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Abstract Wireless power transfer (WPT) is a promising technology and has attracted many researchers’ attention due to its inherent advantages such as reliability, safety, flexibility, and low maintenance costs. For WPT systems, the output voltage varies according to the variable loads and the coupling coefficient conditions, affecting system stability and efficiency. In this regard, this study is concerned with the tracking control problem of WPT systems based on fuzzy supervisory proportional–integral (PI) controller and a phase shift modulation technique, which is for the first time proposed by this paper. By introducing appropriate fuzzy rules, the proposed control scheme not only can track the desired output voltage but also has better robust behaviour to deal with the problem of variations of circuit elements and coupling coefficients. That is, the proposed fuzzy supervisory PI control scheme can perform better than the traditional PI controller. Analysis of the designed control method and simulation results validate the superiority of the proposed method over the traditional PI controller in all conditions, which can make it a suitable choice for the applications of electric vehicle charging systems. The analysis is supported by experimental measurements.

Wireless power transfer (WPT) is a promising technology and has attracted many researchers' attention due to its inherent advantages such as reliability, safety, flexibility, and low maintenance costs. For WPT systems, the output voltage varies according to the variable loads and the coupling coefficient conditions, affecting system stability and efficiency. In this regard, this study is concerned with the tracking control problem of WPT systems based on fuzzy supervisory proportional–integral (PI) controller and a phase shift modulation technique, which is for the first time proposed by this paper. By introducing appropriate fuzzy rules, the proposed control scheme not only can track the desired output voltage but also has better robust behaviour to deal with the problem of variations of circuit elements and coupling coefficients. That is, the proposed fuzzy supervisory PI control scheme can perform better than the traditional PI controller. Analysis of the designed control method and simulation results validate the superiority of the proposed method over the traditional PI controller in all conditions, which can make it a suitable choice for the applications of electric vehicle charging systems. The analysis is supported by experimental measurements. [ABSTRACT FROM AUTHOR]

As road traffic develops, energy-saving and efficient street lights have become a key research field for relevant professionals. To reduce street lights energy consumption, a fireworks algorithm is used to optimize the membership function parameters of fuzzy control and the initial parameters of PI control. A fireworks algorithm improved adaptive fuzzy PI solar LED street light control system is designed. The results showed that in the calculation of Root-mean-square deviation and Mean absolute error, the Root-mean-square deviation of the adaptive fuzzy PI control system improved by the fireworks algorithm was 0.213, 0.258, 0.243, 0.220, and the Mean absolute error was 0.143, 0.152, 0.154, 0.139, respectively, which proved that the prediction accuracy was high and the stability was good. In the calculation of the 1-day power consumption of the solar LED intelligent control system, the average power consumption of the designed solar LED intelligent control system was about 2000W, which was 25.9%, 47.4%, and 42.9% lower than the other three control methods, respectively. This proves that its energy consumption is low, and its heat generation is low, and the battery service life is long. The research and design of an adaptive fuzzy PI control solar LED street light intelligent control system has good performance, which can effectively achieve intelligent management and energy conservation and emission reduction in smart cities.

Copyright of Machine Tool & Hydraulics is the property of Guangzhou Mechanical Engineering Research Institute (GMERI) and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Single-phase single-stage three level AC-DC power factor correction converters are commonly used as switch mode power supplies in telecommunication systems to provide effective power conversion with good operating performance. This paper deals with the comparative analysis of the converter response with four different control techniques, namely proportional integral and derivative controller (PID), fuzzy Logic controller (FLC), sliding mode controller (SMC), and average current controller (ACC) for wide operating conditions. Necessary analytical equations are derived to observe the dynamic behavior of the converter. Simulations are done with MATLAB/Simulink, and the responses of the PID, FLC, SMC, and ACC are compared for line and load regulations. It is observed that the average current control technique yields better transient and dynamic response than the other three control techniques. The effective performance of the ACC is validated through experimentation.

