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Необхідний рівень безпеки машин і механізмів досягається за рахунок використання відповідних систем управління безпекою промислового обладнання, в тому числі програмованих електронних. Такі системи зазвичай включають в себе різноманітні охоронні пристрої для управління налаштуваннями промислового обладнання. Оскільки електронні системи управління в даний час вважаються найбільш перспективними системами управління в цій області, вивчення параметрів безпеки їх прикладної підтримки визначає актуальність даного дослідження. У цьому дослідженні проаналізовано основні вимоги стандартів IEC 61508 та IEC 62061 на відповідність сучасним вимогам безпеки вбудованого та прикладного програмного забезпечення для електронних систем управління машинами та механізмами. Дане дослідження пропонує алгоритм покрокового впровадження програмного забезпечення для електронних систем управління машинами відповідно до базових стандартів безпеки як для вбудованого, так і прикладного програмного забезпечення. Тестування визначено як основний метод перевірки прикладного програмного забезпечення. За результатами аналізу було встановлено, що специфікація вимог безпеки, як вбудованого, так і прикладного програмного забезпечення, повинна висвітлювати необхідні характеристики кожної підсистеми, надаючи інформацію, що дозволяє вибрати обладнання, що відповідає існуючим вимогам безпеки. Наводяться відповідні рекомендації щодо специфіки практичного застосування цих стандартів. The required level of safety of machines and mechanisms is achieved through the use of appropriate safety management systems for industrial equipment, including programmable electronic ones. Such systems usually include a variety of security devices for managing industrial equipment settings. Since electronic control systems are currently considered the most promising control systems in this area, the study of the security parameters of their application support determines the relevance of this study. This study analyses the main requirements of IEC 61508 and IEC 62061 standards for compliance with modern safety requirements of embedded and applied software for electronic control systems of machines and mechanisms. This study proposes an algorithm for step-by-step implementation of software for electronic machine control systems in accordance with basic security standards for both built-in and application software. Testing has been determined as the main method of verification of application software. Based on the results of the analysis, it was found that the specification of security requirements, both built-in and application software, should highlight the necessary characteristics of each subsystem, providing information that allows choosing the equipment that meets existing security requirements. Relevant recommendations are given on the specifics of practical application of these standards.

Excavators are essential equipment in construction sites, and machine guidance (MG) and machine control (MC) systems are employed in excavators to improve their earthwork performance. MG and MC systems provide the equipment operator with critical information, such as the excavation depth and slope angle required for earthwork operations, thus minimizing the assistance of a surveyor. In this study, we analyzed the performance improvement offered by MG and MC systems in earthworks compared to conventional excavation methods. We conducted performance analyses from two perspectives: productivity and accuracy. Productivity represents the quantity of earthwork in terms of time units, and accuracy reflects any deviations from the designed earthwork drawing. The analyses were conducted at a domestic trench experimental site, and the results show a highly reliable 81.12% improvement in productivity and an accuracy of ±2.1 m2 compared to traditional methods.

For saliency-based position sensorless drives, the switching frequency pulsewidth modulation (PWM) voltage injection can achieve noise-free position estimation which is suited for high-performance motion systems. However, considering the switching frequency injection, multiple phase currents should be sampled per PWM cycle instead of single average current. It leads to the implementation issue on the space-vector PWM (SVPWM) inverter using shunt resistor current sensing for machine control. In this article, a modified PWM injection instead of SVPWM injection is proposed for the saliency-based drive using shunt current sensing. It is concluded that at least two transient currents can be sampled per PWM cycle based on the proposed PWM control. More importantly, the field-oriented control is maintained when the saliency-based drive is applied. A 2 kW permanent magnet (PM) machine is used for the experimental verification. This article includes the position estimation comparison using either the proposed PWM injection with shunt resistors or standard SVPWM with Hall-effect sensors.

This paper provides a fundamental research review of Reconfigurable Manufacturing Systems (RMS), which uniquely explores the state-of-the-art in distributed and decentralized machine control and machine intelligence. The aim of this review is to draw objective answers to two proposed research questions, relating to: (1) reconfigurable design and industry adoption; and (2) enabling present and future state technology. Key areas reviewed include: (a) RMS – fundamentals, design rational, economic benefits, needs and challenges; (b) Machine Control – modern operational technology, vertical and horizontal system integration, advanced distributed and decentralized control; (c) Machine Intelligence – distributed and decentralized paradigms, technology landscape, smart machine modelling, simulation, and smart reconfigurable synergy. Uniquely, this paper establishes a vision for next-generation Industry 4.0 manufacturing machines, which will exhibit extraordinary Smart and Reconfigurable (SR*) capabilities.

This work deals with the development of a real-time wind turbine emulator (WTE) for laboratory purpose using a robust sliding mode controller (SMC). The application of power electronic converters with various control strategies in machine control facilitate the imitation of a practical wind turbine characteristics using a separately excited DC motor. The SMC theory is used here to develop a control law that governs the system to track the reference current set by the mathematical model of the wind turbine to get the desired output. The static, dynamic characteristics and also the transient responses of the WTE are satisfactorily reproduced by the proposed SMC method. To validate the performance of WTE prototype, it is tested under various operating conditions. A performance comparison of the proposed SMC with the existing proportional and integral (PI) controller in terms of tracking speed, peak overshoot and settling time are discussed in detail. The experimental result analysis confirms that the proposed control scheme improves the imitation of the real-time wind turbine characteristics and performs efficiently under both steady-state and transient conditions.

