Showing papers in "IEEE Transactions on Industrial Electronics in 2016"

Disturbance-Observer-Based Control and Related Methods—An Overview

Abstract: Disturbance-observer-based control (DOBC) and related methods have been researched and applied in various industrial sectors in the last four decades. This survey, at first time, gives a systematic and comprehensive tutorial and summary on the existing disturbance/uncertainty estimation and attenuation techniques, most notably, DOBC, active disturbance rejection control, disturbance accommodation control, and composite hierarchical antidisturbance control. In all of these methods, disturbance and uncertainty are, in general, lumped together, and an observation mechanism is employed to estimate the total disturbance. This paper first reviews a number of widely used linear and nonlinear disturbance/uncertainty estimation techniques and then discusses and compares various compensation techniques and the procedures of integrating disturbance/uncertainty compensation with a (predesigned) linear/nonlinear controller. It also provides concise tutorials of the main methods in this area with clear descriptions of their features. The application of this group of methods in various industrial sections is reviewed, with emphasis on the commercialization of some algorithms. The survey is ended with the discussion of future directions.

An Intelligent Fault Diagnosis Method Using Unsupervised Feature Learning Towards Mechanical Big Data

Abstract: Intelligent fault diagnosis is a promising tool to deal with mechanical big data due to its ability in rapidly and efficiently processing collected signals and providing accurate diagnosis results. In traditional intelligent diagnosis methods, however, the features are manually extracted depending on prior knowledge and diagnostic expertise. Such processes take advantage of human ingenuity but are time-consuming and labor-intensive. Inspired by the idea of unsupervised feature learning that uses artificial intelligence techniques to learn features from raw data, a two-stage learning method is proposed for intelligent diagnosis of machines. In the first learning stage of the method, sparse filtering, an unsupervised two-layer neural network, is used to directly learn features from mechanical vibration signals. In the second stage, softmax regression is employed to classify the health conditions based on the learned features. The proposed method is validated by a motor bearing dataset and a locomotive bearing dataset, respectively. The results show that the proposed method obtains fairly high diagnosis accuracies and is superior to the existing methods for the motor bearing dataset. Because of learning features adaptively, the proposed method reduces the need of human labor and makes intelligent fault diagnosis handle big data more easily.

Real-Time Motor Fault Detection by 1-D Convolutional Neural Networks

Abstract: Early detection of the motor faults is essential and artificial neural networks are widely used for this purpose. The typical systems usually encapsulate two distinct blocks: feature extraction and classification. Such fixed and hand-crafted features may be a suboptimal choice and require a significant computational cost that will prevent their usage for real-time applications. In this paper, we propose a fast and accurate motor condition monitoring and early fault-detection system using 1-D convolutional neural networks that has an inherent adaptive design to fuse the feature extraction and classification phases of the motor fault detection into a single learning body. The proposed approach is directly applicable to the raw data (signal), and, thus, eliminates the need for a separate feature extraction algorithm resulting in more efficient systems in terms of both speed and hardware. Experimental results obtained using real motor data demonstrate the effectiveness of the proposed method for real-time motor condition monitoring.

Modern Advances in Wireless Power Transfer Systems for Roadway Powered Electric Vehicles

Abstract: Wireless power transfer system (WPTS)-based wireless electric vehicles, classified into roadway-powered electric vehicles (RPEVs) and stationary charging electric vehicles (SCEVs), are in the spotlight as future mainstream transportations. RPEVs are free from serious battery problems such as large, heavy, and expensive battery packs and long charging time because they get power directly from the road while moving. The power transfer capacity, efficiency, lateral tolerance, electromagnetic field, air-gap, size, weight, and cost of the WPTSs have been improved by virtues of innovative semiconductor switches, better coil designs, roadway construction techniques, and higher operating frequency. Recent advances in WPTSs for RPEVs are summarized in this review paper. The fifth- and sixth-generation online electric vehicles, which reduce infrastructure cost for commercialization, and the interoperability between RPEVs and SCEVs are addressed in detail in this paper. Major milestones of the developments of other RPEVs are also summarized. The rest of this paper deals with a few important technical issues such as coil structures, power supply schemes, and segmentation switching techniques of a lumped inductive power transfer system for RPEVs.

