based on an adaptive sliding mode control, which is able to simultaneously estimate ZSC and zero-sequence back EMF under varying conditions. Based on this ZCBO, the estimated ZSC and zero-sequence back EMF could compensate for the one-step control delay and suppress the aforementioned disturbances. Second, although central hexagon modulation is employed in the predictive current control (PCC) scheme, zero-sequence voltage (ZSV) still exists in the zero-sequence path due to the dead time of the inverter, affecting the predictive accuracy of the ZCBO. To accurately establish the ZCBO, the ZSV caused by the dead time of the inverter is considered in the ZCBO. Finally, a comparative study of two types of methods is presented, and simulations established by MATLAB software and experimental confirmations are carried out to verify the effectiveness of the proposed PCC scheme in this paper.

This paper proposes a sensorless vibration harmonic frequency estimation for a servo system driven by a permanent magnet (PM) synchronous machine. Traditional vibration harmonic estimation relies on the measurement using external sensors. An accelerometer is typically installed in the servo system to measure the vibration harmonic signal. Because the accelerometer must be attached on the visibly vibrational location inside the system, this vibration detection results in both issues about installation and reliability. To overcome this drawback, this paper proposes a disturbance observer to estimate the vibration harmonic by using current and position signal. A real-time signal process is developed to identify the vibration frequency from estimated harmonic. A servo system with a 400-W PM machine is built to verify the proposed vibration harmonic and frequency estimation. This paper includes the comparative evaluation between the accelerometer-based vibration harmonic measurement and the sensorless estimation.

This paper proposes a family of single-stage converters consisting of three different converters, each of which is able to produce a variety of waveforms through the waveform-subtraction technique. We brand this converter family as waveform-subtraction based single-stage converter (WSSC). By using only a single-stage converter, the proposed waveform generation technique is able to realize dc–dc–ac conversions and suppress input current ripple, meeting the needs of modernized power grid with renewable energy sources. At the same time, converters in this WSSC family are capable of generating a range of shapes, such as triangular, rectangular, and sawtooth waveforms, with simple structures, demonstrating its suitability of being applied in the electrochemical industry, e.g., in the electroplating process. Furthermore, the proposed family converters also realize substantially better input current ripple suppression compared to other conventional converters. In order to prove the validity and efficacy of the proposed WSSC and the theory underpinning it, in this paper, extensive simulations and analyses are conducted to verify the theoretical foundation of the proposed WSSC strategy, and the prototype of a converter from the proposed converter family is built and tested in our laboratory, which validates the functionality of the WSSC.

With the proliferation of distributed generation in distribution networks, quickly and smoothly converting to a state of regional autonomy in the case of distribution network failure is one of the main challenges for the stable operation of a multimicrogrid (MMG). To address the aforementioned problem, this paper proposes coordinated control of the passive transition from grid-connected to islanded operation for a three/single-phase hybrid MMG. Under the premise of fully considering the constraints on the tie-line transfer power undertaken by the master power supply (MPS), the following two scenarios regarding safety and emergency are formulated: 1) when the output power of the MPS is in the safe range, the proposed strategy coordinates the energy storage (ES) in each submicrogrid (SMG) to achieve power balance; 2) when the output power is in the emergency range, this paper proposes a three-phase balance method based on a bubble sort to realize the combination optimization of the single-phase source-load-storage (SLS) and a fast power regulation method based on implicit enumeration for the SLS to reduce the tie-line transfer power, which could prevent failure of the mode transition from power overload. The test results verify the effectiveness and feasibility of the proposed coordination strategy.

This paper presents an optimization method for selective harmonic elimination in a cascaded multilevel inverter using teaching–learning-based optimization (TLBO). The main objective in selective harmonic elimination (SHE) strategy is to eliminate low-order harmonics by solving nonlinear equations and reaching optimal solution, while the fundamental component is satisfied. In this paper, in one side, the influence of optimal dc sources is investigated to reach the SHE goal, and in another side, comparing optimization methods is considered. In this paper, the TLBO as a recently emerged nature-inspired algorithm is presented to provide better results for the SHE in comparison with genetic algorithm, artificial bee colony, imperialistic competitive algorithm, harmony search, ant colony optimization, particle swarm optimization, and differential evolution. For better comparison of those methods and influence of optimal dc sources, 5-, 9-, and 15-level inverters are chosen and MATLAB software is used for optimization. Simulation results show the superiority of TLBO, higher precision and probability of convergence than other mentioned algorithms. Finally, to validate the influence of optimal dc sources and the accuracy of TLBO results, the experimental setup is conducted for a 5-level cascaded H-bridge inverter with optimal dc sources.

