Review of Three-phase Soft Switching Inverters and Challenges for Motor Drives

For electric vehicles (EVs),it is necessary to improve endurance mileage by improving the efficiency.There exists a trend towards increasing the system voltage and switching frequency,contributing to improve charging speed and power density.However,this trend poses significant challenges for high-voltage and high-frequency motor controllers,which are plagued by increased switching losses and pronounced switching oscillations as consequences of hard switching.The deployment of soft switching technology presents a viable solution to mitigate these issues.This paper reviews the applications of soft switching technologies for three-phase inverters and classifies them based on distinct characteristics.For each type of inverter,the advantages and disadvantages are evaluated.Then,the paper introduces the research progress and control methods of soft switching inverters (SSIs).Moreover,it presents a comparative analysis among the conventional hard switching inverters (HSIs),an active clamping resonant DC link inverter (ACRDCLI) and an auxiliary resonant commuted pole inverter (ARCPI).Finally,the problems and prospects of soft switching technology applied to motor controllers for EVs are put forward.

Winding Inductance and Performance Prediction of a Switched Reluctance Motor with an Exterior-rotor Considering the Magnetic Saturation

This paper deals with an analytical method to effectively calculate the inductance of an exterior-rotor switched reluctance motor(SRM),which evaluates the winding inductance of both the active section and the end section,accounting for the influence of core saturation.According to the inductance calculated by the analytical model,the flux linkage table and torque table can be established,and the steady state performance such as phase current,flux linkage,copper loss and core loss can be predicted.Effectiveness of this method is verified by the finite element method as well as by experimental results of a 12/8 SRM prototype.

Online Optimization in Power Systems With High Penetration of Renewable Generation:Advances and Prospects

Traditionally,offline optimization of power systems is acceptable due to the largely predictable loads and reliable generation.The increasing penetration of fluctuating renewable generation and internet-of-things devices allowing for fine-grained controllability of loads have led to the diminishing applicability of offline optimization in the power systems domain,and have redirected attention to online optimization methods.However,online optimization is a broad topic that can be applied in and motivated by different settings,operated on different time scales,and built on different theoretical foundations.This paper reviews the various types of online optimization techniques used in the power systems domain and aims to make clear the distinction between the most common techniques used.In particular,we introduce and compare four distinct techniques used covering the breadth of online optimization techniques used in the power systems domain,i.e.,optimization-guided dynamic control,feedback optimization for single-period problems,Lyapunov-based optimization,and online convex optimization techniques for multi-period problems.Lastly,we recommend some potential future directions for online optimization in the power systems domain.

Toward the Energy Efficiency of Resource Allocation Algorithms for OFDMA Downlink MIMO Systems

The problem of the simultaneous multi-user resource allocation algorithm in orthogonal frequency division multiple access(OFDMA)based systems has recently attracted significant interest.However,most studies focus on maximizing the system throughput and spectral efficiency.As the green radio is essential in 5G and future networks,the energy efficiency becomes the major concern.In this paper,we develop four resource allocation schemes in the downlink OFDMA network and the main focus is on analyzing the energy efficiency of these schemes.Specifically,we employ the advanced multi-antenna technology in a multiple input-multiple output(MIMO)system.The first scheme is based on transmit spatial diversity(TSD),in which the vector channel with the highest gain between the base station(BTS)and specific antenna at the remote terminal(RT)is chosen for transmission.The second scheme further employs spatial multiplexing on the MIMO system to enhance the throughput.The space-division multiple-access(SDMA)scheme assigns single subcarrier simultaneously to RTs with pairwise“nearly orthogonal”spatial signatures.In the fourth scheme,we propose to design the transmit beamformers based on the zero-forcing(ZF)criterion such that the multi-user interference(MUI)is completely removed.We analyze the tradeoff between the throughput and power consumption and compare the performance of these schemes in terms of the energy efficiency.