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. [ABSTRACT FROM AUTHOR]

Renewable energy resources energy is widely collected from the natural resources of wind, photovoltaic, and geothermal heat energy. Generally, the hybrid system is affected by the unwanted power quality issues such as harmonics, voltage sag, and swell. The proportional resonant (PR) controller is optimised with an Elephant herding optimisation (EHO) algorithm to investigate the dynamic performance of buck–cuk power converters in hybrid renewable energy sources. The proposed power converter is used to regulate the level of voltages by controlling the switching pulse of the converter depending on the duty cycle ratio. An EHO algorithm is employed for tuning the PR controller gain parameters. In the grid side, shunt active power filters are integrated, and the inductor–capacitor–inductor filter is utilised for solving the overshoot and settling time problems. The total harmonic distortion (THD) and steady‐state error are reduced by the proposed technique. The proposed system is designed with the help of MATLAB/Simulink platform, and the output response is determined with the simulated results. The dynamic response of the proposed system is examined based on simulated outcomes, and THD comparison analysis is performed with the existing controllers such as proportional–derivative, proportional–integral–derivative, and fuzzy controller. [ABSTRACT FROM AUTHOR]

This study reports on the development and implementation of the fuzzy incremental controller on a small‐scale linear fresnel reflector solar plant. The control problem is concerned with forcing the output temperature to follow the reference, despite the existence of disturbances. Owing to the non‐linear effects of solar plants, the capability of fixed parameters of the proportional–integral controller to cope with the control problem is limited and leads to unsatisfactory control performance. The proposed controller is a modification to a conventional proportional–integral algorithm with better tuning flexibility. Firstly, the ant colony optimisation algorithm is used to define the optimal parameter of proportional–integral plus series feed‐forward controller while guaranteeing a satisfactory performance of the plant. Secondly, the resulting controller is replaced with an equivalent fuzzy knowledge‐based controller with the error and change of error of the plant as the input variables and flow rate as an output variable. The proposed controller is tested on a quasi‐dynamic model of linear fresnel reflector plant using conventional and renewable energy optimisation toolbox in the environment of MATLAB/Simulink. The controller's performance is compared to the proportional–integral controller, where its effectiveness is evaluated under nominal conditions, measurement delay, noise, and presence of disturbance. [ABSTRACT FROM AUTHOR]

This study presents the structural, operational and control aspects of doubly fed induction generator (DFIG) based wind integrated power systems. The automatic generation control (AGC) of a meshed power system including DFIG-based wind turbines has been framed and investigations under various system perturbation are presented. The two-area system consisting of non-reheat thermal turbines with DFIG and interconnected through parallel AC/DC tie-lines is considered for the study. The system non-idealities such as governor lag and generation rate constraints are taken into consideration. An AGC strategy using a layered recurrent artificial neural network (ANN) is proposed in this work. The gains of the proposed AGC are obtained by effectively training the ANN using a set of reliable data obtained from a widespread range of operating system conditions using robust control strategy. The study also incorporates the design of AGC for the power system using the fuzzy logic concept and other AGC actions such as integral (I), proportional–integral (PI) and proportional–integral–derivative (PID) calculated via the means of particle swarm optimization (PSO). The results obtained with the proposed ANN created AGC are linked and demonstrated their superiority over fuzzy logic PI and traditional PSO-based I/PI/PID AGC strategies under numerous system operating conditions. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Photovoltaic (PV) emulator (PVE) is a non‐linear power supply that produces a similar output to that of the PV module. It requires a closed‐loop controller such as the proportional–integral (PI) and fuzzy logic controllers to operate properly. The PI controller has a low‐computational burden and is not robust since the transient response varies under different load conditions. Although the fuzzy logic controller is robust, it requires high‐computation capability. This study proposed an alternative approach called the shift controller for the PVE to easily compute and maintain a fast transient response under various load conditions. The performance of the proposed shift controller for the PVE is compared with the performance of the PVEs using the PI and fuzzy logic controllers, respectively. The controllers are simulated using MATLAB/Simulink and implemented using dSPACE ds1104 for experimental validation. The results show that the proposed shift controller computes up to 18 times faster than the fuzzy logic controller. The proposed controller also responds faster to load change than the PI controller. [ABSTRACT FROM AUTHOR]

A multi-microgrid (MMG) system comprises of a group of self-sufficient microgrids capable of operating in grid-connected, islanded, or interconnected modes. A three-microgrid-based MMG system consisting of a solar photovoltaic system, doubly-fed induction generator-based wind generation, and static synchronous compensator as distributed energy sources are considered. Each microgrid includes a battery interfaced with a bidirectional DC–DC converter. As there are multiple battery units in the MMG system, different states-of-charge (SoC) are evident in the batteries. Hence, there is a need to charge/discharge by following the SoC of the batteries. In this study, an intelligent scheme employing fuzzy logic is applied to monitor the SoC of the batteries and determine the reference current for current control through the bidirectional DC–DC converter in an MMG system. Microgrid frequency control in the MMG system is carried out using the proposed five-membership function-based fuzzy logic control. During sudden transient events, the proposed intelligent frequency control strategy shows an improved transient response as compared to conventional PI control. A multi-input and multi-output fuzzy logic-based power management algorithm is proposed to handle multiple sources, batteries, and loads in the system. The MMG system with the proposed control is simulated using real-time digital simulator OP4510 from OPAL-RT. [ABSTRACT FROM AUTHOR]