This paper presents a novel motion planning and tracking framework for automated vehicles based on artificial potential field (APF) elaborated resistance approach. Motion planning is one of the key parts of autonomous driving, which plans a sequence of movement states to help vehicles drive safely, comfortably, economically, human-like, etc. In this paper, the APF method is used to assign different potential functions to different obstacles and road boundaries; while the drivable area is meshed and assigned resistance values in each edge based on the potential functions. A local current comparison method is employed to find a collision-free path. As opposed to a path, the vehicle motion or trajectory should be planned spatiotemporally. Therefore, the entire planning process is divided into two spaces, namely the virtual and actual. In the virtual space, the vehicle trajectory is predicted and executed step by step over a short horizon with the current vehicle speed. Then, the predicted trajectory is evaluated to decide if the speed should be kept or changed. Finally, it will be sent to the actual space, where an experimentally validated Carsim model controlled by a model predictive controller is used to track the planned trajectory. Several case studies are presented to demonstrate the effectiveness of the proposed framework.

This paper presents the development of a Class-D full-bridge zero-voltage switching (ZVS) inverter, applicable to wireless power transfer (WPT) systems, operating at 13.56 MHz switching frequency with dynamic dead-time control (DDTC). Resonant-coupled WPT systems are being designed at ultrahigh switching frequencies to reduce the size of the wireless link and the passive components. Maintaining ZVS while controlling the output power delivered to a fixed or variable load is one of the major challenges of designing inverters at multi-MHz switching frequencies. DDTC is the approach deployed in this paper to sustain soft switching of a Class-D full-bridge inverter over the full range of output power while regulating the input dc bus voltage. Simulation results are presented to show that dynamically controlling the dead-time during input dc bus voltage variations reduces switch-node voltage overshoot, prevents large current spikes in the switching devices, and reduces associated high switching loss. Practical results obtained show that DDTC reduces switch-node voltage overshoot, increases the inverter efficiency, and reduces the steady-state temperature of the inverter during output power regulation.

This paper presents a 5-level inverter topology for open-end induction motor drives by using a single dc source. The open stator windings of the drive are supplied with a 3-level flying capacitor inverter from one end and capacitor-fed 2-level inverter from another end. The voltage ratio of the dc link to the capacitor in 2-level inverter is maintained at 4:1 ratio to generate five-level voltage output. The capacitor in 2-level inverter is balanced by the switching redundant vector combinations from both the inverters while the floating capacitors in the 3-level inverter are balanced by using redundant switching states. The proposed topology gives 5-level operation with less number of floating capacitors and power semiconductor switches compared to other existing topologies. Also, the balancing of the capacitors is independent of load power factor and modulation index. Further, the generalization of the proposed dual inverter scheme for any n -level inverter is also included in this paper. The experimental results and required analysis are also presented to validate the inverter scheme.

Satellite dc–dc power converters are required to have electromagnetic interference (EMI) compatibility as well as high reliability. The requirement of high reliability limits the complexity of the structure as well as the number of low-reliability components. In this paper, a conventional active-clamp-forward (ACF) topology is examined for a satellite converter owing to its relatively simple structure, small number of components, and good clamping capability regarding its switch voltage stress. However, it has a pulsating input current shape, a high di / dt level, and high switch voltage stress, which are disadvantageous with regard to the EMI filter size and high-input-voltage converter applications. To overcome these drawbacks, a new ACF topology with a continuous input current waveform is proposed. In the proposed waveform, the voltage stresses on the main switches are relieved, which is crucial to ensure the reliability of satellite FET switches, by utilizing a two-series connected structure. These features allow the proposed converter to serve as a high-input-voltage, high power-density satellite converter. In this paper, 100 W prototype converters with 50 V inputs operating at 300 kHz are built with a high power density of 47.9 W/in3. Experiments on these prototype converters are carried out to verify the features.