Recent Advances in the Design, Modeling, and Control of Multiphase Machines—Part II

Abstract: The main objective of this two-part state-of-the-art paper called “Recent Advances in the Design, Modeling, and Control of Multiphase Machines” is to present latest contributions in the multiphase machines' field. The first part of this paper focuses on the recent progress in the design, modeling, and control, whereas the drive is in healthy operation. This second part presents relevant contributions in two not analyzed fields. The first is in relation with the use of the additional degrees of freedom of multiphase machines and the exploitation of their fault-tolerant capabilities without adding extra hardware. The second one analyzes multiphase generation, particularly in grid-connected wind energy conversion systems and stand-alone applications. Recent progresses are shown and open challenges and future research directions are discussed.

Advances in Converter Control and Innovative Exploitation of Additional Degrees of Freedom for Multiphase Machines

Abstract: Multiphase variable-speed drives and generation systems (systems with more than three phases) have become one of the mainstream research areas during the last decade. The main driving forces are the specific applications, predominantly related to the green agenda, such as electric and hybrid electric vehicles (EVs), locomotive traction, ship propulsion, “more-electric” aircraft, remote offshore wind farms for electric energy generation, and general high-power industrial applications. As a result, produced body of significant work is substantial, making it impossible to review all the major developments in a single paper. This paper therefore surveys the recent progress in two specific areas associated with multiphase systems, namely power electronic supply control and innovative ways of using the additional degrees of freedom in multiphase machines for various nontraditional purposes.

Robust Backstepping Sliding-Mode Control and Observer-Based Fault Estimation for a Quadrotor UAV

Abstract: This study gives the mathematic model of a quadrotor unmanned aerial vehicle (UAV) and then proposes a robust nonlinear controller which combines the sliding-mode control technique and the backstepping control technique. To achieve Cartesian position trajectory tracking capability, the construction of the controller can be divided into two stages: a regular SMC controller for attitude subsystem (inner loop) is first developed to guarantee fast convergence rapidity of Euler angles and the backstepping technique is applied to the position loop until desired attitudes are obtained and then the ultimate control laws. The stability of the closed-loop system is guaranteed by stabilizing each of the subsystems step by step and the robustness of the controller against model uncertainty and external disturbances is investigated. In addition, an adaptive observer-based fault estimation scheme is also considered for taking off mode. Simulations are conducted to demonstrate the effectiveness of the designed robust nonlinear controller and the fault estimation scheme.

Small-Signal Modeling and Parameters Design for Virtual Synchronous Generators

Abstract: The concept of the virtual synchronous generator (VSG) is emerging as an attractive solution for controlling the grid-connected inverter when the renewable energy has a high penetration level into the grid. This paper focuses on the small-signal modeling and parameters design of the power loop of the VSG, and points out that the bandwidth of the power loop should be far less than twice the line frequency for the purpose of avoiding the VSG output voltage to be severely distorted. Consequently, the line-frequency-averaged small-signal model of the VSG is derived for system analysis and parameters design. Based on the model, the decoupling conditions between the active power loops (APLs) and the reactive power loops (RPLs) of the VSG are given. Finally, a step-by-step parameters design method is proposed to facilitate the design of the control parameters of the VSG. A 10-kVA prototype is built and tested in the laboratory, and the experimental results are given to verify the effectiveness of the theoretical analysis and the proposed parameters design method.