Copyright of Computer Measurement & Control is the property of Magazine Agency of Computer Measurement & Control and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

According to the disadvantages of PID control, this paper aims at applying fuzzy control in FOC control of PMSM. The controller automatically adjusts the two parameters of the PI controller based on changes in e and ec. The simulation result shows that more dynamic and steady-state can be obtained by using fuzzy PI control. [ABSTRACT FROM AUTHOR]

Hybrid distribution transformer (HDT) is a novel transformer that has a powerful control on grid current and load voltage, and it is significant for the construction of the smart grid. The load voltage control is the key part in HDT control system. Here, a load voltage control strategy based on fuzzy PI controller is proposed, since the traditional PI controller cannot achieve satisfying dynamic performance under the operation of grid voltage change. The fuzzy controller can respond faster than PI controller for the outputs that is only determined by inputs and independent with time, when the grid voltage rags or swells. While combining the fuzzy controller with the PI controller, the fuzzy control will cover the shortage of PI control in transient process and the PI control ensures that the static performance will not be affected. In the end, the simulation model of HDT is carried out, and the result shows that the load voltage can track the reference faster than the traditional PI controller, which improves the performance of voltage control system. [ABSTRACT FROM AUTHOR]

The study on the stability of DC bus voltage is one of the key issues for researching independent DC microgrid. This paper has studied the independent DC microgrid with photovoltaic and energy-storage systems. The variable step incremental conductance method was taken to realise maximum power point tracking (MPPT). The self-adaptive Fuzzy-PI controller was designed to optimise the traditional double closed-loop control strategy. The energy management system was built to achieve coordinated control of the independent DC microgrid. The simulation results show that the improved strategy can get better robustness and system performance comparing with the traditional PI method. [ABSTRACT FROM AUTHOR]

This study presents an improved power management control strategy of a hybrid direct current (DC) micro‐grid (MG) system consisting of photovoltaic cell, wind turbine generator, battery energy storage (BES), fuel cell (FC), and electrolyser. Based on the voltage and state of charge of BES, FC, and electrolyser, the proposed control scheme improved the dynamics of the DC‐link voltage and contributes a better power management between each generation/source and load. A gain control technique is implemented in the grid‐side inverter controller to regulate the modulation index and improving the voltage stability of the DC‐link. Furthermore, the PI‐controller gains of BES are tuned dynamically based on the deviation in voltage and its derivative using Takagi–Sugeno‐fuzzy control to enhance the transient response of the voltage. For a reliable operation of the DC MG under standalone or prolonged islanding mode of operation, a priority‐based load shedding algorithm is proposed for maintaining proper power coordination between different energy sources and storage devices. Owing to smoother and faster voltage response, the proposed control schemes can comply with the grid code requirements of the changing configuration of the modern renewable energy integrated DC MG. The effectiveness of the proposed control strategy is tested by comparing the existing scheme through MATLAB/Simulink®. [ABSTRACT FROM AUTHOR]

In this paper, a new four-port DC-DC converter topology is proposed to interface renewable energy sources and the load along with the energy storage device. The proposed four-port SEPIC/ZETA bidirectional converter (FP-SEPIC/ZETA BDC) converter comprises an isolated output port with two unidirectional and one bidirectional input ports. This converter topology is obtained by the fusion of SEPIC/ZETA BDC and full-bridge converter. This converter topology ensures the non-reversal of output voltage hence it is preferred mostly for battery charging applications. In this work, photovoltaic (PV) source is considered and the power balance in the system is achieved by means of distributed maximum power point tracking (DMPPT) in the PV ports. The centralized controller is implemented using fuzzy logic controller (FLC) and the performance is compared with conventional proportional integral (PI) controller. The results offer useful information to obtain the desired output under line and load regulations. Experimental results are also provided to validate the simulation results.

