This paper presents an overview of the key technologies and solutions adopted in utility-scaled photovoltaic inverters for large scale photovoltaic plants. The overview starts by presenting the circuit topology and cooling system. Subsequently, it focuses on the on-site integration and deployment of the system and finally on the introduction of a modular-type solution that enables photovoltaic and energy storage in the same low voltage bus.

Proximity and tactile sensors have been widely used to control robots. However, each of these sensors has its own shortcomings. Visual sensors have blind spots, whereas tactile sensors cannot acquire information when non-contact. To overcome these problems, this study develops an optical sensor that can measure the distance and two-axis forces using a beam structure and photo reflectors. The sensor is inexpensive owing to its simple structure. Moreover, the sensor is demonstrated to have sufficient accuracy for both the distance and force measurements at 0.2, 0.5, and 1.0 Hz. Additionally, the usefulness of the sensor is confirmed based on reduced impact control at the time of contact and force control.

In recent years, AC servo drives have been required not only to play the role of high-speed and high-precision positioning devices but also as information devices that acquire various data through sensor networks. Our current flagship product: the Σ-X series, is a component that maximizes the performance of our customers' equipment and provides data acquisition functions to realize digital solutions such as preventive maintenance and failure prediction.

In this paper, we explain our solution concept: i³-Mechatronics, and introduce the lineup, basic performance, and the latest functions of Σ-X based on this concept. In addition, as a case study of the control technology development, the motion control function that has both high vibration suppression performance and easy-to-use adjustment guidelines for the user will be described.

This paper presents a method for robust velocity control of electromagnetic friction brakes for constant velocity (isokinetic) training in rehabilitation. Rehabilitation treatments using robots have become an attractive option due to labor shortages. In robot rehabilitation, isokinetic exercises are a form of highly efficient training. In rehabilitation machines, passive machines (brakes and clutches) are commonly utilized because they are inexpensive and safe. We focus on electromagnetic friction (EF) brakes which have a higher torque-to-weight ratio than magneto-rheological and powder brakes. Owing to such characteristics, the size and weight of the rehabilitation robots can be reduced by using EF brakes. Consequently, it can reduce the burden on subjects. Although EF brakes generate high torque, they have hysteresis and offset torque, which deteriorates the control performance. This paper proposes three contributions of an EF brake. First, the analysis and modeling of the EF brake are proposed. Second, a disturbance observer is proposed for the EF brake. The proposed method can design the disturbance suppression characteristics independent of the tracking performance. Finally, a robust velocity control scheme that considers the sign of the velocity for isokinetic exercises is proposed. The proposed method is compared with the conventional proportional-integral controller and its effectiveness is experimentally confirmed.

Joint gap measurement is an important inspection to prevent buckling of railways. However, this measurement is labor intensive and time consuming because the tracks are too long for manual inspections. Therefore, we have developed a rail joint gap measurement method using train frontal images recorded by a handy video camcorder. In this paper, we describe details pertaining to the proposed method and discuss the measurement results obtained based on an experiment involving a commercial train.

A high-frequency isolated transformer integrated circuit configuration is proposed for an interlink converter for microgrid applications. The interlink converter is connected to a 3-phase AC grid and a DC microgrid. Further, a control algorithm for the proposed circuit configuration is discussed. Subsequently, a 12-kW prototype is built, and experimental results are provided to demonstrate the validity of the proposed circuit, wherein the efficiency for BES/AC conversion was improved by 3% compared with conventional circuits.

Maximum adhesive force control has been developed to restrict the adhesive force to its maximum value by utilizing the adhesive coefficient between the wheel and rail, which peaks at a specific slip ratio when the drive wheel slips. To estimate the slip speed at the peak adhesive force value, the vehicle and wheel speeds are required. In this study, maximum adhesive force control was proposed, which involves estimating the vehicle speed using the LPF of the driving-wheel speed instead of the vehicle speed. Simulation results indicate that the torque was successfully controlled to drive at the maximum adhesive force. In addition, the proposed control method was validated using a wheel-rail test bench.