Implementation of Super-Twisting Control: Super-Twisting and Higher Order Sliding-Mode Observer-Based Approaches

Abstract: In this paper, an output feedback stabilization of perturbed double-integrator systems using super-twisting control (STC) is studied. It is shown that when STC is implemented based on super-twisting observer (STO), then it is not possible to achieve second-order sliding mode (SOSM) using continuous control on the chosen sliding surface. Two methodologies are proposed to circumvent the above-mentioned problem. In the first method, control input is discontinuous, which may not be desirable for practical systems. In the second method, continuous STC is proposed based on higher order sliding mode observer (HOSMO) that achieves SOSM on the chosen sliding surface. For simplicity, we are considering here only the perturbed double integrator, which can be generalized for an arbitrary-order systems. Numerical simulations and experimental validation are also presented to show the effectiveness of the proposed method.

Research on the Performances and Parameters of Interior PMSM Used for Electric Vehicles

Abstract: As a kind of traction device, interior permanent-magnet synchronous machines (IPMSMs) are widely used in modern electric vehicles. This paper performs a design and comparative study of IPMSMs with different rotor topologies (spoke-type PMs, tangential-type PMs, U-shape PMs, and V-shape PMs). The research results indicate that the IPMSM with V-shape PMs is more satisfying with comprehensive consideration. Furthermore, the IPMSM with V-shape PMs is investigated in detail. The influences of geometrical parameters (magnetic bridge and angle between the two V-shape PMs under each pole, etc.) on the performances of V-shape motor are evaluated based on finite-element method (FEM). For accurate research, the effects of saturation, cross-magnetization, and the change in PM flux linkage on d - and q -axis inductances are considered. The back-electromotive force (EMF), flux leakage coefficient, average torque, torque ripple, cogging torque, power per unit volume, power factor, and flux-weakening ability are investigated, respectively. The experimental results verify the validity and accuracy of the process presented in this paper.

Battery Health Prognosis for Electric Vehicles Using Sample Entropy and Sparse Bayesian Predictive Modeling

Abstract: Battery health monitoring and management is of extreme importance for the performance and cost of electric vehicles. This paper is concerned with machine-learning-enabled battery state-of-health (SOH) indication and prognosis. The sample entropy of short voltage sequence is used as an effective signature of capacity loss. Advanced sparse Bayesian predictive modeling (SBPM) methodology is employed to capture the underlying correspondence between the capacity loss and sample entropy. The SBPM-based SOH monitor is compared with a polynomial model developed in our prior work. The proposed approach allows for an analytical integration of temperature effects such that an explicitly temperature-perspective SOH estimator is established, whose performance and complexity is contrasted to the support vector machine (SVM) scheme. The forecast of remaining useful life is also performed via a combination of SBPM and bootstrap sampling concepts. Large amounts of experimental data from multiple lithium-ion battery cells at three different temperatures are deployed for model construction, verification, and comparison. Such a multi-cell setting is more useful and valuable than only considering a single cell (a common scenario). This is the first known application of combined sample entropy and SBPM to battery health prognosis.

Motor Bearing Fault Detection Using Spectral Kurtosis-Based Feature Extraction Coupled With K -Nearest Neighbor Distance Analysis

Abstract: Bearing faults are the main contributors to the failure of electric motors. Although a number of vibration analysis methods have been developed for the detection of bearing faults, false alarms still result in losses. This paper presents a method that detects bearing faults and monitors the degradation of bearings in electric motors. Based on spectral kurtosis (SK) and cross correlation, the method extracts fault features that represent different faults, and the features are then combined to form a health index using principal component analysis (PCA) and a semisupervised k -nearest neighbor (KNN) distance measure. The method was validated by experiments using a machinery fault simulator and a computer cooling fan motor bearing. The method is able to detect incipient faults and diagnose the locations of faults under masking noise. It also provides a health index that tracks the degradation of faults without missing intermittent faults. Moreover, faulty reference data are not required.