The new cellular network standard 5G is characterized by greater bandwidth, lower latencies, higher reliabilities, and a higher number of recipients per cell compared to industrial 4G or wireless networks. This makes 5G a promising technology in latency-critical applications in manufacturing, such as machine tool control systems. Today, machine tools are mostly controlled with on-site industrial PCs, which require space, are often heterogeneous, and have limited processing power. 5G potentially enables to migrate the machine control system to external computing resources. This paper aims at elaborating resulting potentials by conceptualizing and outlining an architecture that integrates the requirements and capabilities of 5G and a machine tool control system.

In this paper, a five-phase permanent magnet synchronous motor (five phase PMSM) decoupled model is proposed to avoid the inaccuracy and computational complexity of conventional five phase PMSM model, which always ignores the mutual inductance between the fundamental and harmonic flux linkage. Unlike traditional inductances based five phase PMSM model, the proposed five phase PMSM decoupled model is built based on flux linkages. Moreover, to improve the accuracy of the proposed five phase PMSM decoupled model for model predictive control, a duel frame-frequency adaptive flux observer (DF-FAFO) is proposed, which can estimate both fundamental flux linkage and 3rd harmonic flux linkage online. The DF-FAFO can estimate the flux linkages accurately and minimize the unwanted harmonic ripple even if the torque is changed. The effectiveness of the proposed decoupled model and the DF-FAFO is demonstrated by simulations.

Doubly-fed induction generators (DFIGs) have drawn prominent interest in the field of wind power generation, but they are vulnerable to grid faults. Grid codes mandate DFIGs to employ a sort of fault ride-through (FRT) technique during faults. Fault current limiters (FCLs) always help to augment the FRT capability of DFIGs and a non-linear controller boosts their performances. In this study, a non-linear auto-regressive moving average-L2 (NARMA-L2) controller-based bridge-type flux coupling non-superconducting FCL (BFC-NSFCL) is proposed to enhance the FRT capability of the wind farm. The authors analysed the performance of the proposed NARMA-L2-based BFC-NSFCL (NL2-BFC-NSFCL) against that of the conventionally used series dynamic braking resistor (SDBR), bridge-type FCL (BFCL), and proportional–integral (PI) controller-based BFC-NSFCL (PI-BFC-NSFCL). They tested the performance of the NL2-BFC-NSFCL through multiple temporary and permanent fault scenarios and carried out the mathematical and graphical analysis in MATLAB/Simulink platform. They found that the proposed NL2-BFC-NSFCL's performance surpasses the performances of the SDBR, the BFCL, and the PI-BFC-NSFCL. Moreover, the NL2-BFC-NSFCL has faster system recovery capability after the occurrence of any fault than other competitors.

In this study, an advanced predictive control system is proposed which consists of two cascade predictive controllers; the first one minimises the power losses while the second one minimises the torque ripple. In the first controller, motor losses are formulated as a function of stator-flux linkage components. Then, the optimal stator-flux linkage vector which causes the minimum losses is found by adopting fast-iterative shrinkage thresholding algorithm (FISTA). The second controller is a predictive direct torque controller adopted to control the stator-flux linkage and torque directly. In this controller, torque ripple is formulated as a function of the stator-voltage vector. Then, the optimal voltage vector which causes the minimum torque ripple is found by adopting FISTA. In the second controller, deadbeat control of the stator-flux linkage is considered as a constraint in minimisation of torque ripple. To assess the effectiveness of the proposed control system, performance of the motor is assessed through various experimental tests, where the results confirm that the proposed control system minimises the power losses and torque ripple, simultaneously. The comparative assessment with the recent predictive controllers indicates that the proposed control system has higher efficiency as well as lower torque ripples in all operating points.

Power converter faults represent about 12% of electrical system faults. More than 31% of these converter faults are caused by the transistors in the converters. These transistor failures are classified into open-gate and short-gate faults. A fault diagnostic and tolerant control system is proposed in this study for an open-gate fault of a three-phase voltage-source inverter (VSI). The system under study is an induction motor fed by a VSI. The diagnostic technique uses a detection method of positive and negative sequence components, which requires only the measurement of motor currents. The diagnostic signals are derived from the negative sequence components of the motor currents. These signals are then compared using logic functions to trigger the tolerant control. In the case of an open-gate fault, the tolerant system converts the inverter topology from six switches to four switches where the faulty inverter leg is disconnected. The proposed control method was evaluated under steady-state and transient conditions through simulation and experiments. The results confirm an effective and reliable performance of the motor under an open-gate fault.