This paper describes the tuning process of the proportional-resonant controller, taking into account the significant computational delay from the digital control system. Different structures of the controller and related contradicting results are discussed. Particular attention is paid to the stability domain and its dependence on different parameters of the proportional-resonant controller. The main outcome of this paper consists in the tuning approach guidelines for selection of controller parameters in case of significant digital system delay. An optimal controller structure and start-up current optimization are proposed. All results are confirmed by simulation and experimental setup.

This paper presents a model predictive control for a six-phase permanent magnet synchronous machine (PMSM) with a reduced-dimension cost function. Only the variables in the harmonic subspace are included into the cost function, while the energy conversion related variables are excluded. This is achieved by using the deadbeat direct torque and flux control method to obtain a reference voltage vector and then to track the torque and stator flux properly in the energy conversion related subspace. Then, according to the position of the reference vector, the appropriate prediction vectors can be determined. Subsequently, a reduced-dimension cost function including only the harmonic constraints is defined to evaluate the feasible prediction vectors. In this way, the predictive model and the cost function are simplified without redundant constraints. Meanwhile, the torque and flux can be regulated satisfactorily, and the harmonic currents are suppressed effectively. Finally, experimental results of the proposed method and the conventional model predictive torque control are presented in this paper to verify the validity of the proposed method.

Active magnetic bearing is a core technology for high-speed rotational machines. Power electronics converter as the active magnetic bearing drive is the actuation unit and its topology highly impacts the performance of the bearing system. This paper introduces the progress of topology of active magnetic bearing drive. The initial topology of an H-bridge does not sufficiently utilize the power electronics devices. The topology with half-bridge and shared phase-leg has been proposed as the fundamental topology. In this paper, two approaches of novel magnetic bearing drive topology modification have been developed on the basis of the fundamental topology. In the first approach, central phase-leg for multiaxis magnetic bearing drive can be further shared and the power electronic devices can be globally optimized in the whole system. Further, a topology with current in the reverse direction can reduce the central phase-leg current rating and power losses. In the second approach, fault-tolerant magnetic bearing drive topology has been developed on the basis of the fundamental topology, too. It can ride-through the open-circuit fault of power electronics switch-in operation and keep levitation for the magnetic bearing. The series work of novel topologies can improve the performance of an active magnetic bearing system in application.

The wind energy generating system (WEGS) in this paper, aims to provide the required active peak power without high frequency fluctuations even under variable wind speed conditions. The generator speed is adjusted according to the intermittent wind speeds through two voltage source converters (VSCs) connected back to back, namely, machine-side VSC (MSVSC) and utility grid side VSC (UGVSC) across the dc-link capacitor. In this paper, the hybrid generalized integrator control is proposed for switching UGVSC and providing dc offset rejection and immunity against oscillatory errors due to subharmonics, thereby improving the power quality (PQ). Fuzzy logic controller (FLC) is implemented for the speed control of the salient pole synchronous generator (SG) driven by the wind turbine. The FLC provides the tracking of the reference speed under high overshoot transient conditions and narrow bandwidth. The switching of MSVSC is obtained by field oriented control. The dynamic performance is improved by the wind feed-forward term, which reduces the oscillation, ensuring balanced and sinusoidal grid currents. The generated power from the WEGS is fed to the grid. The weak grid conditions, namely, grid voltage unbalance, voltage sag, voltage swell, and grid voltage distortion, are considered. The performance of the system is tested on a laboratory prototype. Test results provide the effectiveness of the system with increased wind penetration and performance under weak grid conditions. Moreover, improving the PQ, the grid current total harmonic distortion meets the requirement of IEEE-519 standard, and is found to be less than 5%.