A New Adaptive Sliding-Mode Control Scheme for Application to Robot Manipulators

Abstract: This paper presents a new adaptive sliding-mode control (ASMC) scheme that uses the time-delay estimation (TDE) technique, then applies the scheme to robot manipulators. The proposed ASMC uses a new adaptive law to achieve good tracking performance with small chattering effect. The new adaptive law considers an arbitrarily small vicinity of the sliding manifold, in which the derivatives of the adaptive gains are inversely proportional to the sliding variables. Such an adaptive law provides remarkably fast adaptation and chattering reduction near the sliding manifold. To yield the desirable closed-loop poles and simplify a complicated system model by adapting feedback compensation, the proposed ASMC scheme works together with a pole-placement control (PPC) and a TDE technique. It is shown that the tracking errors of the proposed ASMC scheme are guaranteed to be uniformly ultimately bounded (UUB) with arbitrarily small bound. The practical effectiveness and the fast adaptation of the proposed ASMC are illustrated in simulations and experiments with robot manipulators, and compared with those of an existing ASMC.

The Essential Role and the Continuous Evolution of Modulation Techniques for Voltage-Source Inverters in the Past, Present, and Future Power Electronics

Abstract: The cost reduction of power-electronic devices, the increase in their reliability, efficiency, and power capability, and lower development times, together with more demanding application requirements, has driven the development of several new inverter topologies recently introduced in the industry, particularly medium-voltage converters. New more complex inverter topologies and new application fields come along with additional control challenges, such as voltage imbalances, power-quality issues, higher efficiency needs, and fault-tolerant operation, which necessarily requires the parallel development of modulation schemes. Therefore, recently, there have been significant advances in the field of modulation of dc/ac converters, which conceptually has been dominated during the last several decades almost exclusively by classic pulse-width modulation (PWM) methods. This paper aims to concentrate and discuss the latest developments on this exciting technology, to provide insight on where the state-of-the-art stands today, and analyze the trends and challenges driving its future.

Recent Advances on Fuzzy-Model-Based Nonlinear Networked Control Systems: A Survey

Abstract: In recent years, the analysis and synthesis of fuzzy-model-based nonlinear networked control systems (NCSs) have received increasing attention from both scientific and industrial communities, and a number of significant results have been proposed. This paper gives a review on recent advances on the analysis and design of fuzzy-model-based nonlinear NCSs with various network-induced limitations such as packet dropouts, time delays, and signal quantization. With these network-induced constraints, the developments on various control and filtering design issues are surveyed in details, and some essential technical difficulties are mentioned. Then, some latest results on event-triggered control and filtering design of fuzzy-model-based nonlinear NCSs are also summarized. Finally, some conclusions are drawn and several potential future research topics are highlighted.

Network-Based Event-Triggered Control for Singular Systems With Quantizations

Abstract: This paper investigates the problem of event-triggered $H_{\infty}$ control for a networked singular system with both state and input subject to quantizations. First, a discrete event-triggered scheme, which activates only at each sampling instance, is presented. Next, two new sector bound conditions of quantizers are proposed to provide a more intuitive stability analysis and controller design. Then, network conditions, quantizations, and the event-triggered scheme are modeled as a time-delay system. With this model, the criteria are derived for $H_{\infty}$ performance analysis, and codesigning methods are developed for the event trigger and the quantized state feedback controller. An inverted pendulum controlled through the network is given to demonstrate the effectiveness and potential of the new design techniques.

A Robust Observer-Based Sensor Fault-Tolerant Control for PMSM in Electric Vehicles

Abstract: This paper investigates the problem of automatic speed tracking control of an electric vehicle (EV) that is powered by a permanent-magnet synchronous motor (PMSM). A reconfiguration scheme, based on higher order sliding mode (HOSM) observer, is proposed in the event of sensor faults/failures to maintain a good control performance. The corresponding controlled motor output torque drives EVs to track the desired vehicle reference speed for providing uninterrupted vehicle safe operation. The effectiveness of the overall sensor fault-tolerant speed tracking control is highlighted when an EV is subjected to disturbances like aerodynamic load force and road roughness using high-fidelity software package CarSim. Experiments with a 26-W, three-phase PMSM are presented to demonstrate the validity of the proposed fault-detection scheme.