Position tracking of a user or an object has caught many researchers and entrepreneurs’ attention. It has a significant market opportunity as well as applications in daily life such as Earth sciences, intelligent transportation systems, machine control, mapping, surveying, surveillance, tracking, and vehicle testing. The accuracy of different positioning methods depends upon the accuracy of underlying technology and environmental conditions. In this paper, a hybrid adaptive method is developed to enhance the accuracy of positioning. Based on the accuracy and the environments, a coefficient (weight) vector is assigned to the coordinates obtained from INS, GPS, Cellular Network, and Wi-Fi methods. Subsequently, the weighted average method is used to integrate the coordinates to compute the location. The proposed method is tested in an experimental study with different distance settings. The accuracy and robustness of suggested method are validated with GPS and INS hybrids.

This study presents the optimisation of fractional-order proportional–integral (FOPI) controllers for a bidirectional quasi-Z-source inverter (QZSI) in an electric vehicle (EV) off-road application. An ant colony optimisation Nelder–Mead (ACO-NM) algorithm is used for the optimisation of the controller parameters. This optimisation method is applied to enhance the performance of FOPI control for bidirectional QZSI. Ziegler–Nichols (ZN) with relay and the pole placement tuning method are also used for the FOPI controller design for comparison purposes. The modelling and the control design of bidirectional QZSI for an electric traction system are presented and discussed. Simulations are performed to verify the efficacy of the proposed controller structure with the bidirectional QZSI for two standardised driving cycles. The result shows that the FOPI controller designed with the ACO-NM algorithm provides more suitable ageing performance index values for the battery. The ACO-NM algorithm permits to reduce the root-mean-square value and the standard deviation by 2 and 5% of the battery current compared to the ZN tuning method and direct battery supply topology, respectively. The bidirectional QZSI with this type of controller can globally enhance the performance of EVs by optimising the electric power consumption and extending its driving range.

In this study, a simple carrier-based pulse-width modulation (CBPWM) method is proposed for a three-phase three-level neutral-point-clamped converter with neutral-point (NP) balancing, which can be applied to three-phase three-wire (TPTW) and three-phase four-wire (TPFW) converter systems simultaneously. First, the effect of each switching state for the NP potential in TPTW and TPFW systems is analysed in detail, and a newly NP control strategy by reconstructing the switching state and adjusting the corresponding duration time is deduced for all operation conditions, it only needs to add the offset voltage to the modulation reference voltage to guarantee the NP balance and is easy to implement. Then, under all operating conditions, the mathematical model of NP current is derived and analysed to evaluate the low-frequency voltage oscillation in the NP. Finally, the effectiveness and feasibility of the proposed CBPWM strategy are verified by the experimental results based on a 12 kVA laboratory prototype.

In this paper, an improved modulated model-predictive control (MMPC) scheme is proposed for the current control of permanent magnet synchronous motors (PMSMs). Different from the existing MMPC based motor current control schemes which simply feed the resultant voltage vectors calculated by the finite-control-set model predictive control (FCS-MPC) to the SVPWM module and could not adjust the current control bandwidth, the principle of the proposed MMPC current control scheme is to control the current vector along a predefined trajectory and the resultant current vector is expected to equal the reference current vector at the end of the predictive horizon. Therefore, the control bandwidth of the proposed MMPC can be easily adjusted via the predictive horizon, and the transient performance of the current control can be improved without current overshoot. Moreover, different from existing MMPCs, the proposed control scheme does not need to predict all the resultant currents generated by the basic voltage vector combinations of the six voltage sectors, but only needs to predict the resultant currents generated by the basic voltage vector combinations of three voltage sectors. Therefore, the computational burned is significantly reduced.

This study presents an extremum seeking-proportional–integral and derivative (ES-PID) controller design for brushless direct current motors and its implementation in electric vehicles. The ES-PID controller aims to simultaneously maintain a speed set-point and reduce torque ripples in the presence of load-torque disturbances. The proposed ES-PID combines the simplicity of a PID controller with an extremum seeking approach, a model-free optimisation approach, thereby resulting in an optimal controller that can be realised on simple hardware (with limited computing power and memory). In addition, a theoretical analysis of the proposed ES-PID control scheme in terms of stability and convergence is also presented. Performance evaluation of the proposed ES-PID controller using both simulations and hardware experiments are presented. The results clearly illustrate the ability of the controller to track speed set-point and reduce torque ripples in the presence of load-torque variations.

In this study, an extended Kalman filter (EKF)-based estimation algorithm is presented to improve the speed-sensored control performance of induction motors (IMs). The proposed EKF-based estimation algorithm is to simultaneously estimate the stator stationary axis components of stator currents and rotor fluxes, rotor angular speed, load torque including viscous friction term, rotor resistance and magnetising inductance in a single EKF algorithm without requiring any switching operation or a hybrid structure. In order to improve the speed-sensored control performance, the measurement/output matrix of IM model is extended by the measured rotor speed in addition to stationary axis components of the measured stator currents. Therefore, the proposed EKF algorithm uses the speed and stator current errors between the measured and priori estimation values in order to calculate the posterior estimation ones. For performance evaluation, the eighth order (proposed) EKF algorithm is tested by simulations and real-time experiments under challenging scenarios and compared with the developed sixth order EKF in real time. The obtained real-time results also show that the eighth order (proposed) EKF algorithm provides additional and improved estimations with the increased but feasible execution time in terms of the sixth order EKF designed in this paper.

