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Electronics
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Advanced Control Systems for Electric Drives
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Advanced Control Systems for Electric Drives

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Electrical and Autonomous Vehicles".

Deadline for manuscript submissions: closed (31 July 2020) | Viewed by 68444

Printed Edition Available!
A printed edition of this Special Issue is available here.

Special Issue Editor

Dr. Adel Merabet

E-Mail Website
Guest Editor
Division of Engineering, Saint Mary’s University, Halifax, NS B3H 3C3, Canada
Interests: renewable energy; smart microgrid; control; estimation; artificial intelligence; automation; robotics
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

In recent years, electric drives have attracted the attention of researchers in emerging fields such as electric vehicles (EV), renewable energy systems (wind, tidal, ocean, etc.) and high precision motion applications. Electric drives are composed of electrical machines, power electronic converters and control systems. Their efficient operation, for position and speed regulation, is determined by the control system. Furthermore, electric drives are a highly nonlinear, multivariable, time-varying system, depending on the type of the electrical machines, and require more complex methods of control. They constitute a theoretical and practical challenging control problem. The main aim of this Special Issue is to seek high-quality submissions that highlight advances in control techniques for electric drives, address the implementation challenges, and the use in emerging fields.

Topics of interest include but are not limited to the following:

  • Control algorithms for power electronics converters;
  • Adaptive control, robust control, predictive control, and sliding mode control;
  • Sensorless control;
  • Fault diagnosis and fault tolerant control;
  • Control of electric drives in electric vehicles (EV)l
  • Control of electric drives in renewable energy systems;
  • State and parameters estimation;
  • Artificial intelligence (neural network, fuzzy logic, etc.) control applications.

Dr. Adel Merabet
Guest Editor

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 2400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • Electric AC and DC drives
  • Advanced control
  • Precision control
  • Power converters
  • Fault detection and tolerance
  • Speed and torque control
  • Estimation and filtering
  • Control design and implementation

Published Papers (16 papers)

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Editorial

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4 pages, 163 KiB  
Editorial
Advanced Control for Electric Drives: Current Challenges and Future Perspectives
by Adel Merabet
Electronics 2020, 9(11), 1762; https://doi.org/10.3390/electronics9111762 - 23 Oct 2020
Cited by 5 | Viewed by 2450
Abstract
In the Special Issue “Advanced Control for Electric Drives”, the objective is to address a variety of issues related to advances in control techniques for electric drives, implementation challenges, and applications in emerging fields such as electric vehicles, unmanned aerial vehicles, maglev trains [...] Read more.
In the Special Issue “Advanced Control for Electric Drives”, the objective is to address a variety of issues related to advances in control techniques for electric drives, implementation challenges, and applications in emerging fields such as electric vehicles, unmanned aerial vehicles, maglev trains and motion applications. This issue includes 15 selected and peer-reviewed articles discussing a wide range of topics, where intelligent control, estimation and observation schemes were applied to electric drives for various applications. Different drives were studied such as induction motors, permanent magnet synchronous motors and brushless direct current motors. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)