Event-Triggering Load Frequency Control for Multiarea Power Systems With Communication Delays

Abstract: This paper studies the load frequency control (LFC) for power systems with communication delays via an event-triggered control method to reduce the amount of communications required. The effect of the load disturbances on the augmented output is defined as a robust performance index of the augmented LFC scheme. By utilizing a time-delayed system design approach, a new model of the LFC scheme with delays is formulated, where the communication delays and event-triggered control are integrated for the LFC scheme. Based on the Lyapunov–Krasovskii functional method, the criteria for the event-triggered stability analysis and control synthesis of the LFC scheme are derived. Finally, the effectiveness of the proposed method is verified by simulation studies.

Performance-Driven Distributed PCA Process Monitoring Based on Fault-Relevant Variable Selection and Bayesian Inference

Abstract: Multivariate statistical process monitoring involves dimension reduction and latent feature extraction in large-scale processes and typically incorporates all measured variables. However, involving variables without beneficial information may degrade monitoring performance. This study analyzes the effect of variable selection on principal component analysis (PCA) monitoring performance. Then, it proposes a fault-relevant variable selection and Bayesian inference-based distributed method for efficient fault detection and isolation. First, the optimal subset of variables is identified for each fault using an optimization algorithm. Second, a sub-PCA model is established in each subset. Finally, the monitoring results of all of the subsets are combined through Bayesian inference. The proposed method reduces redundancy and complexity, explores numerous local behaviors, and provides accurate description of faults, thus improving monitoring performance significantly. Case studies on a numerical example, the Tennessee Eastman benchmark process, and an industrial-scale plant demonstrate the efficiency.

Robust Model-Based Fault Diagnosis for PEM Fuel Cell Air-Feed System

Abstract: In this paper, the design of a nonlinear observer-based fault diagnosis approach for polymer electrolyte membrane (PEM) fuel cell air-feed systems is presented, taking into account a fault scenario of sudden air leak in the air supply manifold. Based on a simplified nonlinear model proposed in the literature, a modified super-twisting (ST) sliding mode algorithm is employed to the observer design. The proposed ST observer can estimate not only the system states, but also the fault signal. Then, the residual signal is computed online from comparisons between the oxygen excess ratio obtained from the system model and the observer system, respectively. Equivalent output error injection using the residual signal is able to reconstruct the fault signal, which is critical in both fuel cell control design and fault detection. Finally, the proposed observer-based fault diagnosis approach is implemented on the MATLAB/Simulink environment in order to verify its effectiveness and robustness in the presence of load variation.

Unified Triple-Phase-Shift Control to Minimize Current Stress and Achieve Full Soft-Switching of Isolated Bidirectional DC–DC Converter

Abstract: This paper presents a comprehensive analysis of the current-stress optimization and soft-switching operation of the isolated bidirectional dual active bridge (DAB) dc–dc converter with the unified triple-phase-shift (UTPS) control. On this basis, the current-stress-optimized modulation scheme is proposed for DAB, which leads to the minimum current stress with the required transmission power and voltage conversion ratio in the whole load range. Moreover, the full soft-switching operation is achieved for the converter simultaneously. Distinct from the previous modulation schemes, the proposed optimized modulation scheme is deduced from a unified analysis of TPS where all effective switching modes are investigated. A novel algorithm based on the Karush–Kuhn–Tucker (KKT) conditions is originally proposed to derive closed-form solutions for the global optimal control parameters. This paper also presents a typical closed-loop control strategy for DAB with TPS control and detailed descriptions about the closed-loop operation. A laboratory prototype is applied, and the experimental results validate that the current-stress optimization and efficiency improvement are realized by applying the optimized modulation scheme. The experimental results also verify the effectiveness of the closed-loop control strategy for DAB with TPS control.