This paper proposes a new force estimation approach based on the dither periodic component elimination (DPCE) Kalman filter and the disturbance observer (DOB) for realization of a fine sensorless force control system under the existence of static friction. A dither signal is inserted to the desired reference signal to eliminate the effect of static friction of a ball-screw system. The DOB estimates the periodical torque caused by dither signal. The DPCE Kalman filter uses the periodical torque for the estimation of the high-order torque responses to achieve the torque estimation with the elimination of periodic component. The problem of noise in the force sensation and the effect of static friction are reduced effectively by using the DPCE Kalman filter. Therefore, the bandwidth of the force sensing is increased and the wide band DOB is achieved. As a result, this paper has accomplished the fine sensorless force control realization. The force control experiments of a ball-screw system are carried out to verify the validity and effectiveness of the proposed method.

Compared with the conventional two-level dual-active-bridge (DAB) dc–dc converter, the three-level DAB converter could operate with lower voltage rated switching devices and provide more control degrees of freedom, which enhances the control flexibility. This paper proposes a modulation strategy with five control degrees of freedom. In the previous work with multiple control degrees, the optimization strategies for efficiency or inductor current minimization are investigated; however, these strategies all need detailed mode analysis and complex mathematical optimization tools to obtain the optimal duty cycles. In this paper, an optimization strategy for the root-mean-square value of the inductor current is proposed. This method extracts the fundamental and third-harmonic components from the high-frequency voltages on both sides and adjusts the amplitude of the bridge voltages by the vector diagram to obtain the optimal duty cycles. The inductor current can be reduced significantly at light loads with the proposed strategy, so the efficiency of the converter can be improved. Moreover, the optimization process does not need the detailed operation analysis of the converter, nor does it require the complex mathematical optimization tools. Finally, the performance of the three-level DAB and the optimization strategy are verified by the experimental results.

This paper analyzes different stator windings configurations for permanent-magnet synchronous machines during the presence of a stator turn fault. Due to the inverter pulsewidth modulation, the fault commonly occurs in variable-frequency permanent-magnet machine drives. In this paper, two types of windings are compared to identify key machine topologies that can achieve the reduced influence of the turn fault. When the machine is operated in real time, the windings with separated neutral points reduce the torque ripple caused by fault-reflected flux harmonics. Analytical models based on equivalent circuits are developed to predict the machine flux and torque waveform during the presence of the turn fault. All developed analytical models are verified by the finite-element analysis and experimental results on a 750-W surface permanent-magnet machine prototype.

This paper improves the position sensorless drive by sensing actual machine phase voltages. A high-bandwidth phase voltage measurement is developed for pulsewidth modulation (PWM) voltage inverters. On the basis, the actual phase voltage is obtained based on the digital integration of PWM voltage using the capture modulator in existing drive microcontrollers (MCU's). Comparing to existing phase voltage measurement, no separated A/D converter and communication hardware are required because PWM pulses are directly measured using MCUs. However, for standard machines without neutral points, only line-to-line ac PWM voltages can be measured for the phase voltage reconstruction. Since the capture based on transistor-transistor logic (TTL) logics receives only digital signals, a preprocess circuit to convert ac PWM line voltages to equivalent digital signals is proposed. This paper clearly explains the voltage sensing hardware using MCU capture modulator. According to experimental results, a 150-MHz sampling rate for phase voltage measurement is achieved based on the proposed capture-based voltage measurement. Although the physical limitation of back electromotive force estimation still appears, the proposed phase voltage measurement substantially enhances the sensorless drive performance at low speed.

The stability margin is an important attribute for the robustness analysis of the closed loop in a control system design, which indicates the tolerant-ability of the closed-loop stability to system uncertainty (or fault). Seeking to develop an advanced data-driven monitoring and management framework for control performance (especially for robust stability) of the closed-loop system, this paper presents a study on the data-driven realization of the closed-loop stability margin, and its application to control-performance-oriented process monitoring. Specifically, without identifying the system parameters, a data-driven realization of the stability margin is first determined based on the identified multiplication operator of the closed-loop transfer function matrices using time-domain closed-loop measurements. Second, a control-performance-oriented process monitoring approach is proposed based on the determined data-driven realization of the stability margin. The contributions of this paper will bridge the gap between the model-based robustness analysis/design and the data-driven techniques for the future research. The main results of this paper are verified and demonstrated through the case studies on a dc motor benchmark system.