The mitigation of delay propagation owing to excessive station dwell time is crucial for ensuring stable transport in a highly frequent urban train service. The precise departure time of the preceding train from the station is difficult to predict; however, control methods with predictions are effective in mitigating the delay of the following train. The train trajectory is generated using real-time continuous position information from the communication-based train control (CBTC) system, which can mitigate the delay propagation of the following train without predictions. In this study, a control method for mitigating delay propagation without predictions is proposed. Furthermore, introducing a finite-departure prediction for the preceding train can allow the following trains to avoid stops between stations. We numerically verify the effectiveness of reducing the delay time based on case studies with and without departure prediction. The results show that departure predictions effectively reduce headway and the duration of stops between stations for the following trains.

This paper proposes an autonomous control scheme for power-sharing between energy storage systems (ESSs). The targeted ESS consists of multiple distributed ESSs, all connected to the same DC grid. Importantly, the proposed control method does not require communication between the distributed ESSs and solves the existing power-sharing problems during a communication failure. The autonomous control scheme is based on conventional voltage droop control but features manipulating the reference voltage with a fixed virtual resistance. Each ESS manipulates the reference voltage command value and cooperatively shares the power between any number of ESSs. Operational problems occur when combining autonomous control with an existing state-of-charge (SOC) based mode-switching control, which toggles charge and discharge modes according to the SOC threshold of the battery. There is a possibility that all ESSs are in the same mode, then they cannot share the power and face the risk of system failure. Furthermore, the SOC of each ESS is unbalanced with no power-sharing as it only depends on its power generation and consumption. The resulting difference in charge and discharge cycle causes the difference in the life cycle of the batteries between the ESSs. To solve this problems, this paper additionally proposes a control method for a power-sharing operation that averages the SOC of each ESS without mode switching. Accordingly, the basic control law and control method of autonomous control are derived, and the amount of power-sharing is quantitatively considered, and the proposed control method is experimentally validated.

A novel drive circuit for switched reluctance (SR) motor expanding the operating area under limited source voltage has been proposed by adding external capacitor in series to extend supply voltage. However, the capacitance of the external capacitor has not been optimized to be sufficient to extend the driving range of the SR motor. Subsequently, the authors have previously proposed a conservative design method for capacitance by linearizing the winding current. However, there is a problem in that the difference between the conservative design and the simulated fluctuation of the capacitor voltage is large. In this paper, an optimal design method is proposed for the capacitance by using an LC equivalent circuit at the beginning of excitation and demagnetization.

Physical human-robot interaction applications requiring safety and compliance characteristics usually employ mechanical devices such as series elastic actuators (SEAs). So far, impedance control schemes for SEAs have been investigated to overcome the limited displayable stiffness at the end point, represented by the stiffness of a physical spring, in a passive manner. SEAs usually mount two encoders on both the motor and load sides for position measurements. However, in several applications, the installation of a load-side encoder is not feasible from both cost and manufacturing perspectives. In this scenario, a Kalman Filter based on micro electro mechanical system accelerometers has been proposed for estimating the external force and load side quantities, without the need for load-side encoders. Herein, a novel impedance control scheme leveraging this approach is proposed to effectively overcome the stiffness of the physical spring while maintaining passivity at the end point. Compared with conventional load-side encoder-based impedance control schemes, the proposed control scheme presents comparable performance, as demonstrated by simulation and experimental results.

The dynamic and steady-state behaviors of distributed power supply in a DC architecture with a minimized DC bus capacitor is investigated in this paper using the power balance control technique. The circuit is simulated and analyzed using MATLAB Simulink. The proposed system significantly improves the dynamic response of the converter to load steps with the minimized DC bus capacitor for a distributed Power System. The possibility of using a ratio of capacitance/watt lower than the typical values used in commercial applications, while maintaining the output voltage regulation, is theoretically proved. The minimized DC bus capacitors of the proposed system are 100 μF (0.1 μF/W), 400 μF (0.47 μF/W), 80 μF (0.53 μF/W), 100 μF (0.67 μF/W), 2000 μF (5 μF/W) and 2000 μF (5 μF/W) for the 380 Vdc, 100Vdc, 60Vdc, 48Vdc, 24Vdc, and 12Vdc, respectively. The simulation results show the following advantages: small capacitor size, reduced converter volume, good steady-state behavior, and fast dynamic transient response.