Although the control strategy regarding quasi-Z-source inverter (qZSI) has been widely studied, the dynamic response and steady-state accuracy of the system with a non-linear section should be further improved. Based on this, this study proposes an energy shaping control (ESC) method based on the port-controlled Hamiltonian (PCH) model for qZSIs. Firstly, based on the average state-space model, the PCH model of the qZSI system is first built, which is an indispensable preprocessing for the following controller design. Based on the proposed model, the ESC method combining the interconnect matrix with damping configuration is proposed to improve the dynamic response and steady-state accuracy, which is verified through comparing with several existing linear and non-linear control strategies in detail. Finally, simulation and experimental results verify the effectiveness of the proposed method.

The droop control strategies can realise an autonomous power allocation among virtual synchronous generators (VSGs) that can provide the recompenses of reduced system complexity and enhanced reliability. The stability of a low-inertia microgrid can be improved by implementing a VSG, designed for the coordination between multiple variable electric vehicle (EV) based charging loads. This study mainly investigates two control schemes. Firstly, the instantaneous contribution from EV charging control for any disturbance that can provide adequate damping and inertia to a low-inertia microgrid without degradation of the battery. Secondly, the adjustment of Q-V droop control is suggested by correcting the excitation voltage of a VSG. This method can reduce the influence of line impedances and power ratings on reactive power sharing in a multi-VSGs system. Additionally, four different active and reactive power control modes of VSG are discussed to emphasise EV charging and discharging control through the VSG controller. These modes are explained through circuit and vector diagrams in direct and quadratic coordinates. The efficacy of the proposed strategies and their influence on power sharing is theoretically demonstrated and analysed. Finally, the theoretical results are validated through extensive simulation and experimental verification.

This article presents the theoretical aspects of developing a control system for the processing of frozen raw meat by cutters in automatic mode. The method for analytical calculation of the productivity rate of meat cutting by a cutter with a screw tooth provides an accuracy for which relative error does not exceed 6%. The authors show automatic process control in minced meat production using a control system computer (CSC), with the aim of building an automatic control system (ACS) for chopping raw materials frozen in the form of blocks. The task of ACS synthesis was solved: the system structure and its elements were chosen, the topology of their cause-and-effect relationships and an algorithm of control devices were developed, and their parameters were determined. The ACS’s control loop scheme for raw material cutting speed was realized, where an assembly of devices was chosen as the object of management (OM): the squirrel cage induction motor (SCIM) of the cutting mechanism drive; the frequency converter (FC) of the supply voltage, which changes the rotation speed of the SCIM (the rotation speed of the milling cutter); and the milling cutter of the chopper. The shaping filter method was used, to predict the size of the meat chips produced, to modulate the perturbation acting on the system from the load side. Based on the single-stage chopping of raw meat, an automatic line is created for producing meat products, with a minced meat quality management system based on artificial intelligence on the principle of ‘unmanned technology’.

To realise the resonant characteristics of motor drive system, a wavelet multiresolution filter (WMF)-based scheme is proposed in this study to perform the detection of the mechanical resonant frequencies for interior permanent magnet synchronous motor servo drives. In a conventional motor drive system, the compliance in the coupling between motor and load may cause resonance. Moreover, the parasitic torque ripples resulting from the harmonics of a pulse-width modulation inverter may excite mechanical vibrations. In the proposed scheme, the localisation analysis of signal can be completed with the WMF at any time and frequency domains for the extraction of resonant frequencies. Then, a band-pass filter is applied to perform the frequency sweeping for the detection of resonant frequencies. In the final stage, the signal smoothing is implemented with the calculation of absolute and average values. To verify the effectiveness of the proposed resonant-frequency detection scheme using the WMF, some experimental results at different rotor speed and load conditions are provided. In addition, a two-channel dynamic signal analyser is also adopted in the experimentation for the comparison of resonant-frequency detection.

A voltage-controlled canonical switching cell-derived DC–DC converter with improved power quality feeding a variable speed permanent magnet brushless direct current (PMBLDC) motor-drive system for home appliances, is presented in this study. The converter is operating in the continuous conduction mode (CCM). This converter has less stress on the converter devices due to CCM of operation. A single converter is used for both the power factor correction (PFC) and the speed control of the drive, thus reducing the number of elements in the system. The speed control, along with PFC in this system is achieved via a PI controller having speed reference as an input. This system is capable of providing the low speed to rated speed operation while maintaining a unity power factor. The Hall-effect sensor-based electronic commutation of a PMBLDC motor-drive is implemented at the fundamental frequency. This significantly improves efficiency by reducing the switching losses of the voltage source inverter. A prototype of it is developed in the laboratory for implementation of the scheme. Simulated and real-time experimental results of the scheme are presented here for performance validation at various dynamic and steady-state operating conditions.