Research

Jump to: Editorial

45 pages, 22479 KiB  
Article
Sensorless Fractional Order Control of PMSM Based on Synergetic and Sliding Mode Controllers
by Marcel Nicola and Claudiu-Ionel Nicola
Electronics 2020, 9(9), 1494; https://doi.org/10.3390/electronics9091494 - 11 Sep 2020
Cited by 26 | Viewed by 3184
Abstract
The field oriented control (FOC) strategy of the permanent magnet synchronous motor (PMSM) includes all the advantages deriving from the simplicity of using PI-type controllers, but inherently the control performances are limited due to the nonlinear model of the PMSM, the need for [...] Read more.
The field oriented control (FOC) strategy of the permanent magnet synchronous motor (PMSM) includes all the advantages deriving from the simplicity of using PI-type controllers, but inherently the control performances are limited due to the nonlinear model of the PMSM, the need for wide-range and high-dynamics speed and load torque control, but also due to the parametric uncertainties which occur especially as a result of the variation of the combined rotor-load moment of inertia, and of the load resistance. Based on the fractional calculus for the integration and differentiation operators, this article presents a number of fractional order (FO) controllers for the PMSM rotor speed control loops, and id and iq current control loops in the FOC-type control strategy. The main contribution consists of proposing a PMSM control structure, where the controller of the outer rotor speed control loop is of FO-sliding mode control (FO-SMC) type, and the controllers for the inner control loops of id and iq currents are of FO-synergetic type. Superior performances are obtained by using the control system proposed, even in the case of parametric variations. The performances of the proposed control system are validated both by numerical simulations and experimentally, through the real-time implementation in embedded systems. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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28 pages, 15188 KiB  
Article
Realization of the Neural Fuzzy Controller for the Sensorless PMSM Drive Control System
by Hung-Khong Hoai, Seng-Chi Chen and Chin-Feng Chang
Electronics 2020, 9(9), 1371; https://doi.org/10.3390/electronics9091371 - 24 Aug 2020
Cited by 14 | Viewed by 3494
Abstract
A neural fuzzy controller (NFC)-based speed controller for the sensorless permanent magnet synchronous motor (PMSM) drive control system is realized in this paper. The NFC is a fuzzy logic controller (FLC), which adjusts the RBFNN-based (radial basis function neural network) parameter by adapting [...] Read more.
A neural fuzzy controller (NFC)-based speed controller for the sensorless permanent magnet synchronous motor (PMSM) drive control system is realized in this paper. The NFC is a fuzzy logic controller (FLC), which adjusts the RBFNN-based (radial basis function neural network) parameter by adapting the dynamic system characteristics. For sensorless PMSM drive, the integration of sliding mode observer (SMO) and phase-locked loop (PLL) is executed to estimate the rotor position and speed. To eliminate the initial rotor position estimation and overcome the conventional PLL-based position estimation error in the direction reversion transition, the I-f control strategy is applied to start up the motor and change the rotational direction effectively. The system performance was verified in various experimental conditions. The simulation and experimental results indicate that the proposed control algorithm is implemented efficiently. The motor starts up with diverse external loads, operates in a wide speed range for both positive and negative directions, and reverses the rotational direction stably. Furthermore, the system presents robustness against disturbance and tracks the command speed properly. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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25 pages, 2305 KiB  
Article
Discrete-Time Neural Control of Quantized Nonlinear Systems with Delays: Applied to a Three-Phase Linear Induction Motor
by Alma Y. Alanis, Jorge D. Rios, Javier Gomez-Avila, Pavel Zuniga and Francisco Jurado
Electronics 2020, 9(8), 1274; https://doi.org/10.3390/electronics9081274 - 07 Aug 2020
Cited by 2 | Viewed by 2441
Abstract
This work introduces a neural-feedback control scheme for discrete-time quantized nonlinear systems with time delay. Traditionally, a feedback controller is designed under ideal assumptions that are unrealistic for real-work problems. Among these assumptions, they consider a perfect communication channel for controller inputs and [...] Read more.