A Direct Current excited Reluctance Motor (DCRM) powered by three-phase sinusoidal currents is expected to have a higher torque density than a Switched Reluctance Motor (SRM) powered by unipolar currents because they can achieve a greater angular variation of magnetic co-energy even in the magnetic saturation region. In this study, a non-sinusoidal current drive method for DCRM is proposed to increase torque. The non-sinusoidal current waveform is defined by a Fourier series function, and the optimum coefficients of the current function are solved using nonlinear programming. According to simulation results, the average torque of a DCRM driven by optimized non-sinusoidal current waveform is increased. Furthermore, the current balance between the armature coil and the excitation coil is investigated. As a result, the average torque is increased by up to about 25% when compared to conventinal sinusoidal current drive.

In this paper, we propose a novel method to improve the circuit simulation accuracy of insulated-gate bipolar tran- sistor (IGBT) power devices under a short-circuit state. To determine the IGBT junction temperature, the transient thermal resistance of an IGBT device on the order of micro seconds is estimated by transient thermal simulations. The saturation current without self-heating effects is estimated based on a short-circuit test and the transient thermal resis- tance. The IGBT SPICE parameter is extracted from the saturation current characteristics during the short-circuit state. The coupled electrical-thermal simulations with the SPICE model and thermal resistance model are applied to several short-circuit evaluations with different parasitic impedance and gate driving condition, and the results are consistent with the measured current and voltage waveforms.

Patients diagnosed with bronchial asthma or chronic obstructive pulmonary disease (COPD) are required to use in- halers to control their symptoms. However, approximately 70 % of the patients use their inhalers incorrectly because of misunderstandings regarding their use or habituation owing to long-term use. Currently, in-person instructions provided by pharmacists or doctors are the only remedy to this problem. Therefore, new evaluation method, which eliminates the input of a doctor or pharmacist, is urgently needed. This study aims to realize automatic evaluation of individual inhaler motion. A new sensing attachment with inertial measurement unit (IMU) is developed for an inhaler device. We propose an evaluation method using data from the sensing attachment, without doctor or pharmacist issued instructions. The proposed evaluation method for inhaler motion is based on a dynamic programming (DP) matching algorithm. Furthermore, the evaluation method is verified via suitable clinical experiments. Based on the experimental results, all clinical data could be classified by the proposed method.

Many contact-rich tasks in factories are still executed manually because it is often difficult for robots to adapt to variable environmental conditions. To incorporate the adaptability of humans to the environment into robots, a machine learning technique called learning from demonstration (LfD) has been well studied. A popular approach for automating complex tasks involves selecting the appropriate action from several segmented motions, called movement primitives. In this study, we propose a method for autonomously selecting a recovery action and correcting the trajectory when the task is determined to have failed based on force. Although conventional technologies can divide motions into time series, they are unable to recognize the presence of failures in detail in response to slight environmental variations. Therefore, we propose a two-stage clustering method, which consists of time segmentation of trajectories and labeling of segmented motions, to recognize failures and generate of recovery actions in response to the failures. The proposed method was able to perform the task even in cases of a 20 mm position error by accurately selecting recovery actions and correcting the trajectory.

Robots are increasingly used for substituting various tasks that were previously performed by humans. However, certain tasks can only be accomplished by humans. To substitute such tasks, robots should be able to reproduce the motion of humans. There are two steps to achieving this goal. First, human motion needs to be measured properly using sensors. Second, the robots need to be properly controlled to reproduce the motion. In particular, the present study focuses on the second step and proposes a method for controlling a robot to reproduce a certain motion.

There are several problems when reproducing a motion. One major problem is the phase delay, which is inevitable when controlling the position of a robot. In previous studies, master-replica systems were utilized to cope with the phase delay. However, using master-replica systems makes it difficult for the operator to perform tasks. Therefore, this paper proposes a control method for robots to precisely reproduce human motion without using the master-replica system.