This study proposes a new approach for the detection of broken rotor bar (BRB) fault in three phase induction motor drive using Hilbert transform (HT) and artificial neural networks (ANNs), where the machine is controlled by direct torque control (DTC). HT is preferred to develop the stator current envelope. The sideband frequency and its amplitude of the samples are the input for the ANN. By using fast Fourier transform, the amplitude and frequency components are extracted and the severity of fault is determined by comparing the magnitude of an average of sideband frequency with the fundamental frequency. High accuracy identification of fault is found by ANN, where the results are trained and tested to a minimum mean square error that will detect the number of BRB in the induction motor. DTC is adopted for a suitable control technique in the industrial drives system to maintain good performance in torque control. The performance of the proposed method is verified by using MATLAB/SIMULINK and experimental tests.

An improved and more robust flux vector orientated control scheme for an emerging doubly-fed reluctance generator without a shaft angular position or velocity sensor has been proposed, computer-simulated, and experimentally verified. Whilst retaining the cost and other advantages of using a fractional power electronics converter rating, this promising medium-speed brushless machine technology has been viewed by research and industrial communities as an appealing economical solution for the compromised reliability and high maintenance requirements associated with the presence of slip rings, brushes, and the failures prone three-stage gearbox of conventional wound rotor doubly-fed induction generators, traditionally deployed for commercial wind turbines. The comprehensive comparative simulation and test results obtained have been shown to agree very well undoubtedly demonstrating the good overall performance of the sensorless controller. A precise speed reference tracking with smooth, intrinsically decoupled real and reactive power responses of the grid-connected winding has been achieved for the typical variable loading profiles and narrow speed ranges (e.g. around 2 : 1 or so) of a laboratory emulated wind turbine.

This study proposes a new method leading to a reduction in the current and torque ripple of an induction motor (IM) drive controlled by predictive torque control (PTC). The method lies within the optimisation of a DC-link voltage magnitude by the PTC cost function. Using a three-phase silicon-controlled rectifier, the DC-link voltage can be adjusted in such way that the current and torque ripple, caused mainly by treating the inverter as a source of only eight voltage vectors, is significantly reduced. The DC-link optimisation algorithm is integrated into the PTC that is used for the torque and flux control. In another prediction stage, the influence of the DC-link voltage on the torque and flux ripple is directly evaluated and then optimised by a second cost function. The theoretical analysis of the DC-link voltage influence on the drive behaviour is supported by simulation and experimental results conducted on a 5.5 kW IM drive, which confirm the benefits of the PTC with the DC-link voltage optimisation, especially if the drive operates in a region below the nominal speed.

Phase characteristics of the generator-exciter-power (GEP) system with a conventional automatic voltage regulator (AVR) varies significantly with operating condition (OCs). In this study, a novel modification in the conventional excitation controllers (first-order AVR, ST1A and AC1A) is presented. The authors found that the GEP phase responses are robust over a wide range of OCs yielding a robust phase compensation design for power system stabiliser. Additionally, they observed improved small-signal stability without affecting the transient stability. Simulation results are presented on SMIB, IEEE 39- and 68-bus power systems, wherein a detail sub-transient model of synchronous generator is considered.

This study confers a novel approach towards fuzzy-PI (proportional–integral) controlled pulse width modulation (PWM) controlled permanent magnet synchronous motor (PMSM) drive operated through a conventional voltage source inverter (VSI) supplemented with buck-converter fed current source inverter (CSI). It is observed that in a PWM controlled VSI, output voltage and current obtained contains certain harmonic distortion. A buck-converter fed CSI is capable of minimising the voltage and current ripples prominently even with the application of PWM. Thereby, in this study, an economic, as well as robust design procedure for the buck converter, fed CSI is proposed. Moreover, a particle swarm optimisation (PSO) mechanism is introduced to optimise the performance of the proposed fuzzy logic controller. Additionally, an over-current protection scheme of the PMSM motor is proposed. The performance of a PMSM drive is analysed in MATLAB/SIMULINK platform. Furthermore, the proposed concept is tested and verified in a real-time test-bench developed in the laboratory. Finally, from the performed test conditions, it can be confirmed that the proposed current control strategy of the drive system shows excellent performance in various operating conditions and can be employed in light-weight electric vehicles.

Distributed energy storage systems (DESSs) play an important role in maintaining voltage stability in DC microgrids. In order to improve the inertia of DC microgrid and balance the charge/discharge power and the state-of-charge (SOC) of each energy storage unit (ESU), an SOC-based virtual DC machine (VDCM) control strategy for DESSs in DC microgrid is proposed in this paper. By adding SOC to the armature resistance, the improved virtual machine algorithm can dynamically balance power and SOC simultaneously. In this article, the transient stability of DC bus voltage is enhanced using the output inertia of VDCM, and the SOC differences between ESUs are rapidly reduced by introducing the average SOC of ESUs. Small-signal models of both each ESU-interfacing converter and DESS-inclusive DC microgrid with proposed control method are established. The impact of VDCM parameters on voltage stability is analyzed. Finally, a test DC microgrid is built to verify feasibility and effectiveness of the VDCM control strategy.