This work introduces a neural-feedback control scheme for discrete-time quantized nonlinear systems with time delay. Traditionally, a feedback controller is designed under ideal assumptions that are unrealistic for real-work problems. Among these assumptions, they consider a perfect communication channel for controller inputs and outputs; such a perfect channel does not consider delays, or noise introduced by the sensors and actuators even if such undesired phenomena are well-known sources of bad performance in the systems. Moreover, traditional controllers are also designed based on an ideal plant model without considering uncertainties, disturbances, sensors, actuators, and other unmodeled dynamics, which for real-life applications are effects that are constantly present and should be considered. Furthermore, control system design implemented with digital processors implies sampling and holding processes that can affect the performance; considering and compensating quantization effects of measured signals is a problem that has attracted the attention of control system researchers. In this paper, a neural controller is proposed to overcome the problems mentioned above. This controller is designed based on a neural model using an inverse optimal approach. The neural model is obtained from available measurements of the state variables and system outputs; therefore, uncertainties, disturbances, and unmodeled dynamics can be implicitly considered from the available measurements. This paper shows the performance and effectiveness of the proposed controller presenting real-time results obtained on a linear induction motor prototype. Also, this work includes stability proof for the whole scheme using the Lyapunov approach. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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26 pages, 8964 KiB  
Article
Research on Harmonic Torque Reduction Strategy for Integrated Electric Drive System in Pure Electric Vehicle
by Jianjun Hu, Ying Yang, Meixia Jia, Yongjie Guan, Chunyun Fu and Shuiping Liao
Electronics 2020, 9(8), 1241; https://doi.org/10.3390/electronics9081241 - 01 Aug 2020
Cited by 15 | Viewed by 3760
Abstract
In order to study the influence of harmonic torque on the performance of the integrated electric drive system (permanent magnet synchronous motor + reducer gear pair) in a pure electric vehicle (PEV), the electromechanical coupling dynamic model of a PEV was established by [...] Read more.
In order to study the influence of harmonic torque on the performance of the integrated electric drive system (permanent magnet synchronous motor + reducer gear pair) in a pure electric vehicle (PEV), the electromechanical coupling dynamic model of a PEV was established by considering the dead-time effect and voltage drop effect of an inverter and the nonlinear characteristics of the transmission system. Based on the model, the dynamic characteristics of an integrated electric drive system (IEDS) are studied, and the interaction between the mechanical system and electrical system is analyzed. On this basis, a harmonic torque reduction strategy for an IEDS is proposed in this paper. The simulation results show that the proposed strategy can effectively reduce the harmonic torque of the motor and reduce the speed fluctuation and dynamic load of the system components, which can improve the stability of the IEDS and prolong the life of the mechanical components. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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12 pages, 4653 KiB  
Article
Hall-Sensor-Based Position Detection for Quick Reversal of Speed Control in a BLDC Motor Drive System for Industrial Applications
by Mohanraj Nandakumar, Sankaran Ramalingam, Subashini Nallusamy and Shriram Srinivasarangan Rangarajan
Electronics 2020, 9(7), 1149; https://doi.org/10.3390/electronics9071149 - 16 Jul 2020
Cited by 20 | Viewed by 3258
Abstract
This paper proposes the novel idea of eliminating the front-end converters used indirect current (DC) bus voltage variation, thereby allowing for control of the speed of the brushless direct current (BLDC) motors in the two-quadrant operation of a permanent magnet brushless direct current [...] Read more.
This paper proposes the novel idea of eliminating the front-end converters used indirect current (DC) bus voltage variation, thereby allowing for control of the speed of the brushless direct current (BLDC) motors in the two-quadrant operation of a permanent magnet brushless direct current (PMBLDC) motor, which is required for multiple bi-directional hot roughing steel rolling mills. The first phase of steel rolling, the manufacture of plates, strips etc., using hot slabs from the continuous casting stage, is carried out for thickness reduction, before the same is sent to the finishing mill for further mechanical processing. The hot roughing process involves applying high, compressive pressure, using a hydraulically operated mechanism, through a pair of backup rolls and work rolls for rolling. Overall, the processes consist of multiple passes of forward and reverse rolling at increasing roll speeds. The rolling process was modeled, taking into account parameters like roller dimensions, angle and length of contact, and rolling force, at various temperatures, using actual data obtained from a steel mill. From this data, speed and torque profiles at the motor shaft, covering the entire rolling process, were created. A profile-based feedback controller is proposed for setting the six-pulse inverter frequency and parameters of the pulse width modulated (PWM) waveform for current control, based on Hall sensor position, and the same is implemented for closed loop operation of the brushless direct current motor drive system. The performance enhancement of the two different controllers was also evaluated, during the rolling of 1005 hot rolled (HR) steel, and was taken into consideration in the research analysis. The entire process was simulated in the MATLAB/Simulink platform, and the results verify the suitability of an entire-drive system for industrial steel rolling applications. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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29 pages, 7153 KiB  