Electrical and electronic devices, when exposed to one or more power quality problems, are prone to failure. This study aims to enhance the quality of power in three-phase four-wire distribution grid using fuel cell integrated unified power quality conditioner (FCI-UPQC). The proposed FCI-UPQC has a four-leg converter on the shunt side and three-leg converter on the series side. A combination of a synchronous reference frame and instantaneous reactive power theories is utilised to generate reference signals of the FCI-UPQC. Also, this study proposes an adaptive neuro-fuzzy inference system (ANFIS) controller to maintain the DC-link voltage in the FCI-UPQC. The ANFIS controller is designed like a Sugeno fuzzy architecture and trained offline using data from the proportional–integral controller. The obtained results proved that the proposed FCI-UPQC compensated power quality problems such as voltage sag, swell, harmonics, neutral current, source current imbalance in the three-phase four-wire distribution grid. The presence of fuel cell in this work makes more effectiveness of the proposed system by providing real power support during supply interruption on the grid side.

The study on the stability of DC bus voltage is one of the key issues for researching independent DC microgrid. This paper has studied the independent DC microgrid with photovoltaic and energy-storage systems. The variable step incremental conductance method was taken to realise maximum power point tracking (MPPT). The self-adaptive Fuzzy-PI controller was designed to optimise the traditional double closed-loop control strategy. The energy management system was built to achieve coordinated control of the independent DC microgrid. The simulation results show that the improved strategy can get better robustness and system performance comparing with the traditional PI method.

Hybrid distribution transformer (HDT) is a novel transformer that has a powerful control on grid current and load voltage, and it is significant for the construction of the smart grid. The load voltage control is the key part in HDT control system. Here, a load voltage control strategy based on fuzzy PI controller is proposed, since the traditional PI controller cannot achieve satisfying dynamic performance under the operation of grid voltage change. The fuzzy controller can respond faster than PI controller for the outputs that is only determined by inputs and independent with time, when the grid voltage rags or swells. While combining the fuzzy controller with the PI controller, the fuzzy control will cover the shortage of PI control in transient process and the PI control ensures that the static performance will not be affected. In the end, the simulation model of HDT is carried out, and the result shows that the load voltage can track the reference faster than the traditional PI controller, which improves the performance of voltage control system.

A novel generalised Hopfield neural network (GHNN) based self‐adaptive proportional–integral–derivative (PID) controller for load frequency control (LFC) is designed for a two‐area interconnected power system with nonlinearities of generator rate constraint and governor dead band. The control problem is conceptualised as an optimisation problem with an objective function as an area control error in terms of the PID controller parameters. The differential equations governing the behaviour of the GHNN were solved to obtain the controller parameters Kp, Ki and Kd. To test the feasibility and robustness of the proposed controller, the system is tested in the presence of randomness in load demands, imprecisely modelled system dynamics, nonlinearities in the system model and uncertainties in the system parameter variations. The proposed method is simulated using Matlab R2014b/Simulink and the results obtained have shown that the propounded controller performance is superior to the integral, PID and fuzzy‐based proportional–integral controllers. In addition, the Lyapunov stability analysis of the overall closed‐loop system was carried out and the controller is implemented in real‐time digital simulator run in hardware‐in‐the‐loop to validate the effectiveness of the proposed method. Furthermore, the proposed controller is applied to the three‐area power system to test its adaptability. [ABSTRACT FROM AUTHOR]

A new direct adaptive fuzzy speed control method for a linear switched reluctance motor with unknown control gain sign is presented. The proposed control system consists of two parts: a fuzzy system and an adaptive law. Fuzzy system approximates an unknown ideal control law with unknown adjustable parameters. After determination of the control law, an appropriate adaptation law is designed to update the adjustable parameters to achieve control objectives. The adaptation law is designed using the error between the unknown ideal control law and fuzzy control law. Unlike previous works, in this study, the unknown control gain sign is taken as an unknown constant parameter and is determined online by an appropriate adaptation law. Proposed control method along with a fuzzy sliding mode speed control and a proportional integral speed control strategies are experimentally studied and the performance index is used to evaluate each strategy. The robustness of the proposed method to the parameters and external load force change has been verified via simulation and experiments. The results indicate that the proposed control method has an acceptable performance. [ABSTRACT FROM AUTHOR]

This study focused on the high-precision and efficient steering control of a flexible chassis with a fuzzy-PI composite technique. The flexible chassis is a four-wheel independent steering and four-wheel independent drive electric chassis based on an off-centered steering axis module. The off-centered steering axis module is steered by jointly controlling the speed of the wheel and the locking torque of the electromagnetic steering lock. The fuzzy controller is applied to control the electromagnetic steering lock to reduce steering resistance and accelerate the steering process when the steering angle error is big, and the PI controller is designed to stabilize the steering process and to ensure the accuracy when the steering angle error is small. Simulation results showed that the proposed composite control system is very robust to steering angle without sacrificing high precision and efficiency. [ABSTRACT FROM AUTHOR]