Investigation of degradation and recovery characteristics of NBTI in 28-nm high-k metal gate process

Degradation induced by the negative bias temperature instability(NBTI)can be attributed to three mutually uncoupled physical mechanisms,i.e.,the generation of interface traps(ΔV_(IT)),hole trapping in pre-existing gate oxide defects(ΔV_(HT)),and the generation of gate oxide defects(ΔV_(OT)).In this work,the characteristic of NBTI for p-type MOSFET fabricated by using a 28-nm high-k metal gate(HKMG)process is thoroughly studied.The experimental results show that the degradation is enhanced at a larger stress bias and higher temperature.The effects of the three underlying subcomponents are evaluated by using the comprehensive models.It is found that the generation of interface traps dominates the NBTI degradation during long-time NBTI stress.Moreover,the NBTI parameters of the power-law time exponent and temperature activation energy as well as the gate oxide field acceleration are extracted.The dependence of operating lifetime on stress bias and temperature is also discussed.It is observed that NBTI lifetime significantly decreases as the stress increases.Furthermore,the decrease of charges related to interface traps and hole detrapping in pre-existing gate oxide defects are used to explain the recovery mechanism after stress.

Integrated Sliding Mode Velocity Control of Linear Permanent Magnet Synchronous Motor with Thrust Ripple Compensation

In this paper,a compound sliding mode velocity control scheme with a new exponential reaching law(NERL)with thrust ripple observation strategy is proposed to obtain a high performance velocity loop of the linear permanent magnet synchronous motor(LPMSM)control system.A sliding mode velocity controller based on NERL is firstly discussed to restrain chattering of the conventional exponential reaching law(CERL).Furthermore,the unavoidable thrust ripple caused by the special structure of linear motor will bring about velocity fluctuation and reduced control performance.Thus,a thrust ripple compensation strategy on the basis of extend Kalman filter(EKF)theory is proposed.The estimated thrust ripple will be introduced into the sliding mode velocity controller to optimize the control accuracy and robustness.The effectiveness of the proposal is validated with experimental results.

Data-Based Filters for Non-Gaussian Dynamic Systems With Unknown Output Noise Covariance

This paper proposes linear and nonlinear filters for a non-Gaussian dynamic system with an unknown nominal covariance of the output noise.The challenge of designing a suitable filter in the presence of an unknown covariance matrix is addressed by focusing on the output data set of the system.Considering that data generated from a Gaussian distribution exhibit ellipsoidal scattering,we first propose the weighted sum of norms(SON)clustering method that prioritizes nearby points,reduces distant point influence,and lowers computational cost.Then,by introducing the weighted maximum likelihood,we propose a semi-definite program(SDP)to detect outliers and reduce their impacts on each cluster.Detecting these weights paves the way to obtain an appropriate covariance of the output noise.Next,two filtering approaches are presented:a cluster-based robust linear filter using the maximum a posterior(MAP)estimation and a clusterbased robust nonlinear filter assuming that output noise distribution stems from some Gaussian noise resources according to the ellipsoidal clusters.At last,simulation results demonstrate the effectiveness of our proposed filtering approaches.

Quantization and Event-Triggered Policy Design for Encrypted Networked Control

This paper proposes a novel event-driven encrypted control framework for linear networked control systems(NCSs),which relies on two modified uniform quantization policies,the Paillier cryptosystem,and an event-triggered strategy.Due to the fact that only integers can work in the Pailler cryptosystem,both the real-valued control gain and system state need to be first quantized before encryption.This is dramatically different from the existing quantized control methods,where only the quantization of a single value,e.g.,the control input or the system state,is considered.To handle this issue,static and dynamic quantization policies are presented,which achieve the desired integer conversions and guarantee asymptotic convergence of the quantized system state to the equilibrium.Then,the quantized system state is encrypted and sent to the controller when the triggering condition,specified by a state-based event-triggered strategy,is satisfied.By doing so,not only the security and confidentiality of data transmitted over the communication network are protected,but also the ciphertext expansion phenomenon can be relieved.Additionally,by tactfully designing the quantization sensitivities and triggering error,the proposed event-driven encrypted control framework ensures the asymptotic stability of the overall closedloop system.Finally,a simulation example of the secure motion control for an inverted pendulum cart system is presented to evaluate the effectiveness of the theoretical results.