Article
Benchmark of Rotor Position Sensor Technologies for Application in Automotive Electric Drive Trains
by Christoph Datlinger and Mario Hirz
Electronics 2020, 9(7), 1063; https://doi.org/10.3390/electronics9071063 - 28 Jun 2020
Cited by 14 | Viewed by 13453
Abstract
Rotor shaft position sensors are required to ensure the efficient and reliable control of Permanent Magnet Synchronous Machines (PMSM), which are often applied as traction motors in electrified automotive powertrains. In general, various sensor principles are available, e.g., resolvers and inductive- or magnetoresistive [...] Read more.
Rotor shaft position sensors are required to ensure the efficient and reliable control of Permanent Magnet Synchronous Machines (PMSM), which are often applied as traction motors in electrified automotive powertrains. In general, various sensor principles are available, e.g., resolvers and inductive- or magnetoresistive sensors. Each technology is characterized by strengths and weaknesses in terms of measurement accuracy, space demands, disturbing factors and costs, etc. Since the most frequently applied technology, the resolver, shows some weaknesses and is relatively costly, alternative technologies have been introduced during the past years. This paper investigates state-of-the-art position sensor technologies and compares their potentials for use in PMSM in automotive powertrain systems. The corresponding evaluation criteria are defined according to the typical requirements of automotive electric powertrains, and include the provided sensor accuracy under the influence of mechanical tolerances and deviations, integration size, and different electrical- and signal processing-related parameters. The study presents a mapping of the potentials of different rotor position sensor technologies with the target to support the selection of suitable sensor technologies for specified powertrain control applications, addressing both system design and components development. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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14 pages, 5671 KiB  
Article
Design of a Low-Order FIR Filter for a High-Frequency Square-Wave Voltage Injection Method of the PMLSM Used in Maglev Train
by He Zhao, Liwei Zhang, Jie Liu, Chao Zhang, Jiao Cai and Lu Shen
Electronics 2020, 9(5), 729; https://doi.org/10.3390/electronics9050729 - 28 Apr 2020
Cited by 8 | Viewed by 2712
Abstract
In position sensorless control based on a high-frequency pulsating voltage injection method, filters are used to complete the extraction of high-frequency response signals for position observation. A finite impulse response (FIR) filter has the advantages of good stability and linear phase. However, the [...] Read more.
In position sensorless control based on a high-frequency pulsating voltage injection method, filters are used to complete the extraction of high-frequency response signals for position observation. A finite impulse response (FIR) filter has the advantages of good stability and linear phase. However, the FIR filter designed by using traditional methods has a high order which will cause a large time delay. This paper proposes a low-order FIR filter design method for a high-frequency signal injection method in the permanent magnet linear synchronous motor. Based on the frequency characteristics of the current signal, the requirement that the FIR filter needs to meet were analyzed. According to the amplitude–frequency characteristic of the FIR filter, these requirements were converted into constraint equations. By solving these equations, the coefficient of the FIR filter could be obtained. The simulation and experiment results showed the effectiveness of this low-order FIR filter. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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22 pages, 8149 KiB  
Article
Realization of the Sensorless Permanent Magnet Synchronous Motor Drive Control System with an Intelligent Controller
by Hung-Khong Hoai, Seng-Chi Chen and Hoang Than
Electronics 2020, 9(2), 365; https://doi.org/10.3390/electronics9020365 - 21 Feb 2020
Cited by 29 | Viewed by 7644
Abstract
This paper presents the sensorless control algorithm for a permanent magnet synchronous motor (PMSM) drive system with the estimator and the intelligent controller. The estimator is constructed on the novel sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate [...] Read more.