The static synchronous compensator (STATCOM) has attracted considerable attention because it can stabilise severe transients that are caused by power system disturbances. This study presents a novel interval type 2 fuzzy control system (IT2‐FCS)‐based controller for the STATCOM to stabilise bus voltages that are caused by faults or forced wind farm outages in a smart grid. Two IT2‐FCSs are presented to tune increments of the proportional integral (PI) controller, which are optimised by the gradient descent method. The IT2 fuzzy rules, involving upper and lower membership functions, result in a fast and stable system response. Since many possible scenarios may arise in the power system, the Taguchi method is used to design experiments using an orthogonal array, in which all scenarios are mutually independent. A power system that consists of a wind farm and STATCOM is studied. Comparative studies show that the proposed method is superior to traditional PI and type 1 FCS methods. [ABSTRACT FROM AUTHOR]

Voltage sag is the most common and severe power quality problem in the recent times due to its detrimental effects on modern sensitive equipment. Generally, direct‐on‐line starting of the three‐phase induction motor (IM) and various kinds of short circuit fault are directly responsible for this event. This study investigates the impacts of starting and stopping of two three‐phase IMs on the load voltage profile. To be more critical, two three‐phase short circuit faults and one unsymmetrical fault are also simulated in the same network at different instants of time. A simple control algorithm of a real power optimised dynamic voltage restorer (DVR) with a reduced power factor strategy is presented to protect the sensitive load from these types of detrimental events. A novel fuzzy‐proportional–integral based self‐tuned control methodology is implemented in the proposed work to compensate the loss in the DVR circuit as well as to regulate the load voltage and the direct current link voltage. The results show the effectiveness of the adopted control scheme in DVR application to mitigate the voltage sag. [ABSTRACT FROM AUTHOR]

In this paper, the vector control strategy along with a non linear control are applied to the doubly fed induction generator (DFIG) based wind energy. Three control strategies (PI, Fuzzy and sliding mode control) are explained, analysed and compared in terms of response time, harmonic filtering and robustness to the parametric variation. These control strategies are evaluated in the steady and transient state to control both the active and the reactive power in the grid connected mode. The analysis of the DFIG behaviour under the mentioned control strategies is verified in the simulations. Also, a representation of numerical results is displayed in a summary table. The three strategies control present some advantages and drawbacks in term of performances when they operate with power optimization and power limitation strategies. However, the sliding mode control is better under the parameters variation and speed change. Although, the fuzzy control delivers a fast response time and presents a good harmonic distortion value(THD) while the PI control ensures a perfect precision during constant wind speeds. [ABSTRACT FROM AUTHOR]

This paper investigates on an additional active power compensation of a microgrid to a weak grid using fuzzy‐supervisory control. This reduces the economic penalty of microgrid for going over‐contract with the grid in terms of power demand. The objectives of this work are (a) to maximise grid support during periods of over‐contract, (b) to minimise distortions and increase dynamic stability of dc link voltage and (c) to improve the total harmonic distortion (THD) of the dispatched power. The microgrid comprises of a wind energy conversion system (WECS) and Li‐ion battery energy storage system (BESS). During variations in wind speed, power feed into the point of common coupling (PCC) depends upon deviations in the wind power, dc link voltage, violations in grid contract power and the state of charge (SOC) of the battery. The deviations in these inputs are utilised by the supervisory controller to compute additional power support to the grid, by discharging the battery. Performances of the fuzzy‐supervisory controller are compared with a classical‐supervisory controller with similar power dispatch parameters. Further, inverter currents are regulated using a fuzzy proportional‐derivative and integral (FPD + I) controller to reduce distortions and improve dynamic response of the dispatched power. [ABSTRACT FROM AUTHOR]