Indonesia is an archipelagic country with many remote islands. Supplying electricity is difficult in some remote islands in Indonesia, such as Adaut regency of west Maluku. One solution to solve this electricity supply problem is the creation of a microgrid system. However, the application of renewable energy on microgrids can lead to several technical challenges, such as frequency disturbances and voltage instability. Therefore, a control algorithm that can maintain the system stability is required. One recently developed algorithm is the synchronverter. In this study, the synchronverter is used to maintain network stability on an islanded wind farm based microgrid. As a result, we asses the microgrid stability responses with the synchronverter algorithm or a conventional synchronous generator to evaluate the microgrid stability performance. The outcomes of this study indicate that the synchronverter algorithm can maintain the stability of microgrid even it is interrupted by intermittent wind speed input and load changes.

This paper provides an overview of a circuit analysis model for a DC brush motor, taking into consideration showering arc events. A mechanical contacts model that reproduces showering arc behavior is developed by combining new variable resistors with the steady arc model. As a result, spike surge waveforms can now be simulated via circuit analysis. It is also become clear that spike surges with continuous showering arcs constitute the maximum condition of conducted EMI. The measured and simulated conducted EMI show good agreement within 9 dB up to 108 MHz, in accordance with the CISPR 25 standard. Moreover, it is now possible to quantitatively predict the amount of conducted EMI in a system comprising a step-down DC-DC converter and a DC brush motor, by considering a dominant magnetic coupling and parasitic impedances.

In this study, an automotive photovoltaic (PV) system was fabricated for electric vehicles. The PV panel for the PV system prototype comprises modules. Each module is equipped with a converter for maintaining maximum power point tracking (MPPT) operation. This configuration allows performing the MPPT operation individually for each PV module. Furthermore, the MPPT operation performance during driving was verified. The PV system prototype maintained power generation during driving using the MPPT operation. In situations where the solar radiation varies frequently, the range of the MPPT voltage search influences the tracking achievement ratio (TAR). In addition, a TAR of 97% was achieved by optimizing the range of the MPPT voltage search.

Permanent magnet synchronous machines (PMSMs) are widely used in a variety of applications. The static eccentricity of the rotor is a common fault in the fabrication process. These faults cause imbalanced electromagnetic force and exert unexpected vibration and acoustic noise during the design process. In the worst case, it causes bearing or motor failure. This research investigates the impact of this fault on the temporal and spatial harmonic distribution of gap flux density and electromagnetic force. Moreover, a compensation method has been proposed to suppress imbalanced force due to static eccentricity by using a triple three-phase winding motor. By controlling the three inverters independently, the winding current of each group can be controlled. Therefore, the gap flux density and electromagnetic force in each group can be brought into a desired state. Therefore, the imbalanced electromagnetic force can be restored using this system. In this paper, the effectiveness of the proposed method is verified by Finite Element Analysis (FEA) and experiment.

A cell capacitor is one of the most fragile components in a modular multilevel converter (MMC). Capacitance decreases and equivalent series resistance (ESR) increases, as the capacitor deteriorates. This paper proposes an online monitoring method for both the capacitance and ESR of the cell capacitors in an MMC without any additional components or operation. The proposed method measures the impedance of the cell capacitor not only at a low frequency but also at a switching sideband-frequency of the cell without current sensors for capacitor current. The high-frequency components around the switching frequency improve the estimation accuracy compared with the previous methods that measure only impedance at low frequencies. The experimental results confirm that the proposed method estimates the capacitance and ESR with errors of 3.1% and 8.8%, respectively.

The compressor motor of an air conditioner is subjected to the a fluctuating load torque during the suction and discharge of refrigerant, resulting in a speed ripple in the machine angular cycle. This paper proposes a new predictive feedforward control system that predicts and suppresses the speed ripple cuased by the periodic disturbance of compressor motor by using error data of speed PI controller. The speed ripple suppression performance of proposed control method is experimentally confirmed by applying it to achieve speed control of an air conditioner compressor motor.

An accurate target tracking system improves the quality of flyby imaging of the target and consequently aids effective planetary exploration. A vision-based tracking system is one of the more popular systems, utilizing imaging data to achieve the required tracking accuracy. However, recent high-accuracy target tracking requirements cannot be achieved with targeting error feedback only. This paper summarizes the asteroid flyby mission characteristics and requirements, shows how possible error sources in the tracking system, and displays an exemplar control system design. The tracking error source is generally divided into a navigation error, which is a tracking profile generation error, and a control error, which is caused by the control system. A high-quality onboard relative-trajectory determination system is required to improve the navigation accuracy of the control system, because the pre-designed or offline-estimated relative trajectory contains uncertainties that cause the tracking profile generation error. Previous studies focused on this navigation error because of its sensitive effect on control system performance, showing some methods for improvement. This paper discusses how the control system can be improved to achieve greater precision during target tracking by considering the navigation and system characteristics. A realistic case study scenario is defined and analyzed based on an actual target tracking interplanetary probe mission. The characteristics of the designed control system are presented and its performance is analyzed via numerical simulation, using the case study data.