A Review of State-of-the-art Flexible Power Point Tracking Algorithms in Photovoltaic Systems for Grid Support:Classification and Application

To maximize conversion efficiency,photovoltaic(PV)systems generally operate in the maximum power point tracking(MPPT)mode.However,due to the increasing penetra tion level of PV systems,there is a need for more developed control functions in terms of frequency support services and voltage control to maintain the reliability and stability of the power grid.Therefore,flexible active power control is a manda tory task for grid-connected PV systems to meet part of the grid requirements.Hence,a significant number of flexible pow er point tracking(FPPT)algorithms have been introduced in the existing literature.The purpose of such algorithms is to real ize a cost-effective method to provide grid support functional ities while minimizing the reliance on energy storage systems.This paper provides a comprehensive overview of grid support functionalities that can be obtained with the FPPT control of PV systems such as frequency support and volt-var control.Each of these grid support functionalities necessitates PV sys tems to operate under one of the three control strategies,which can be provided with FPPT algorithms.The three control strate gies are classified as:①constant power generation control(CP GC),②power reserve control(PRC),and③power ramp rate control(PRRC).A detailed discussion on available FPPT algo rithms for each control strategy is also provided.This paper can serve as a comprehensive review of the state-of-the-art FPPT algorithms that can equip PV systems with various grid support functionalities.

An Incentive Mechanism for Federated Learning:A Continuous Zero-Determinant Strategy Approach

As a representative emerging machine learning technique, federated learning(FL) has gained considerable popularity for its special feature of “making data available but not visible”. However, potential problems remain, including privacy breaches, imbalances in payment, and inequitable distribution.These shortcomings let devices reluctantly contribute relevant data to, or even refuse to participate in FL. Therefore, in the application of FL, an important but also challenging issue is to motivate as many participants as possible to provide high-quality data to FL. In this paper, we propose an incentive mechanism for FL based on the continuous zero-determinant(CZD) strategies from the perspective of game theory. We first model the interaction between the server and the devices during the FL process as a continuous iterative game. We then apply the CZD strategies for two players and then multiple players to optimize the social welfare of FL, for which we prove that the server can keep social welfare at a high and stable level. Subsequently, we design an incentive mechanism based on the CZD strategies to attract devices to contribute all of their high-accuracy data to FL.Finally, we perform simulations to demonstrate that our proposed CZD-based incentive mechanism can indeed generate high and stable social welfare in FL.

Multi-timescale Modeling and Dynamic Stability Analysis for Sustainable Microgrids:State-of-the-art and Perspectives

The increasing trend for integrating renewable energy sources into the grid to achieve a cleaner energy system is one of the main reasons for the development of sustainable microgrid(MG)technologies.As typical power-electronized power systems,MGs make extensive use of power electronics converters,which are highly controllable and flexible but lead to a profound impact on the dynamic performance of the whole system.Compared with traditional large-capacity power systems,MGs are less resistant to perturbations,and various dynamic variables are coupled with each other on multiple timescales,resulting in a more complex system instability mechanism.To meet the technical and economic challenges,such as active and reactive power-sharing,voltage,and frequency deviations,and imbalances between power supply and demand,the concept of hierarchical control has been introduced into MGs,allowing systems to control and manage the high capacity of renewable energy sources and loads.However,as the capacity and scale of the MG system increase,along with a multi-timescale control loop design,the multi-timescale interactions in the system may become more significant,posing a serious threat to its safe and stable operation.To investigate the multi-timescale behaviors and instability mechanisms under dynamic inter-actions for AC MGs,existing coordinated control strategies are discussed,and the dynamic stability of the system is defined and classified in this paper.Then,the modeling and assessment methods for the stability analysis of multi-timescale systems are also summarized.Finally,an outlook and discussion of future research directions for AC MGs are also presented.