A novel fuzzy proportional–integral (PI) control with fault ride‐through (FRT) capability is investigated for double fed induction generators (DFIGs), where an approximation error considered Takagi–Sugeno fuzzy observer is employed to approximate the non‐linear model of DFIG. Based on the obtained observer, a H2 controller with PI structure is used to achieve specified engineering purposes, such as maximum power point tracking and automatic voltage regulator. A H∞ controller is proposed to cope with the undetected disturbances in the H2 control, and a robust technique is also proposed to override the effect of approximation error due to the fuzzy approximation. Then, the controller design is formulated as a mixed H2/H∞ suboptimisation problem with the regional pole placement constrain, which can be solved easily by using linear matrix inequality technology. In order to further improve the FRT capability, a power angle compensator is proposed to reduce terminal voltage drop via limiting DFIG power angle jump during faults. The results of dominant eigenvalue analysis and simulation are presented and discussed, which shows the capabilities of DFIG with the proposed control strategy to improve system damping, fault‐tolerant control and FRT, and its contribution on power system transient stability support. [ABSTRACT FROM AUTHOR]

A decentralised control scheme is proposed to manipulate the speed and the pitch angle of a 1.5 MW wind turbine. In region 2, the goal is to capture maximum power by tracking a reference turbine's speed. For region 3, the goal is to regulate the turbine's speed at its rated value and harvest the rated power. L1 adaptive controllers are proposed to achieve the previous goals. A new L1 adaptive algorithm, based on fuzzy modelling and variable structure adaptation, is introduced. Performance bounds on the proposed controllers are derived. Simulation results illustrate the superiority of the proposed algorithm compared with both proportional–integral and basic L1 adaptive controllers. [ABSTRACT FROM AUTHOR]

This study presents a fuzzy‐proportional–integral (PI) controller having self‐tuning property for current control of doubly fed induction generator (DFIG). Two fuzzy‐PI‐based controllers: first one is used for controlling rotor current of DFIG, whereas the other come up with optimal output‐scaling factor for the former are employed to carry out the algorithm. The proposed controller is robust with different operating conditions and parameter changes because of having adaptive feature. The performance of the control algorithm both transient and steady‐state conditions are tested with several experiments performed various operating points. The results achieved from both simulation and experimental tests verify that the implemented method is superior to steady‐state and transient response at all operations as exhibits robustness to wind speed and parameter variations. [ABSTRACT FROM AUTHOR]

In this study, novel adaptive fuzzy fault‐tolerant control method is proposed for multiple high‐speed trains (HSTs) in the presence of actuator faults, unknown non‐linear dynamics and external disturbances. The fuzzy logic system is used to approximate the unknown functions. Based on proportional and integral‐based sliding mode technique, two adaptive fuzzy control schemes are then proposed to achieve string stability. In the first scheme, the actuator faults are not considered. In the second scheme, a novel fuzzy fault‐tolerant control with fewer adjustable parameters is constructed to further reduce the online computational load. By using Lyapunov analysis, the individual stability and string stability of whole multiple HSTs are proven. In addition, all signals of the closed‐loop system are uniformly ultimately bounded and all HSTs track the reference trajectory to a small compact set around zero. Finally, comparative simulation is introduced to verify the reliability and effectiveness. [ABSTRACT FROM AUTHOR]

nente. Tal tipo de dispositivos de electrónica de potencia convierten una tensión continua a otra de menor magnitud y cuyas ca- racterísticas de no linealidad son evidenciadas. Se presentan entonces, dos técnicas de control no lineal, la primera propuesta es un control óptimo PI (error proporcional e integral del error) convencional, basado en la minimización del criterio ITSE (integral del cuadrado del error ponderado en el tiempo). Para ello se obtiene un modelo de la planta en un punto de operación. La se- gunda propuesta es un control difuso cuyos conjuntos de entrada y salida son también definidos minimizando el criterio ITSE en el sistema general, y estableciendo como entradas el error proporcional y la integral del error. A continuación se realiza una va- riación de la carga para establecer la eficiencia del sistema con los dos controladores mencionados. Se debe tener en cuenta que este tipo de sistemas no debe presentar sobretensiones considerables, ya que puede ocasionar daño en él. En este sentido, los parámetros encontrados en el diseño de los dos controladores corresponden a una metodología analítica y descriptiva. Los resultados obtenidos en simulación, y estableciendo como figura de mérito el índice de desempeño mencionado (ITSE) y el con- sumo de potencia, muestra que la respuesta del sistema para el control difuso presenta un mayor consumo de potencia que el control óptimo, mientras que el ITSE obtenido es mayor para el control óptimo que para el difuso. Se concluye que la explora- ción de este tipo de conversores, utilizando técnicas de control no lineal y minimizando los diferentes índices de desempeño, es aplicable.