GaN power devices improve the performance in power conversion circuits. Since the current rating of the GaN devices is still small, many devices must be connected in parallel to create a large-current power module. Device cooling and low stray inductance are the major challenges in designing a high-power half-bridge circuit with multi-parallel GaN devices. In order to overcome these challenges, we propose an inverter circuit structure with 12 parallel GaN devices capable of double-sided cooling and a well-balanced stray inductance. Such a system is applicable to electric vehicle design.

Multi-agent systems (MASs) are composed of multiple autonomous agents, and the overall behavior of an MAS is determined by the local interactions between its agents. In recent years, research on MASs aimed at their application in real-world environments has garnered considerable interest. In particular, consensus control in environments with constrained communication range of agents and obstacles is being extensively investigated. In this study, the consensus problem of MASs is examined by considering the effects of obstacles. In particular, an obstacle avoidance algorithm is developed as a control method for real-world autonomous machines such as autonomous mobile robots. In conventional control methods, obstacles are provided as coordinate points; however, in this study, they are introduced as variously shaped polygons. Furthermore, the graph topology is dynamic, which enables more realistic situations. Finally, a simulation study is performed, and the effectiveness of the developed algorithm for applying to the MAS consensus problem is demonstrated.

This study proposes a control method for an electrolytic capacitor-less dual-inverter with an aim to reduce the interharmonic currents. Owing to the low-energy buffer of the electrolytic capacitor-less inverter, load fluctuations superimpose harmonic currents on the input current. The proposed control method facilitates output power pulsation control of main inverter, which is a constant frequency regardless of load fluctuations. The experimental results exhibit a reduction in the interharmonic currents at 20 and 80 Hz by 68 and 72 %, respectively. Moreover, the power factor is improved by 11 pt., and total harmonic distortion (THD) of the input current is reduced by 26 pt. under rated load conditions. Therefore, the proposed control method can effectively reduce the interharmonic currents and improve the power factor and THD of the input current.

This paper proposes a Fourier series expansion-based sensorless position control method for permanent magnet synchronous motors (PMSMs). More specifically, a minor sampling process that is shorter than the vector control period is introduced to reduce the amount of signal injection. The effectiveness of this method is demonstrated via simulatively and experimentally to show that the amount of signal injection can be reduced using the proposed method.

This paper proposes a control and modulation method for a Current-Fed Dual Active Bridge (DAB) converter to improve the conversion efficiency for wide voltage range applications. The current-fed DAB converter is preferred in battery applications owing to its high-power density and low current ripple. On the other hand, the high-conversion efficiency range is limited to close to the nominal DC voltage condition as the DAB converter. The proposed method provides Zero-Voltage-Switching (ZVS) in a wide DC voltage range by Triangular Current Mode (TCM). Furthermore, the proposed control reduces the inductor RMS current compared with the DAB converter to minimize the conduction loss. The validity of the proposed method is established by experimental results. According to the experiment using a 2-kW prototype, the conversion efficiency reached 97.2% when the input voltage was varied by 50% from the nominal DC voltage, then the conversion loss was reduced by 52.5% owing to the proposed control. Finally, the maximum power density of the current-fed DAB converter was improved by 38.1% compared to that of the DAB converter.

This paper presents optimal current-control methods for driving two different synchronous motors using a single inverter. When one inverter drives two motors, system efficiency will deteriorate if their loads are not identical. Moreover, even with identical loads, system efficiency will deteriorate if the parameters of the two motors are not identical. To address this issue, this paper proposes optimal current-control methods for systems with two different motors driven by a single inverter.