This paper presents the sensorless control algorithm for a permanent magnet synchronous motor (PMSM) drive system with the estimator and the intelligent controller. The estimator is constructed on the novel sliding mode observer (SMO) in combination with a phase-locked loop (PLL) to estimate the position and speed of the rotor. The intelligent controller is a radial basis function neural network (RBFNN)-based self-tuning PID (Proportional-Integral-Derivative) controller, applied to the velocity control loop of the PMSM drive control system to adapt strongly to dynamic characteristics during the operation with an external load. The I-f startup strategy is adopted to accelerate the motor from standstill, then switches to the sensorless mode smoothly. The control algorithm program is based on MATLAB and can be executed in simulations and experiments. The control system performance is verified on an experimental platform with various speeds and the dynamic load, in which the specified I-f startup mode and sensorless mode, inspected by tracking response and speed regulation. The simulation and experimental results demonstrate that the proposed method has worked successfully. The motor control system has smooth switching, good tracking response, and robustness against disturbance. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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16 pages, 2467 KiB  
Article
Effective Position Control for a Three-Phase Motor
by Patxi Alkorta, Oscar Barambones, José Antonio Cortajarena, Itziar Martija and Fco. Javier Maseda
Electronics 2020, 9(2), 241; https://doi.org/10.3390/electronics9020241 - 01 Feb 2020
Cited by 6 | Viewed by 4800
Abstract
This document presents an efficient proportional derivative (PD) position controller for three-phase motor drives. The regulator has been designed in frequency domain, employing the direct–quadrature (d–q) synchronous rotating reference frame and the indirect vector control. The presented position regulator [...] Read more.
This document presents an efficient proportional derivative (PD) position controller for three-phase motor drives. The regulator has been designed in frequency domain, employing the direct–quadrature (d–q) synchronous rotating reference frame and the indirect vector control. The presented position regulator is easy to tune and incorporates a feed forward (FF) term to compensate effectively the effect of the load disturbance. This position controller has been validated experimentally by using two industrial three-phase motors: an induction motor (IM) of 7.5 kW and a permanent magnet synchronous motor (PMSM) of 3.83 kW. The inner proportional integral (PI) current loops of both machines have also been designed in the frequency domain. Each machine has connected in its shaft an incremental encoder of 4096 pulses per revolution, to measure the position. Several simulations and experimental tests have been carried out with both motors, in favorable conditions and also with various types of adversities (parametric uncertainties, unknown load disturbance and measurement noise in the position and current loops), getting very good results and suggesting that this controller could be used in the research area and also in the industry. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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16 pages, 4054 KiB  
Article
A Novel Control Method of Clutch During Mode Transition of Single-Shaft Parallel Hybrid Electric Vehicles
by Jingang Ding and Xiaohong Jiao
Electronics 2020, 9(1), 54; https://doi.org/10.3390/electronics9010054 - 30 Dec 2019
Cited by 13 | Viewed by 3105
Abstract
The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor [...] Read more.
The mode transition of single-shaft parallel hybrid electric vehicles (HEVs) between engine and motor has an important impact on power and drivability. Especially, in the process of mode transition from the pure motor-drive operating mode to the only engine-drive operating mode, the motor starting engine and the clutch control problem have an important influence on driving quality, and solutions have a bit of room for improving dynamic performance. In this paper, a novel mode transition control method is proposed to guarantee a fast and smooth mode transition process in this regard. First, an adaptive sliding mode control (A-SMC) strategy is presented to obtain the desired torque trajectory of the clutch transmission. Second, a proportional-integral (PI) observer is designed to estimate the actual transmission torque of the clutch. Meanwhile, a fractional order proportional-integral-differential (FOPID) controller with the optimized control parameters by particle swarm optimization (PSO) is employed to realize the accurate position tracking of the direct current (DC) motor clutch so as to ensure clutch transmission torque tracking. Finally, the effectiveness and adaptability to system parameter perturbation of the proposed control approach are verified by comparison with the traditional control strategy in a MATLAB environment. The simulation results show that the driving quality of the closed-loop system using the proposed control approach is obviously improved due to fast and smooth mode transition process and better adaptability. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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18 pages, 3999 KiB  