Disturbance Observer Based Speed Control of PMSM Using Fractional Order PI Controller

In this paper, fractional order PI(FOPI) control is developed for speed control of permanent magnet synchronous motor(PMSM). Designing the parameters for FOPI controller is a challenging task, especially for nonlinear systems like PMSM.All three PI controllers in the conventional vector controlled speed drive are replaced by FOPI controllers. Design of these FOPI controllers is based on the locally linearized model of PMSM around an operating point. This operating point changes with the load torque. The novelty of the work reported here is in use of Non Linear Disturbance Observer(NLDO) to estimate load torque to obtain this new operating point. All three FOPI controllers are then designed adaptively using this new operating point. The scheme is tested on simulation using MATLAB/SIMULINK and results are presented.

Design and Implementation of Digital Fractional Order PID Controller Using Optimal Pole-Zero Approximation Method for Magnetic Levitation System

The aim of this paper is to employ fractional order proportional integral derivative(FO-PID)controller and integer order PID controller to control the position of the levitated object in a magnetic levitation system(MLS),which is inherently nonlinear and unstable system.The proposal is to deploy discrete optimal pole-zero approximation method for realization of digital fractional order controller.An approach of phase shaping by slope cancellation of asymptotic phase plots for zeros and poles within given bandwidth is explored.The controller parameters are tuned using dynamic particle swarm optimization(d PSO)technique.Effectiveness of the proposed control scheme is verified by simulation and experimental results.The performance of realized digital FO-PID controller has been compared with that of the integer order PID controllers.It is observed that effort required in fractional order control is smaller as compared with its integer counterpart for obtaining the same system performance.

Bayesian Multidimensional Scaling for Location Awareness in Hybrid-Internet of Underwater Things

Localization of sensor nodes in the internet of underwater things(IoUT)is of considerable significance due to its various applications,such as navigation,data tagging,and detection of underwater objects.Therefore,in this paper,we propose a hybrid Bayesian multidimensional scaling(BMDS)based localization technique that can work on a fully hybrid IoUT network where the nodes can communicate using either optical,magnetic induction,and acoustic technologies.These communication technologies are already used for communication in the underwater environment;however,lacking localization solutions.Optical and magnetic induction communication achieves higher data rates for short communication.On the contrary,acoustic waves provide a low data rate for long-range underwater communication.The proposed method collectively uses optical,magnetic induction,and acoustic communication-based ranging to estimate the underwater sensor nodes’final locations.Moreover,we also analyze the proposed scheme by deriving the hybrid Cramer-Rao lower bound(H-CRLB).Simulation results provide a complete comparative analysis of the proposed method with the literature.

A Review of Nonlinear Kalman Filter Appling to Sensorless Control for AC Motor Drives

Sensorless control of AC motor drives,which takes the advantages of cost saving,higher reliability,and less hardware,has been developed for several decades.Among the existing speed sensorless control methods,nonlinear Kalman filter-based one has attached widespread attention due to its superb estimation accuracy and inherent resistibility to noise.However,the determination of noise covariance matrix and robustness of model uncertainties are still open issues in practice.A great number of studies try to solve these problems in resent years.This paper reviews the application of extended Kalman filter(EKF),unscented Kalman filter(UKF),and cubature Kalman filter(CKF)in speed sensorless control for AC motor drives.As an iterative algorithm,EKF has advantages in processor implementation.However,EKF suffers from the linearization error and model uncertainties when applying to sensorless control system.This paper presents the predominant improvements of EKF which is also applicative in UKF and CKF mostly.