This study proposed a control method to reduce the torque ripple vibration of an integrated on-board charger using the windings of an interior permanent magnet synchronous motor (IPMSM). During a battery-charging operation, stopping the motor results in noise, as well as damage to the motor and other components from the torque vibration caused by the charging current. In the proposed control method, the generated torque was estimated using a back-electromotive force table, and the phase current was controlled to eliminate the torque. The proposed method can suppress torque vibration, irrespective of the angle of the rotor in the IPMSM. The effectiveness of the proposed method was verified experimentally, with the torque vibration suppressed by 94% compared with that of the conventional control method.

In mobile applications such as eletric vehicles, weight and installation space are the primary limiting factors that affect the system efficiency and consequently the driving range. Reusing the machine windings of an electrical machine as inductors, e. g. in DC-DC converters for onboard chargers, saves weight and space. However, currents in the machine windings when operating as DC-DC converter can result in undesired torque ripple generated by the machine. Therefore, stable rotor positions of a switched reluctance machine have to be found to prevent it from rotating in DC-DC converter operation mode. In this study, stable rotor positions for a wide range of current distributions are determined, enabling flexibility in the choice of currents. A method to analyze such stable equilibrium positions for switched reluctance motors is presented. The proposed method is used to determine the stable positions that facilitate flexible current distribution between phases. Moreover, locus curves are calculated, simulated, and measured to illustrate and evaluate stable rotor positions for the various current distributions.

This paper reports a prediction method for the three-dimensional (3D) position coordinates of a 3D capacitive proximity sensor consisting of multiple sensing electrodes; this sensor was developed in our previous studies. Notably, the sensor could detect an object nearby; however, obtaining a formula to directly determine the object position from the sensor output was difficult owing to strong non-linearity. Therefore, in this paper, we propose a method of obtaining an approximate formula instead of an accurate formula to estimate the 3D position of objects from sensor outputs using machine learning techniques. The method obtained datasets that were a combination of the sensor outputs and the 3D positions estimated from camera images using an image processing technique. The machine learning models were trained using the obtained training datasets, and the trained models could predict two-dimensional positions from the sensor outputs. The following four conventional machine learning models were used in this study: a multilayer perceptron, radial basis function network, support vector regression, and random forest (RF). RF delivered the best performance in the evaluation based on the root mean square error and coefficient of determination.

This study investigates the effect of an inductance model on the sensorless control performance of a synchronous reluctance motor (SynRM). A high-frequency voltage injection method based on the position dependence of the inductance and an extended electromotive force estimation method based on the motor model are applied to achieve sensorless control. More specifically, the inductances are modeled in several patterns and applied to the two methods. Subsequently, the characteristics in the steady and transient states are compared. Moreover, the effect of the inductance model on the sensorless control performance of a SynRM with magnetic saturation is investigated by comparing the characteristics in the full-speed region under the combination of the two methods.

Lithium-ion batteries (LIBs) are used to power a range of applications starting from portable consumer electronics to electric vehicles and grid-tied energy storage systems. Now, with the increasing application of LIB in high power and sophisticated applications, it is of great significance to predict the remaining useful life (RUL) for reliable operation and to protect the battery pack from unwanted incidents including catastrophic failure. Real-time information on RUL is essential to predict battery failure condition resulting in effective prevention or at least reduction of the damage that may cause by the battery failure. Moreover, accurate RUL is extremely helpful for scheduling routine maintenance and necessary replacement at the end of its useful life. Consequently, RUL prediction has become a topic of interest to researchers. There are several RUL estimation techniques proposed in the last decade where machine learning (ML)-based techniques showed superiority in terms of accuracy, adaptability, and modeling. Therefore, ML-based RUL prediction methods are comprehensively reviewed based on their essential performance parameters in this paper. A detailed discussion on the issues, challenges, trends, and future research scopes are also presented to provide clear guideline to the researchers.

This paper describes a novel method for current detection in sensorless control using high-frequency voltage injection. The proposed method adopts a low-pass filter to prevent ringing. Generally, reactive current cannot be detected using a DC filter; however the proposed method permits detection via voltage injection. High responsiveness and a simple construction have been achieved using the method. Simulation results indicate that active and reactive currents can be reconstructed using a single shunt current; the experimental results indicate that the proposed method can be applied to a motor drive without lowering the performance, unlike when using a current sensor.