In this study, a modified complementary sliding mode control (MCSMC) method based on a disturbance force observer with mass identification (DFOB-MI) applicable to the permanent magnet linear synchronous motor is proposed to achieve high-performance servo control fields. MCSMC is an improvement on the complementary sliding mode control (CSMC) method, which incorporates an approach angle into the saturation function. MCSMC allows for asymptotic convergence of the position tracking errors and guarantees the global robustness of the system. In addition, compared to hybrid control strategies combining neural networks with CSMC, the MCSMC method has a simpler structure and faster response. However, in practical applications, the mass variation of the mover has a significant impact on system performance. To achieve better dynamic and static characteristics, a disturbance force observer capable of identifying the mass variation based on model reference adaptive identification theory is proposed. DFOB-MI can identify the mass of the mover and provide information on the disturbance caused by the change of the load. Thus, the compensation current is calculated to reduce the disturbance and realise compensation. The more accurate tracking performance and stronger robustness of the proposed control scheme compared to conventional approaches have been confirmed through comparative experimental studies.

This study presents the design of a 2-pole high-speed BLDC motor for kitchen blenders and its control method with the aim to reduce the speed ripple that decreases the grinding performance in the high-speed region. In blender machines, the high pulsating load caused by the blending materials such as ice cubes acting on the grinding blade, create significant speed ripple in the constant power region. Because current and torque are limited to protect the drive, the actual motor torque cannot overcome the pulsated load if the speed reference is maintained. Therefore, the speed fluctuates, and the grinding performance is lowered. In the proposed variable speed reference control scheme, the speed command is continuously modified to overcome the maximum pulsating torque requirement which results in lower speed ripple. To achieve this, if the load torque suddenly increases, the current value is then set based on the maximum load and speed reference value is temporarily lowered. If then the load torque becomes lower than the actual torque, the previously set speed reference value is reused. The design result and grinding performance of the proposed control method are verified by simulations and experiments. Hard white beans are used for actual performance testing.

This study investigates the stability of multiple three-phase converters connected to weak grids. It has been derived a flexible modelling regarding the number of converter and type of collector system. The both eigenvalues and impedance based methods are applied to the stability analysis. The eigenvalues method is used to give guidelines on the choice of the phase-looked loop (PLL) gains. To improve the stability margins, the increase in the PLL damping ratio is proposed. Moreover, it is used to investigate the PLL interaction with converter current and DC bus voltage controllers. The impedance based method extends the stability analysis to multiple three-phase converters. In addition, it has been used to show the effects of converter current and DC bus voltage controllers parameters on the stability margins. Finally, in order to validate the theoretical analysis, time-domain results with hardware-in-the-loop are given, showing a strong correlation with the theoretical analysis in the frequency domain.

Generalised predictive control (GPC) is known for its good dynamic performance and long prediction horizon, but the performance can be severely deteriorated when measurement noises exist due to the wide control bandwidth of GPC. Meanwhile, the unmodelled periodic disturbances can cause ripples to the output variables. In this study, a practical permanent magnet synchronous motor (PMSM) drive system with speed measurement noise and periodic disturbances is considered, for which a novel multivariable GPC method is proposed to achieve both good dynamic performance and speed ripple mitigation. The proposed method has a simple structure, since the traditional cascaded speed and current control loops are replaced by a non-cascaded one. To reject the measurement noise without jeopardising the system stability, an internal low-pass filter is embedded in the GPC. Meanwhile, external resonant loops are added to the GPC to mitigate the low-order speed ripples caused by the periodic disturbances. Furthermore, a deadbeat-based current constraint method is proposed to avoid overcurrent during transient processes. Theoretical stability analysis of the proposed method is presented. Experimental results show that the proposed method has good steady-state and dynamic performances, including measurement noise rejection and speed ripple mitigation.

In this study, a novel sensorless control of the surface-mounted permanent-magnet synchronous motor (PMSM) is proposed. Firstly, by taking the derivative of the back electromotive force (EMF), the high-order voltage equations of PMSM, in which the dominant time-changing parts of back-EMF are separated and modelled, are deduced. Then a generalised extended state observer, which possesses the preferable tracking ability for time-varying states, is designed to estimate the back-EMF. Also, since the difference between the measured stator resistance and its real value, which changes with temperature, will lead to position errors, a resistance estimation scheme is proposed. Compared with the conventional sensorless method of PMSM, the proposed method can provide a more accurate and smooth position and speed estimation under resistance uncertainty without extra filter and compensator. Furthermore, since the effects of speed and current change rate are taken into consideration, the application of the proposed scheme is broadened. The effectiveness of the proposed method is verified by the experiments in different cases.

The paper reports the results of a research on validation and optimization of automatic and semi-automatic guidance systems for agricultural machinery based on Real-Time positioning services provided by GNSS Networks (NRTK). The research is based on experimental campaigns performed on test areas, located in Umbria (central Italy) on the land of six farming companies. The tests have interested many processes of the agricultural work carried out in different seasons and environmental conditions, by means of agricultural machinery of various size, power and characteristics. For the performance evaluation of different guidance systems and positioning methods, reference solutions obtained in post-processing with geodetic GNSS receivers have been utilized. To reach generalized conclusions, appropriate parameters have been defined and evaluated in order to compare the quality of the results of tests performed with different equipment and conditions, and to quantify the economic benefits achieved through the GNSS guidance systems. Further tests have been performed to evaluate the ability of machine control systems to acquire a series of useful agronomic and geometric data during the work to be included in a farm-level GIS, including the three-dimensional geometry of the crops, the creation of reports about processes and treatments and the optimization of the machine paths and related agricultural activities.