A Study on Development of a Hybrid Aerial/Terrestrial Robot System for Avoiding Ground Obstacles by Flight

To date, many studies related to robots have been performed around the world. Many of these studies have assumed operation at locations where entry is difficult, such as disaster sites, and have focused on various terrestrial robots, such as snake-like, humanoid, spider-type, and wheeled units. Another area of active research in recent years has been aerial robots with small helicopters for operation indoors and outdoors. However,less research has been performed on robots that operate both on the ground and in the air. Accordingly, in this paper, we propose a hybrid aerial/terrestrial robot system. The proposed robot system was developed by equipping a quadcopter with a mechanism for ground movement. It does not use power dedicated to ground movement, and instead uses the flight mechanism of the quadcopter to achieve ground movement as well. Furthermore, we addressed the issue of obstacle avoidance as part of studies on autonomous control. Thus, we found that autonomous control of ground movement and flight was possible for the hybrid aerial/terrestrial robot system, as was autonomous obstacle avoidance by flight when an obstacle appeared during ground movement.

Development of a Consequent Pole Transverse Flux Permanent Magnet Linear Machine with Passive Secondary Structure

Transverse-flux machines have the advantage of high force density owing to the peculiarity of decoupling of electric loading and magnetic loading.In this paper,a novel consequent-pole transverse-flux permanent magnet linear machine(CP-TFPMLM)is proposed and investigated.The origination of the proposed machine is from an existing transverse-flux flux-reversal linear machine(TF-FRLM),by partially replacing permanent magnet poles with soft magnetic iron for further reducing the cost of magnets.The fundamental structure and operating principle are introduced at first.The electromagnetic performance,including back EMF,detent force,and thrust force,are investigated with the finite element method.The proposed machine can achieve similar performance as compared to the TF-FRLM but with half of the magnets are used.

The Power Allocation Game on A Network:A Paradox

The well-known Braess paradox in congestion games states that adding an additional road to a transportation network may increase the total travel time, and consequently decrease the overall efficiency. This paper presents a paradox in a similar spirit and involves a distributed resource allocation game on networks, namely the power allocation game between countries developed in Li and Morse(2017). The paradox is that by having additional friends may actually decrease a country's total welfare in equilibrium. Conditions for this paradox to occur as well as the price of anarchy results are also derived.

A Low Complexity Algorithm for Subcarrier-and-Bit Allocation in OFDMA-Based LTE Systems

In this paper, we propose optimum and sub-optimum resource allocation and opportunistic scheduling solutions for orthogonal frequency division multiple access （OFDMA）-based multicellular systems. The applicability, complexity, and performance of the proposed algorithms are analyzed and numerically evaluated. In the initial setup, the fractional frequency reuse （FFR） technique for inter-cell interference cancellation is applied to classify the users into two groups, namely interior and exterior users. Adaptive modulation is then employed according to the channel state information （CSI） of each user to meet the symbol error rate （SER） requirement. There then, we develop subcarrier-and-bit allocation method, which maximizes the total system throughput subject to the constraints that each user has a minimum data rate requirement. The algorithm to achieve the optimum solution requires high computational complexity which hinders it from practicability. Toward this suboptimum method with the reduced to the order of O（NIO, the total number of subcarriers end, we complexity propose a extensively where N and K denote and users, respectively. Numerical results show that the proposed algorithm approaches the optimum solution, yet it enjoys the features of simplicity, dynamic cell configuration, adaptive subearrier-and-bit allocation, and spectral efficiency.

Effect of Effective Grain Size and Grain Boundary of Large Misorientation on Upper Shelf Energy in Pipeline Steels

X65, X70, and X80 belong to high grade pipeline steels. Toughness is one of the most important properties of pipeline steels when the pipeline transports the gas or oil, and the means to control toughness is very important for exploring even higher grade pipeline steels. We established the relationship between toughness and crystallographic parameters of high grade pipeline steels by studying the crystallographic parameters of X65, X70, and X80 using EBSD and analyzing Charpy CVN of X65, X70 and X80. The results show that the effective grain size, the frequency distribution of grain boundary misorientation and the ratio of high angle grain boundary to small angle grain boundary are important parameters. The finer the effective grain size, and the higher the frequency distribution of grain boundaries （〉 50~）, the more excellent toughness of high grade pipeline steels will be.