Humans possess an outstanding ability to understand contact states, thereby leading to appropriate actions. In this study, we consider the operation of autonomous machining tasks on heterogeneous materials using robots; this mechanism poses a challenge as robotic machining is mainly performed on homogeneous materials using the current robotic technology. Herein, we propose a method to recognize contact states, e.g. the materials and deformation types of fragile objects, to selectively process parts of tissues without damaging other tissues. Furthermore, an identification method is proposed based on a time-delay neural network (TDNN) to identify fragile objects and their deformation types, such as elastic and plastic, for real-time applications. We used a multi degrees-of-freedom (DoF) robotic arm to cut and process fragile objects. We examined the planning of an appropriate trajectory based on the contact states identified by the TDNN during cutting motion. The selective cutting motion of a robot was demonstrated with high success rates despite variations in the cutting speed.

This paper presents an observer-based robust control for mechatronic systems that utilize a surface-mounted permanent magnet synchronous motor (SPMSM). A mechatronics system with an SPMSM typically comprises a mechanical moving part (outer-loop) and a power converter (inner-loop) to drive the motor. We explain the dynamic modeling of the SPMSM and provide a brief discussion on disturbances in the SPMSM. A cascaded tracking error dynamics of the SPMSM is derived by using a speed controller and torque modulation to analyze disturbances present in outer-loop and inner-loop systems. This cascaded structure highlights how the disturbances in the mechanical moving parts (outer-loop) and power converter (inner-loop) hinder the motion-tracking performance of the SPMSM. This paper demonstrates how the cascaded structure facilitates the stability analysis of the closed-loop system and the design of feedback controllers. The paper aims to help readers understand intrinsic problems in motion control of a mechatronic system driven by the SPMSM and how to design an observer-based robust control of the SPMSM.

In modern power grids, many distributed generators (DGs) are connected via grid-connected inverters. Generally, the possibility of resonances among inverters and other equipment placed in proximity and the network itself must be analyzed in advance. However, it is often difficult to approach the problem for complex systems by using model-based techniques, as they require obtaining a linear approximate analytical model. The impedance-based stability analysis method provides a practical alternative to the linear model approximation method. It directly measures the impedances of the source and load subsystems and evaluates its stability using the Nyquist criteria. In this study, we assume a scenario in which grid-connected inverters with advanced inverter control, such as the virtual synchronous generator (VSG) control, will become the primary power source in the near future and focuses on the possibility of instability phenomena caused by (i) a large-scale system with long-distance transmission lines using π-sections and (ii) the output filter of DGs with the natural frequencies in high frequency band. Accordingly, the impact of the dominant grid-connected inverter on stability in a large, complex system is evaluated based on the impedance in both the dq (MIMO) and equivalent sequence (SISO) domains. The results suggest that grid-forming controls, such as VSG controls, may resonate with their output filters in the kHz band and that capacitance in long transmission lines cannot be ignored as they can cause system instability. Moreover, it is found that the unstable frequencies identified in the two eigenvalue loci of the dq impedance are also identified in the sequence domain impedance within a single Nyquist plot, further validating the presence of unstable frequencies.

This paper presents an interleaved boost converter with integrated magnetics for common-mode (CM) noise reduction without introducing electromagnetic interference (EMI) filters. The noise reduction is realized using the balanced technique, which is an effective CM noise reduction technique from a circuit topology perspective. The application of this technique addresses the issue of the CM noise, while avoiding an increase in circuit volume due to EMI filters. Additionally, an interleaved circuit topology and integrated magnetics contribute to realizing the high-power density converter. The effectiveness of the proposed converter is discussed through theoretical analyses, simulations, and experiments.

In this study, we established a topic selection method that recommends topics that are interesting and unfamiliar to users. To achieve this aim, we used conceptual distance to identify topics that were unfamiliar to users and improved the accuracy of this method by removing conceptually similar words. Many words used in conversations are excluded in the dictionaries and thesauruses. Thus, we developed a model for conceptual distance measurement using machine learning to measure conceptual distances even for such words. By conducting the subject experiments, we confirmed that the established system recommends topics a user is interested in but unfamiliar with compared with the baseline method developed in a previous research.