Unknown Input Observer-Based Robust Fault Estimation for Systems Corrupted by Partially Decoupled Disturbances

Abstract: Robust fault estimation plays an important role in real-time monitoring, diagnosis, and fault-tolerance control. Accordingly, this paper aims to develop an effective fault estimation technique to simultaneously estimate the system states and the concerned faults, while minimizing the influences from process/sensor disturbances. Specifically, an augmented system is constructed by forming an augmented state vector composed of the system states and the concerned faults. Next, an unknown input observer (UIO) is designed for the augmented system by decoupling the partial disturbances and attenuating the disturbances that cannot be decoupled, leading to a simultaneous estimate of the system states and the concerned faults. In order to be close to the practical engineering situations, the process disturbances in this study are assumed not to be completely decoupled. In the first part of this paper, the existence condition of such an UIO is proposed to facilitate the fault estimation for linear systems subjected to process disturbances. In the second part, robust fault estimation techniques are addressed for Lipschitz nonlinear systems subjected to both process and sensor disturbances. The proposed technique is finally illustrated by the simulation studies of a three-shaft gas turbine engine and a single-link flexible joint robot.

An Envelope Type (E-Type) Module: Asymmetric Multilevel Inverters With Reduced Components

Abstract: This paper presents a new E-type module for asymmetrical multilevel inverters (MLIs) with reduced components. Each module produces 13 levels with four unequal dc sources and 10 switches. The design of the proposed module makes some preferable features with a better quality than similar modules such as the low number of semiconductors and dc sources and low switching frequency. Also, this module is able to create a negative level without any additional circuit such as an H-bridge, which causes reduction of voltage stress on switches. Cascade connection of the proposed structure leads to a modular topology with more levels and higher voltages. Selective harmonics elimination pulse width modulation (SHE-PWM) scheme is used to achieve high-quality output voltage with lower harmonics. MATLAB simulations and practical results are presented to validate the proposed module good performance. Module output voltage satisfies harmonics standard (IEEE519) without any filter in output.

Practical Tracking Control of Robot Manipulators With Continuous Fractional-Order Nonsingular Terminal Sliding Mode

Abstract: This paper studies practical tracking control design of robot manipulators with continuous fractional-order nonsingular terminal sliding mode (CFONTSM) based on time-delay estimation (TDE). The proposed control design requires no detailed information about the robot dynamics, leading to an attractive model-free nature thanks to TDE, and ensures fast convergence and high tracking precision under heavy lumped uncertainties due to the FONTSM surface and fast-TSM-type reaching law. Stability of the closed-loop system and finite-time convergence are analyzed using Lyapunov stability theory. Comparative 2-DOF (degree of freedom) simulation and experiment results show that the proposed control design can ensure higher tracking precision and faster convergence compared with TDE-based continuous integer-order NTSM (CIONTSM) design in a wide range of speed; meanwhile, better performance is also observed compared with TDE-based IONTSM and FONTSM control designs using a boundary layer technique.

A Review on Recent Development of Spacecraft Attitude Fault Tolerant Control System

Abstract: Motivated by several accidents, attitude control of a spacecraft subject to faults/failures has gained considerable attention in a wider range of aerospace engineering and academic communities. This paper is concerned with industrial practices and theoretical approaches for fault tolerant control (FTC) and fault detection and diagnosis (FDD) in spacecraft attitude control system. An overview on recent development of spacecraft attitude FTC system design is presented. The basis of a FTC system is introduced. The existing engineering FTC techniques and theoretical methodologies, including their advantages and disadvantages, are discussed. Moreover, closely associated with the reliability-relevant issues, recent progress in attitude FTC design strategies is reviewed. A brief review of some open problems in the general area of spacecraft attitude control design subject to components faults/failures is further concluded.

Neural Learning Control of Marine Surface Vessels With Guaranteed Transient Tracking Performance

Abstract: This paper studies neural learning control with predefined tracking error bound for a marine surface vessel whose accurate dynamics could not be obtained a priori . With the introduction of an error transformation function, the constrained tracking control of the original vessel is transformed into the stabilization of an unconstrained system. A filtered tracking error is introduced based on the error transformation, and radial basis function (RBF) neural networks (NNs) are employed to approximate unknown vessel dynamics. Subsequently, stable adaptive NN control is proposed to ensure ultimate boundedness of all the signals in the closed-loop system and to guarantee prescribed tracking performances. Under persistent excitation (PE) condition, the proposed adaptive NN control is shown to be capable of acquiring knowledge on the vessel dynamics and of storing the learned knowledge in memory. The stored knowledge is reused to develop neural learning control such that the improved control performance with faster tracking convergence rate and less computational burden could be achieved, while prescribed transient and steady-state tracking control performances are guaranteed. Simulation studies are performed to demonstrate the effectiveness of the proposed design techniques.