In this paper, a new modular and active snubber cell, easily applicable, and attractive for converters, especially have many switches proposed. This snubber cell is implemented on the single phase of a grid-connected three-phase T-type three-level inverter (T-3LI). In this new converter, the main switches turn- on under zero-voltage transition and turn- off under zero-voltage switching (ZVS). Also, auxiliary switches turn- on under zero-current switching and turn- off under ZVS. All snubber diodes operate under soft switching (SS). There are no additional current and voltage stresses on the main switches. During an SS operation, the switching energies are transferred to a dc voltage source. Then, these energies are processed to input with an independent dc–dc converter. Thus, all switching energies are recycled. In this paper, the principle operation and steady-state analysis of the modular and active snubber cell for a single-phase T-3LI are presented and experimental results, rated 1 kW and 100 kHz, are provided to verify theoretical analysis.

Metallic joints are created in multivariable gas metal arc welding process by maintaining a balance between the quantum of heat generated and the feeding rate of electrode metal to the weld gap. The wire feeding control is often independently handled. The wire feeder unit should be simple, low cost, and capable of producing accurate speed. Arc welding controllers are often kept in clumsy conditions and the wire feeder unit is located close to the welder, could be much away from the controller. To reduce interconnections, separate sensing element for speed feedback should be avoided. Due to their negligible electrical and mechanical time constant, the pancake-type permanent magnet dc motor is suitable for wire feeding, where sensing of back electromotive force (EMF) for feedback is easy. When high frequency pulsewidth modulation (PWM) controller is used, the sensing of back EMF gets complicated. This paper explores the constraints on the choice of PWM frequency along with its maximum pulsewidth for different types of dc motors. It further elaborates comparatively on the choice of suitable control function for generating accurate speed control of wire feeding using back EMF as feedback. Finally, this paper also details the experimental results using the proposed control function.

This paper proposes a mutual calibration strategy for multiple current sensors in an electric vehicle motor drive. The motor drive usually consists of three current sensors, i.e., a dc-bus current sensor and two phase current sensors. Due to the aging effect and harsh operating environment, the accuracy uncertainty issue is inevitable in these crucial sensors, which results in poor driving performance. In this paper, the detection voltage injection (DV-Injection) method is proposed for mutual calibration of the aforementioned current sensors. Two opposite basic vectors are set together to detect and eliminate the offset error of the dc-bus current sensor. Then, both the directly measured phase-current values by the phase-current sensors and the indirectly measured values by the dc-bus current sensor are sampled. These values are utilized for mutual calibration of the phase-current sensor offset errors and scaling error differences among all the current sensors. Meanwhile, the DV-Injection process is only applied in the period of calibration process, whereas in the remaining intervals the space vector pulsewidth modulation technology is utilized. Finally, the effectiveness of the proposed scheme is verified by simulation study in MATLAB/Simulink and experimental results on a 5-kW interior permanent magnet synchronous motor motor prototype.

Active flow control by means of plasma actuators has potential advantages over conventional strategies, e.g., mechanical or hydraulic components may be replaced by lightweight, compact, fast response plasma actuators. In this paper, several designs of dielectric barrier discharge (DBD) plasma actuators are presented for aerospace applications and the focus is on the associated feedback control implementation. The interdisciplinary nature of aerodynamic feedback control with plasma, however, makes direct experimental demonstrating an outstanding challenge. Here, we propose a realistic experimental control implementation afforded by commercial off-the-shelf electric products and the major achievement is the detailed instruction (in both electricity and aerodynamics) and the successful demonstration of the closed-loop design in controlling the dominant modes from a cylinder flow setup. The essence of our approach is to drive DBD plasma actuations by a downstream sensor and excite aerodynamic velocity perturbations, which are further amplified on the shear flow from the cylinder, leading to airflow structures, such as vortex roll-up and randomization, which are measured by the downstream sensor to complete the whole loop. We benchmark our control approach by comparing to the predicted dominant frequencies of the controlled flow system, which can be achieved by the Barkhausen stability criterion after establishing the corresponding transfer function of the whole flow control system. Overall, this paper shall assist a host of new applications in aerospace applications in the near future.