Article
Unified Predictive Current Control of PMSMs with Parameter Uncertainty
by Peng Tang, Yuehong Dai and Zhaoyang Li
Electronics 2019, 8(12), 1534; https://doi.org/10.3390/electronics8121534 - 12 Dec 2019
Cited by 7 | Viewed by 2235
Abstract
Predictive current control (PCC) applied on permanent magnet synchronous motors (PMSMs) has been developed into mainly three methods: the conventional finite-control-set PCC, the double voltage vectors PCC, and deadbeat PCC. However, each approach has its particular calculation way for voltage vectors selection and [...] Read more.
Predictive current control (PCC) applied on permanent magnet synchronous motors (PMSMs) has been developed into mainly three methods: the conventional finite-control-set PCC, the double voltage vectors PCC, and deadbeat PCC. However, each approach has its particular calculation way for voltage vectors selection and respective execution duration. This paper, based on the deadbeat idea, presents a unified predictive current control scheme of PMSMs. Under this scheme, the prior three classes are able to be clearly unified into one frame with lower calculation effort. Furthermore, to cope with problem of parameter mismatch in dq-axis current predictive model, a integrated identification method is proposed. Firstly, data selectors are designed to reject abnormal data of sampling signals, and then the interval-varying multi-innovation least squares algorithm is combined with forgetting factor (V-FF-MILS) to approximate the error terms caused by electromagnetic parameters error. The estimated results are online fed to the model of PMSM to enhance its accuracy. Finally, the processor in loop (PIL) simulation results verify that the proposed integrated scheme has advantages in current control of PMSMs with large-scale parameter uncertainty. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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13 pages, 3598 KiB  
Article
Cascade Second Order Sliding Mode Control for Permanent Magnet Synchronous Motor Drive
by Adel Merabet
Electronics 2019, 8(12), 1508; https://doi.org/10.3390/electronics8121508 - 09 Dec 2019
Cited by 11 | Viewed by 2912
Abstract
This paper presents a cascade second-order sliding mode control scheme applied to a permanent magnet synchronous motor for speed tracking applications. The control system is comprised of two control loops for the speed and the armature current control, where the command of the [...] Read more.
This paper presents a cascade second-order sliding mode control scheme applied to a permanent magnet synchronous motor for speed tracking applications. The control system is comprised of two control loops for the speed and the armature current control, where the command of the speed controller (outer loop) is the reference of the q-current controller (inner loop) that forms the cascade structure. The sliding mode control algorithm is based on a single input-output state space model and a second order control structure. The proposed cascade second order sliding mode control approach is validated on an experimental permanent magnet synchronous motor drive. Experimental results are provided to validate the effectiveness of the proposed control strategy with respect to speed and current control. Moreover, the robustness of the second-order sliding mode controller is guaranteed in terms of unknown disturbances and parametric and modeling uncertainties. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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21 pages, 3571 KiB  
Article
A Method Based on Multi-Sensor Data Fusion for UAV Safety Distance Diagnosis
by Wenbin Zhang, Youhuan Ning and Chunguang Suo
Electronics 2019, 8(12), 1467; https://doi.org/10.3390/electronics8121467 - 03 Dec 2019
Cited by 32 | Viewed by 4859
Abstract
With the increasing application of unmanned aerial vehicles (UAVs) to the inspection of high-voltage overhead transmission lines, the study of the safety distance between drones and wires has received extensive attention. The determination of the safety distance between the UAV and the transmission [...] Read more.
With the increasing application of unmanned aerial vehicles (UAVs) to the inspection of high-voltage overhead transmission lines, the study of the safety distance between drones and wires has received extensive attention. The determination of the safety distance between the UAV and the transmission line is of great significance to improve the reliability of the inspection operation and ensure the safe and stable operation of the power grid and inspection equipment. Since there is no quantitative data support for the safety distance of overhead transmission lines in UAV patrol, it is impossible to provide accurate navigation information for UAV safe obstacle avoidance. This paper proposes a mathematical model based on a multi-sensor data fusion algorithm. The safety distance of the line drone