Tracking Control of Networked Multi-Agent Systems Under New Characterizations of Impulses and Its Applications in Robotic Systems

Abstract: This paper examines the problem of tracking control of networked multi-agent systems with multiple delays and impulsive effects, whose results are applied to mechanical robotic systems. Four kinds of impulsive effects are taken into account: 1) both the strengths of impulsive effects and the number of nodes injected with impulses are time dependent; 2) the strengths of impulsive effects occur according to certain probabilities and the number of nodes under impulsive control is time varying; 3) the strengths of impulses are time varying, whereas the number of nodes with impulses takes place according to certain probabilities; 4) both the strengths of impulses and the number of nodes with impulsive control occur according to certain probabilities. By utilizing the comparison principle, criteria are established for these different cases and a relationship between the frequencies (occurrence probabilities) of impulses and systems' parameters is unveiled. Finally, an example for tracking control of robotic systems is provided to show the effectiveness of the presented results.

Characteristics and Design of Power Hardware-in-the-Loop Simulations for Electrical Power Systems

Abstract: This paper presents a compendious summary of power hardware-in-the-loop (PHIL) simulations that are used for designing, analyzing, and testing of electrical power system components. PHIL simulations are an advanced application of real-time simulations that represent novel methods, which conjoin software and hardware testing. This contribution outlines necessary requirements for the implementation of PHIL simulations, which are defined by the nature of the digital real-time simulator, the power amplifier, and the power interface (PI). Fundamental characteristics, such as the input/output systems, PI, interface algorithm, and system stability considerations, are discussed for PHIL setups, in order to illustrate both flexibility and complexity of this compound simulation method. The objective of this work is to elaborate an understandable overview of PHIL simulation for electrical power systems and to constitute a contemporary state-of-the-art status of this research area.

An LCC-Compensated Resonant Converter Optimized for Robust Reaction to Large Coupling Variation in Dynamic Wireless Power Transfer

Abstract: In this paper, a reformed compensation network based on traditional LCL topology is proposed to realize robust reaction to large coupling variation that is common in dynamic wireless charging application. From the perspective of smoothing, the power characteristic against coupling factor and to achieve high efficiency simultaneously, extra reactive element is inserted into the resonant tank to provide higher degree of design freedom, forming the improved LCC type compensated inductive power transfer (IPT) system that features with distinct parameter design approach. Comparing to existing compensation topologies, the optimized LCC compensation topology shows more robust power characteristic against variation of coupling factor and, thus, minimizes the need for complex control which is usually undesired in dynamic charging scheme, thereby helping maintain effective power transfer in dynamic charging application and largely enhancing the systematic controllability. Finally, the effectiveness of the proposed method is experimentally verified. The power transfer profile is smooth against coupling factor to realize high tolerance to position as the power drop is no more than 20% within almost 200% of coupling factor variation.

Disturbance Observer-Based Integral Sliding-Mode Control for Systems With Mismatched Disturbances

Abstract: This paper develops the disturbance observer-based integral sliding-mode control approach for continuous-time linear systems with mismatched disturbances or uncertainties. The disturbance observer is proposed to generate the disturbance estimate, which can be incorporated in the controller to counteract the disturbance. With the help of the proposed disturbance observer, both the memoryless and memory-based integral sliding surfaces and integral sliding-mode controllers are developed, respectively, and two approaches, i.e., $H_\infty$ control and steady-state output-based approaches, are proposed to design the controller and disturbance rejection gains. Finally, the effectiveness and applicability of the proposed technique are illustrated by a numerical example and a real-time experiment.