The performance of the conventional model predictive current control (MPCC) method is not without steady-state ripples in electrical drives. Although some recently proposed MPCC methods have succeeded to mitigate this drawback, they have led to reductions in the dynamic speed response inherent to the conventional MPCC method. An improved MPCC is proposed here which would enhance the conventional MPCC method without any side effect on its merits. In this proposed method, three control strategies are presented for transient- and steady-state operations. The first two strategies are applied to improve motor performance in the steady state, through calculating the voltage vector (VV) and its optimal duration to minimise ripples in both d–q-axis currents. The third strategy is applied in the transient-state operation, where, instead of two VVs, an allowable non-zero VV is applied throughout the control cycle to prevent dynamic response reduction caused by zero VV. The experimental results confirm the effectiveness of this proposed method in reducing torque ripples, flux ripples, and the stator current total harmonic distortion in relation to those obtained by the previous MPCC methods.

The fast and stable inner current loop in the permanent magnet synchronous motor control system is the key factor that ensures the torque control performance of the motor. The deadbeat predictive current control has good dynamic response performance, but it depends heavily on the precise mathematical model of the controlled object. The parameter mismatch will degrade the control performance. A deadbeat predictive current control method based on online parameter identification is proposed in this study. This method does not need to inject additional d-axis current to identify the parameters during the operation of the motor; it only needs to make full use of the inherent phenomenon that the q-axis current changes when the load of the motor changes during operation, and perform parameter identification. Aiming at the problem that the effect of parameter identification is easily affected by motor speed, a new variable step-size neural network algorithm is designed in this study. The speed factor is introduced into step function to ensure the performance of the identification algorithm at a different speed. Finally, based on the new online parameter identification algorithm, the deadbeat predictive current control method is used to verify the experiment.

Following the climatic changes, there is a universal commitment to reduce greenhouse gas emissions, especially those due to mobility. A particular interest is addressed to hybrid propulsion systems, which are currently considered as viable candidates for a sustainable mobility. Within this commitment, the study proposes an approach to improve the cost-effectiveness, compactness and reliability of the electric drive unit of hybrid propulsion systems. This is achieved thanks to different associations of brushless DC motors (BDCMs) and reduced topologies of DC/AC converters such as the four switch inverter and three switch inverter. A special attention is focused upon the analysis of the sequences and commutations characterising the six-phase and three-phase BDCM drive operation. Implementation schemes of dedicated control strategies are given. Moreover, a comparison of selected features related to the ratings of the investigated BDCM drives is carried out and commented. Experimental results are provided to validate the performances of a reduced structure inverter fed three-phase BDCM under the dedicated control strategy.

In electric vehicles (EVs) and hybrid EVs, energy efficiency is essential where the energy storage is limited. Adding to its high stability and low cost, the induction motor efficiency improves with loss minimisation. Also, it can consume more power than the actual need to perform its working when it is operating in less than full load condition. This study proposes a control strategy based on the fuzzy logic control (FLC) for EV applications. FLC controller can improve the starting current amplitude and saves more power. Through the MATLAB/SIMULINK software package, the performance of this control was verified through simulation. As compared with the conventional proportional integral derivative controller, the simulation schemes show good, high-performance results in time-domain response and rapid rejection of system-affected disturbance. Therefore, the core losses of the induction motor are greatly reduced, and in this way improves the efficiency of the driving system. Finally, the suggested control system is validated by the experimental results obtained in the authors’ laboratory, which are in good agreement with the simulation results.

This study presents a method of chaotification of universal motor drive by selecting appropriate topology of the power circuit and suitably choosing values of circuit components for mixing application. The purpose of chaotification is to improve homogeneity in the mixture and to reduce consumption of time, cost and energy. In particular, the dynamic behaviour of a pulse-width modulation controlled chopper fed universal motor drive with diode bridge rectifier at the source side has been explored for the occurrence of chaos in the mixer motor. Performance of the drive has been investigated with two different topologies of the filter circuit. The first topology uses a capacitor filter after diode rectifier and the other includes an LC filter at the motor terminals along with source-side capacitor filter. A systematic methodology for selecting appropriate values of the filter circuit components has been proposed for imparting chaotic motion to the motor load system. A comparative study showing a range of load torque and speed for which sub-harmonic or chaotic speed oscillation occurs in the motor for both the topologies of filter circuit has also been presented. Computer simulations and results of laboratory experiment performed on a 0.5 hp, 1800-rpm universal motor validate the proposed design method of the motor drive for the better mixing process.