In recent years, there has been an increasing interest in hand movements in various application fields. However, the human hand is too dexterous and only has limited space. Developing a proper method to monitor and capture hand motion is meaningful. Conventionally, an optical measurement method is widely used to capture hand gestures. Nevertheless, this method is costly and has the problem of line-of-sight shielding. In this paper, a sensor fusion algorithm is proposed to calculate a more accurate result by calculating acceleration, magnetic field strength, and angular speed from the inertial measurement unit (IMU). The core concept of this algorithm is based on the idea of feedback control. To validate the performance, the active rotary platform is set up to compare the measured results to the references directly. Most of the error results are less than 3°, and the standard deviations are less than 1°. The measurement results ensure the feasibility of the inertial measurement method with the sensor fusion algorithm proposed in this paper.

This paper presents a unified second-stage LC filter applied in the three-state switching cell buck–boost converter, which provides current and voltage with low ripple and low noise. The unified second-stage filter promotes a reduction in the number of devices while maintaining the filtering performance of the converter, with second-stage LC filters at the input and at the output. Moreover, the unified filter, when associated with a three-state switching cell buck–boost converter, allows a size reduction of filter devices, especially for designs with duty cycle range around 1/2. Furthermore, the unified filter arrangement provides nondissipative clamping of switching devices and reduce the system order when compared to the converter with second-stage LC filters. In this paper, the static and dynamic characteristics of the proposed converter in continuous conduction mode (CCM) are reported. Experimental data were obtained from a laboratory prototype with an input range of 32 $\sim$ 72 V, constant output of 48 V, a load of 150 W, and switching frequency of 45 kHz. The measured efficiency for the rated load was 97% for maximum input voltage. A comparison of the size and performance of the proposed filter with the topology that uses second-stage LC filters at the input and at the output is also presented.

In this paper, we propose adaptive algorithms of gain tuning for Kalman filters and switching Kalman and $\mathcal {H}_{\infty }$ filters for discrete systems. Both of the gain tuning and switching rely on square means of innovations. This paper also provides stability analyses on time-varying Kalman filters and derives a sufficient condition for their asymptotic stability, on which our gain-tuning algorithm is based. It should be noted that the stability condition is available for even nonstabilizable systems having their uncontrollable poles on the unit circle. To illustrate those algorithms, we perform simulations using a harmonic oscillator model that is nonstabilizable and has its poles on the unit circle. Furthermore, we apply the algorithms to estimation of a ship's oscillation, particularly, with time-varying frequencies by simulations and model experiments. Consequently, all the results of stability analyses, simulations, and experiments have convinced that the algorithms are solid and effective.

Supercapacitors are receiving significant interest in wireless sensor network applications due to their high power density and longer lifespan. In such applications, consideration of the leakage effect is crucial for online control and management of supercapacitors. Motivated by this fact, in this paper we propose an online scheme to estimate the state-of-charge (SOC) of supercapacitors, taking the leakage effect into account. First, we propose a completely observable equivalent circuit model (ECM) of a supercapacitor, which captures the leakage effect. Then, we design an unscented-Kalman-filter-based SOC estimator on the proposed ECM. To illustrate the proposed scheme, we consider a commercially available 5 F supercapacitor (Maxwell BCAP0005) and conduct experimental studies to identify the ECM parameters. We also perform simulation and experimental studies to test the effectiveness of the proposed estimation scheme, in this paper. Finally, we evaluate the robustness of the proposed scheme under parametric and measurement uncertainties.

A space vector modulation (SVM) technique of a dual-inverter system for an open-end winding motor drive is described in this paper, where one inverter has a battery power source and the other has an only capacitor across the dc bus. The SVM must be achieved to operate the motor with field-oriented control and simultaneously to control the capacitor voltage at a constant value by using redundant switching states of the dual-inverter system. The control of the capacitor voltage is carried out by selecting a charging or a discharging mode in each redundant switching state, taking the instantaneous motor power factor into account. In addition, it is also required to reduce the error voltage pulses, which are generated in output multilevel voltage waveforms during the dead time. The compensation method of the existing dead-time scheme and the improved SVM sequence to reduce the error voltage vectors are proposed in this paper. The proposed methods are examined through several experimental tests and are confirmed to generate superior output voltage waveforms from the viewpoint of the measured total harmonic distortion and dv / dt .