This paper deals with a comparison study between different kinds of controllers based on a speed tracking problem inside an electrical vehicle using an axial-flux permanent-magnet traction motor. In fact, the framework of these works is the control of the powertrain of electric vehicles which is a great challenge to ensure driving comfort. To do so, the vehicle's performances are carried out using an established simulation platform implemented on Matlab- Simulink environment. Then, obtained results are compared for the three synthesized controllers. It has been found that required speed levels are reached with a clear advantage of the adaptive Fuzzy-PI controller versus the PI and the fuzzy counterparts, from the points of view of rise and selling times. [ABSTRACT FROM AUTHOR]

This study presents fuzzy‐proportional–integral (PI)‐based sensorless frequency and voltage control strategy for doubly fed induction generator connected to a dc microgrid system. A significant reduction of the costs can be achieved by this topology because only a single dc/ac converter and a diode rectifier are required instead of the traditional back‐to‐back converter topology. To improve the performance of the rotor current controller, a fuzzy PI‐based control algorithm is used. Furthermore, a simple sensorless control technique based on the detection of the stator frequency is employed to detect the rotor position. The sensorless control technique can operate without the knowledge of the machine parameters. The main aim of this study is to keep the stator frequency as well as the dc bus voltage at the desired value under different load and wind speed conditions without using position sensor. Simulation and experimental studies were performed to verify the dynamic and steady‐state performances of the proposed control strategy The results show that the proposed strategy not only has an excellent steady state and dynamic performance, but also it is robust against the variation of system parameters such as wind speed and load. [ABSTRACT FROM AUTHOR]

Precise control of EC for fertilizer solution is one of the key technologies to realize smart irrigation in the production of protected vegetable. Serious lag and instability in EC detection will happen during the mixing of fertilizer and water due to differences in mother liquor concentration, fertilizer suction method and irrigation flow etc. To solve this problem, a new EC sensor was designed to measure the EC value of fertilizer solution indirectly by measuring the frequency based on different EC values leading to different equivalent resistances, and the smart irrigation system was developed as microcontroller (MSP430) was the master controller. Meanwhile, a subsection control strategy was introduced to regulate and control the EC value of fertilizer solution, and the opening or closing of electromagnetic valve for the suction of fertilizer solution was controlled by outputting corresponding duty cycle. When the difference between the target EC value and the measured value was large, PI control was adopted to narrow the gap as fast as possible. In this study, the threshold is defined as 0.2 mS/cm according to practical knowledge, therefore, fuzzy control with good robustness and high adaptability was adopted when the difference was smaller than 0.2 mS/cm. In fuzzy control stage, triangle function and centroid method were selected as membership function and defuzzification calculation with 63 rules and the output language variable value was divided into 13 levels. A compound venturi was designed as fertilizer solution suction device, with the diameter of inlet and outlet pipes was both 40 mm, and a closedcontainer (10 cm× 10 cm× 6 cm) was installed at the throat part to connect the inlet and outlet pipes, and 7 suction interface were located at the bottom of the container to link with the electromagnetic valves. The main pipe of the irrigation system was controlled by 24VDC electromagnetic valve and the drippers of the branch pipes were inserted into the substrate near plant roots. The filter was installed between inlet water and the irrigation system to avoid blocking venturi and drippers. An experiment including 4 different target EC values and 4 different suction pipelines was carried out to test the effect of the designed control system. The results showed that the frequency measured by our EC sensor had a significant linear correlation with the measured EC value with R2 is 0.999 5. In the case of subsection control, when the target EC value was 2 mS/cm, the steady response time was 122 s and maximum overshoot is 0.34 mS/ cm when 4 channels were used for fertilizer solution suction, which performed much better than only PI control with steady response time 180 s and maximum overshoot up to 0.62 mS/cm. In addition, the higher the target EC value set, the more accurate the steady EC value was, however, the steady response time became longer and overshoot was more serious. The subsection control strategy used in this study can effectively overcome excessive overshoot, also the time for mixing fertilizer solution and the measured EC value can both meet the requirements for the practical production of protected vegetable. [ABSTRACT FROM AUTHOR]

Aiming at the problems that static var compensator cannot suppress the voltage flicker and the cost of static synchronous compensator is expensive, a three‐layer hybrid reactive power compensation scheme was proposed in this study based on the expert‐decision, differential‐slope voltage regulation, and the expert‐decision subsystem combining with fuzzy self‐tuning proportional–integral (PI) control. By switching in a dynamic load which can always change the bus voltage, the whole system was simulated under the much reactive power shortage and the less shortage. The simulation results verify the effectiveness of the proposed coordinated control method in the reactive compensation and the suppression of the voltage flicker. [ABSTRACT FROM AUTHOR]