In this study, a novel speed control algorithm that combines the model-free adaptive discrete-time integral terminal sliding mode control (MFA-DITSMC) method and non-linear disturbance observer (NDO) is presented for a permanent magnet synchronous motor (PMSM) drive system. To improve the robustness and assure excellent response speed, the MFA-DITSMC method is proposed and the designed process of a speed controller is divided into two steps. Firstly, the motion equation of the PMSM is converted into a discrete-time form and then the compact-format dynamic linearisation model is obtained. Secondly, the MFA speed controller is constructed by using the DITSMC method. Moreover, aiming at the deterioration of control precision caused by unknown lumped disturbances that exist in a control system, the NDO is devised to estimate and further reject disturbance. Finally, the effectiveness of the proposed algorithm is illustrated by simulation and experiments, and the results demonstrate that the designed speed controller has satisfactory dynamic response performance and strong robustness.

A hybrid direct torque control (DTC) method is proposed in this study for a permanent magnet synchronous motor (PMSM) drive based on the finite-set control (FSC). After selecting the optimal voltage vectors, the steady-state torque and flux ripple is minimised using the conventional DTC and the most efficient and dynamically-fast mode of the control algorithm. The philosophy of the control approach proposed is based on the FSC and DTC. In other words, the process of optimisation relies on a combination of FSC DTC. Compared to conventional PMSM drive control, the proposed technique optimises the switching state of the inverter and minimises the cost function by adopting measures resembling DTC. In addition, the sensitivity of this method to motor parameters is very low, and it is computationally simple. The results obtained from the experiments and simulations validated the applicability of this method to PMSM drives by suggesting that the proposed model provides dynamically-fast responses to low torque and flux ripples using a simple-to-implement hybrid structure.

In this work, a new elevator system created by a linear switched reluctance motor is presented. Unlike conventional linear motors, the proposed linear motor has more than one translator. Each phase in a translator generates a pulsing force; hence, the total generated force has noticeable ripple making it difficult to soft motion. In order to solve this problem, similar phases in different translators have been located in positions with specified distances together. As a result, similar force pulses would be shifted so that they can compensate together. An appropriate control strategy has been designed for the system, which can control the current, force, speed, and position simultaneously. A conventional proportional-integral controller and an adaptive fuzzy controller have been used to control the speed. In order to have a precise study, a prototype elevator system along with its control unit has been made and the obtained results have been compared with the simulation results. These results confirm that the proposed structure can significantly produce force and speed ripples. The Institution of Engineering and Technology 2020. Scopus 2-s2.0-85091657149

Model predictive control is an effective approach to achieve high performance on electric motor drives. In this study, a two-vector based low-complexity model predictive flux control (TVLC-MPFC) is proposed and introduced for low power current-source inverter (CSI)-fed induction motor (IM) drive. In contrast to conventional two-vector based model predictive flux control (TV-MPFC), TVLC-MPFC is a more simplified scheme with a lower calculation burden, which eliminates the requirement on the iteration procedures to obtain the results of the optimal current vector combination with optimal dwell time. Moreover, since TVLC-MPFC avoids the possibility of selecting the wrong vector combination in some cases, which would happen with conventional TV-MPFC, it presents better output performance than TV-MPFC. The robustness of TVLC-MPFC under parameter uncertainty is discussed as well. Experimental tests are carried out on a low power CSI-fed IM drive (5 kW/208 V/14.3 A) and verify the effectiveness of the proposed scheme.

In this study, an intelligent second-order sliding mode control (SMC) method combining second-order SMC (SOSMC) and recurrent radial basis function neural network (RRBFNN) applicable to the permanent magnet linear synchronous motor (PMLSM) is proposed to achieve high-performance servo control fields. On the basis of a dynamic model of PMLSM and the SMC theory, the chattering problem in SMC is weakened and the tracking accuracy is improved by the design of SOSMC. As for the boundary of the uncertainty factors is difficult to obtain, the optimal performance of SOSMC is hard to achieve, the RRBFNN uncertainty observer is introduced for estimating the value of the uncertainty factors. Owing to the strong learning ability, the network parameters can be trained online. Besides, a robust compensator is developed to suppress the uncertainties such as approximation error, optimal parameter vector and higher Taylor series for further improving the robustness. Moreover, the adaptive learning algorithms are obtained by using the Lyapunov theorem to guarantee the asymptotical stability of the system. The experiments demonstrate that the proposed scheme provides high performance dynamic characteristics and strong robustness to uncertainties.

The industrial application of electric machines in variable-speed drives has recently grown thanks to the development of microprocessors and power converters. Although three-phase machines constitute the most common case, the interest of the research community is also focused on multiphase machines with more than three phases. The principal reason lies in the exploitation of their advantages such as reliability, better current distribution among phases or lower current harmonic in the converter, to name a few. Nevertheless, multiphase drive applications require the development of complex controllers to regulate the torque (or speed) and flux of the machine. In this regard, predictive current controllers have appeared as a viable alternative due to an easy formulation and high flexibility to incorporate different control objectives. It is found, however, that these controllers face some peculiarities and limitations in their use that require attention. This work attempts to tackle the predictive current control technique as a viable alternative for the regulation of multiphase drives, paying special attention to the development of the control technique and the discussion of the benefits and limitations. Case examples with experimental results using a symmetrical five-phase induction machine with distributed windings are included to this end.