Hybrid current sensors are suitable for wide bandwidth current measurement. They entail the fusion of two different measurement circuits, one for DC and low-frequency current and another for high-frequency current. Thus, the advantages of the different measurement principles are incorporated in one current sensor. Hybrid current sensors generate output signals through a superposition of the signals from the low-frequency and high-frequency current sensors. This is realized using analog signal processing by means of an analog operational amplifier circuit. Realization of the superposition of the frequency responses of the different measurement circuits to achieve a constant gain in the transition area is challenging. This study focused on the analog signal processing and its enhancement. Specifically, two possible signal processing approaches to increase the bandwidth based on the state-of-the-art realization of a low-pass filter were devised. These approaches were investigated using a simulation model. Frequency response measurements using a hybrid current sensor based on tunneling magnetoresistance sensors and a Rogowski coil were used for verification. The results show that by enhancing the signal processing, the bandwidth of the current sensors can be significantly increased.

Position-sensorless positioning servo systems for interior permanent magnet synchronous motors (IPMSMs) have been developed to achieve dimension and cost reduction. In these systems, parameter mismatch between the IPMSM, position controller, and position estimator due to thermal variation and aged deterioration is inevitable. To solve this problem, a parameter identification method based on an adaptive scheme has been proposed. However, to use the adaptive scheme, this method can only be applied under no-load conditions, and it is difficult to compensate for parameter variations during actual operation, i.e., under load conditions.

This paper proposes a novel learning-based position control in position-sensorless positioning servo systems. In the proposed method, a feedfoward controller established via learning adaptively compensates the parameter fluctuations in these systems. As learning progresses, the transient response of position control is improved while ensuring robustness to disturbance torque. The effectiveness of the proposed position control system is demonstrated via experiments.

This paper presents a reduced order modeling technology and the application of a half-wave rectified brushless synchronous motor for model-based design (MBD). The motor contains a field winding that is single phase short circuited through a diode, instead of a brush, at the rotor. Therefore, the motor features a maintenance free, brushless structure and easily variable field flux operation. However, the motor must be coupled with the circuit to consider the on/off behavior of the diode using electromagnetic simulations. For this, we propose a reduced order model (ROM) modeling method that reproduces the behavior of a motor generated from electromagnetic analysis to use it for MBD while maintaining the simulation accuracy of the motor. The motor characteristics can be simulated in a short period of time with a pulse width modulation (PWM) inverter switching drive and control strategy, such as maximum torque control, by using the proposed ROM modeling method. We compare the simulation results of the proposed ROM with the results of an electromagnetic finite element analysis (FEA) and experimental measurement conducted with a prototype motor. We clarify the characteristics of the proposed ROM in the motor and reproduce the same behavior in a simulation within a duration shorter than that required by the electromagnetic FEA. Finally, we demonstrate the superiority of the proposed method.

In this paper, a new force observation approach is proposed to realize a superior wideband and periodicity-free sensorless force control system. The proposed force observer is established by the periodicity estimation integrated singular spectrum analysis based disturbance observer. The singular spectrum analysis is designed to significantly separate the essential components of force estimation of the disturbance observer from extreme noise contamination. Accordingly, the bandwidth of the force sensing is considerably broadened at a highly increased pole of the disturbance observer. Additionally, to eliminate the superimposition of the undesired dither periodicity from the force sensation, the periodicity estimation is developed using the least squares method. The proposed method attains a superior widened force sensing bandwidth and high-performance force sensation. The effectiveness validation of the proposed method is performed through the experimental results of force control implemented in a ball-screw system.

Active power decoupling (APD) method has been studied to enhance the lifetime of residential photovoltaic (PV) power generation systems. In single-phase inverter, the DC voltage has a ripple due to the propagation of the 2nd power pulsation from the fundamental voltage and current. The APD method suppresses the DC voltage ripple by compensating for the power pulsation. However, a single-phase grid voltage contains harmonic components and power pulsation from these harmonics, which can propagate to the DC side. Conventional APD control compensates for the 2nd power pulsation only from the fundamental components, and thus cannot suppress the DC voltage ripple caused by the harmonic components. Therefore, this paper proposes control strategies for APD method that can compensate for the power pulsation caused by both fundamental and harmonic components. Furthermore, the effectiveness of the APD control is verified using a 400 W power conditioning system.