Turbomolecular pumps with ultrahigh vacuum performances are a desired technology among modern vacuum systems, which requires the pump to synchronously possess the wide pumping speed and high vacuum. This paper describes a systematic design methodology for a magnetically levitated turbomolecular pump with consideration of multiphysics constraints, such as the mechanical strength, rotor dynamics, electromagnetic losses, and thermal characteristic. These variables will directly decide the acquisition of high vacuum performances. The design process for such high-performance pumps requires multidisciplinary and highly iterative due to the complex interaction of the many design variables involved. The structure of the bladed rotor is determined in terms of the material selection and mechanical verification. In this paper, an effective modeling method is presented to achieve accurate bending modes of the bladed rotor. An assessment on the loss level and the thermal limit is performed to ensure the temperature rise of the pump within the acceptable range. The measured results show that the pump can achieve the high vacuum performance with the pumping speed of 4370 l/s and the lowest working pressure of 10–8 magnitude. The proposed design process described in this paper provides the general guidelines for the multidisciplinary design of high-performance turbomolecular pumps.

Manual assembly is still an essential part in modern manufacturing. Understanding the actual state of the assembly process can not only improve quality control of products, but also collect comprehensive data for production planning and proficiency assessments. Addressing the rising complexity led by the uncertainty in manual assembly, this paper presents an efficient approach to automatically capture and analyze hand operations in the assembly process. In this paper, a detection-based tracking method is introduced to capture trajectories of hand movement from the camera installed in each workstation. Then, the actions in hand trajectories are identified with a novel temporal action localization model. The experimental results have proved that our method reached the application level with high accuracy and a low computational cost. The proposed system is lightweight enough to be quickly set up on an embedded computing device for real-time online inference and on a cloud server for offline analysis as well.

This paper proposes and experimentally evaluates a method, which is able to measure the refrigeration capacity of compressors in extremely short times. Traditionally, the measurement of this parameter is done using specialized and expensive test rigs and can take up to 4.5 h for the measurement of a single compressor. To overcome this long measurement time, it is proposed to use a simpler measuring system, in which, instead of measuring the refrigeration capacity directly, the rate of pressure rise imposed by the compressor to a cylinder with fixed volume is measured. This paper shows that both variables have a high correlation factor when the test and compressor conditions are taken into account. As the correlation among the variables is nonlinear, it is not possible to use simple mathematical correlation functions, so neural networks are used for that purpose. By using the proposed method, the refrigeration capacity of a compressor can be determined in less than 7 s, which is approximately 0.05% of the time required by traditional methods. To guarantee the metrological reliability of the results presented by the proposed neural model, this paper proposes a novel approach based on the Monte Carlo and the bootstrap methods.

In this paper, a three-dimensional (3-D) motion tracking method is proposed for binocular microscopic vision system to precisely record the motion trajectories of millimeter size objects in the Cartesian space. Primarily two fundamental problems are solved. The first problem arises from the limited depth of field (DOF) of microscope. Considering the motion of the objects, the existing autofocusing methods requiring sequential images either in focus or defocus are not workable. Therefore, a one-shot prior autofocusing approach is desired, which needs to take the motion tendency of objects into account. Besides, the autofocusing process always lags behind the motion of objects, and there inevitably will be prediction deviation on the motion tendency of objects. This leads to the second problem to estimate the 3-D motion states from defocused images. In this paper, we first explain the defocusing process from the perspective of S-Transform, based on which the Bayesian inference inspired method to estimate the depth from defocus from one single image is derived thereafter. Afterwards, a motion states, including both the position and velocity, estimation approach is developed within the Kalman filter framework. The above two aspects mutually supply the necessary information for each other to be functional to accurately realize the DOF tracking and motion tracking of moving objects. Experiments were well-designed to validate the effectiveness of the proposed method, and experiments result showed a tracking precision of 3 μ m was achieved.