This paper introduces an intelligent extraction of optimum power and its dispatch by using fuzzy logic from a grid tied hybrid generation system comprising of a permanent magnet synchronous generator based wind turbine and a low concentration photovoltaic generator. For photovoltaic generator, maximum power point tracking control is implemented using fuzzy logic under varying solar irradiance. Power extracted from wind turbine is designed as a fuzzy function of the dc link voltage error, its rate of change and error in the direct axis current of the inverter. This reduces high frequency oscillations in the wind extracted power. Such an extraction is considered as a novelty of this paper. A failure mode and effect analysis is done for power converters and possible mitigation schemes are suggested for different faults. A 1:1 delta wye‐grounded transformer is used at the inverter output to eliminate the triplet harmonics. Further, dynamic performances of both fuzzy proportional‐derivative and integral (PD+I) controller and classical proportional integral (PI) controller, to control the inverter currents, are compared. The proposed method results in an enhanced power dispatch and improvement in distortions and oscillations in the converter currents. This also reduces the probability of failures in the converter switches and other passive components. [ABSTRACT FROM AUTHOR]

In this paper, a fuzzy proportional derivative and/or a classical proportional integral is used to control the terminal voltage of the photovoltaic (PV) array connected to the input of a dc/dc step-up converter. The voltage reference is tracked continuously by employing a perturb and observe and the incremental conductance algorithms in order to make the PV array operate as close as possible to the maximum power point (MPP). However, these techniques produce oscillations around the MPP, which can be reduced by applying adaptive steps instead of fixed steps. Additionally, this paper presents the complete mathematical model of the power converter associated with a PV array where the parasitic elements are included. Simulations and experimental results under different environmental conditions are presented to demonstrate the effectiveness of the proposed approach. [ABSTRACT FROM AUTHOR]

This study mainly focuses on the development of two newly designed control strategies including an adaptive control scheme and a fuzzy neural network (FNN) control system for a single-stage boost inverter. First, the dynamic model of a single-stage boost inverter is analyzed and built for the later control manipulation. Then, a model-based adaptive control scheme and a model-free FNN control system with varied learning rates are designed sequentially. The effectiveness of the proposed adaptive control scheme and the proposed FNN control system is verified by experimental results of a 1-kW single-stage boost inverter prototype, and their merits are indicated in comparison with a traditional double-loop proportional-integral (PI) control framework. Experimental results show that the superior FNN control system has significant improvements of 45.2% total harmonic distortion and 37.1% normalized mean square error compared to the conventional double-loop PI control framework under nonlinear loads. [ABSTRACT FROM PUBLISHER]

With the rapid growth of the wind energy systems in the past years and their interconnection with the existing power system networks, it has become very significant to analyse and enhance the transient stability of the wind energy conversion systems connected to the grid. This study investigates the transient stability enhancement of a grid‐connected wind farm using doubly‐fed induction machine‐based flywheel energy storage system. A cascaded adaptive neuro‐fuzzy controller (ANFC) is introduced to control the insulated gate bipolar transistor switches‐based frequency converter to enhance the transient stability of the grid‐connected wind farm. The performance of the proposed control strategy is analysed under a severe symmetrical fault condition on both a single‐machine infinite bus model and the IEEE‐39 bus New England test system. The transient performance of the system is investigated by comparing the results of the system using the proposed ANFCs with that of the black‐box optimisation technique‐based proportional–integral controllers. The validity of the system is verified by the simulation results which are carried out using PSCAD/EMTDC environment. [ABSTRACT FROM AUTHOR]

In this study, a fuzzy‐PI controlled grid interactive inverter has been designed and implemented. The proportional and integral gains of the PI controller are decided and tuned by the fuzzy logic controller (FLC) according to required operation point of the system. Thus, adaptive nature of the FLC and robust structure of the PI controller are synthesised. Eventually, an adaptive PI controller which can adopt changes because of different operation conditions, grid disturbances and natural effects with fast transient response is obtained. Simulation studies are validated with experimental results. Both simulation and experimental results show that proposed system has fast dynamic response and tracks reference current with a low overshot and short settling time. In addition, the waveform of the inverter output current is sinusoidal and also the current is in same phase and frequency with the line voltage. Furthermore, the total harmonic distortion level of the inverter current meets the international standards. In addition, the proposed inverter system is compared with conventional PI controlled grid interactive inverter with various proportional and integral gains. [ABSTRACT FROM AUTHOR]