is diagnosed. In these tasks, firstly, the physical model of the UAV in the complex electromagnetic field is established to determine the influence law of the UAV on the electric field distortion and analyze the maximum electric and magnetic field strength that the UAV can withstand. Then, based on the main factors affecting the UAV such as the maximum wind speed, inspection speed, positioning error, and the size of the drone, the adaptive weighted fusion algorithm is used to perform first-level data fusion on the homogeneous sensor data. Then, based on the improved evidence, the theory performs secondary fusion on the combined heterogeneous sensor data. According to the final processing result and the type of proposition set, we diagnose the current safety status of the drone to achieve an adaptive adjustment of the safety distance threshold. Lastly, actual measurement data is used to verify the mathematical model. The experimental results show that the mathematical model can accurately identify the safety status of the drone and adaptively adjust the safety distance according to the diagnosis result and surrounding environment information. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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19 pages, 4215 KiB  
Article
On-Off Control of Range Extender in Extended-Range Electric Vehicle using Bird Swarm Intelligence
by Dongmei Wu and Liang Feng
Electronics 2019, 8(11), 1223; https://doi.org/10.3390/electronics8111223 - 26 Oct 2019
Cited by 6 | Viewed by 2319
Abstract
The bird swarm algorithm (BSA) is a bio-inspired evolution approach to solving optimization problems. It is derived from the foraging, defense, and flying behavior of bird swarm. This paper proposed a novel version of BSA, named as BSAII. In this version, the spatial [...] Read more.
The bird swarm algorithm (BSA) is a bio-inspired evolution approach to solving optimization problems. It is derived from the foraging, defense, and flying behavior of bird swarm. This paper proposed a novel version of BSA, named as BSAII. In this version, the spatial distance from the center of the bird swarm instead of fitness function value is used to stand for their intimacy of relationship. We examined the performance of two different representations of defense behavior for BSA algorithms, and compared their experimental results with those of other bio-inspired algorithms. It is evident from the statistical and graphical results highlighted that the BSAII outperforms other algorithms on most of instances, in terms of convergence rate and accuracy of optimal solution. Besides the BSAII was applied to the energy management of extended-range electric vehicles (E-REV). The problem is modified as a constrained global optimal control problem, so as to reduce engine burden and exhaust emissions. According to the experimental results of two cases for the new European driving cycle (NEDC), it is found that turning off the engine ahead of time can effectively reduce its uptime on the premise of completing target distance. It also indicates that the BSAII is suitable for solving such constrained optimization problem. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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19 pages, 1911 KiB  
Article
Robust Current Predictive Control-Based Equivalent Input Disturbance Approach for PMSM Drive
by Xudong Liu and Qi Zhang
Electronics 2019, 8(9), 1034; https://doi.org/10.3390/electronics8091034 - 15 Sep 2019
Cited by 16 | Viewed by 3577
Abstract
The implementation and experimental validation of current control strategy based on predictive control and equivalent input disturbance approach is discussed for permanent magnet synchronous motor (PMSM) control system in the paper. First, to realize the current decoupling control, the deadbeat predictive current control [...] Read more.
The implementation and experimental validation of current control strategy based on predictive control and equivalent input disturbance approach is discussed for permanent magnet synchronous motor (PMSM) control system in the paper. First, to realize the current decoupling control, the deadbeat predictive current control technique is adopted in the current loop of PMSM. Indeed, it is well known that the traditional deadbeat current control cannot completely reject the disturbance and realize the zero error current tracking control. Then, according to the model uncertainties and the parameter variations in the motor, an equivalent input disturbance approach is introduced to estimate the lump disturbance in the system, which will be used in the feed-forward compensation. Thus, a compound current controller is designed, and the proposed algorithm reduces the tracking error caused by the disturbance; the robustness of the drive system is improved effectively. Finally, simulation and experiment are accomplished on the control prototype, and the results show the effectiveness of the proposed current control algorithm. Full article
(This article belongs to the Special Issue Advanced Control Systems for Electric Drives)
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