Fuzzy PI Controller Research Articles

STATCOM with Fuzzy-PI Controller for Low Voltage-Ride through Enhancement of DFIG based Wind Farm

This paper represents the study of Fuzzy Logic Control-Based STATCOM devices to enhance the capabilities of the low voltage-ride through of a grid connected DFIG based wind farm and its comparison with conventional STATCOM device. The proposed FLC based STATCOM device have designed using MATLAB/Simulink.Compare to the output responses of the voltage, currents, speed, real power and reactive power of both stator as well as rotor of the two investigated systems during grid faults, the STATCOM with fuzzy-PI controller gives best performance with faster recovery, adjustable speed, smoother current profiles and better reliable than traditional controller

Optimal Management Energy System and Control Strategies for Isolated Hybrid Solar-Wind-Battery-Diesel Power System

This paper proposes optimal control strategies of a standalone Hybrid Power System (HPS) to supply sustainable and optimal energy to an isolated site with improved quality of electrical energy. A topology of Isolated Hybrid Power System (IHPS) is proposed, consists of: a Photovoltaic System (PVS), a Wind Energy Conversion System (WECS), electronic power devices controlled to maximize energy production from renewable sources and to maintain the constant DC-link voltage, a Battery Energy Storage System (BESS), Diesel Generator (DG), and a Pulse Width Modulation (PWM) Voltage Source Inverter (VSI) located at the load-side end. In addition, a novel control strategy has been proposed, in this work, to maximize the power from the PVS. This presented strategy, based on the combination between Perturb and Observe (P&O) algorithm and the Fuzzy PI Controller (FPIC), presents a good performance, especially in the dynamic state compared to the classical algorithm P&O. A supervisory control algorithm has been elaborated to manage the energy flows between the devices of the hybrid system to make the decision of the optimal operating mode in order to ensure a continuous supply of the load with minimum usage of batteries and DG. The simulation results developed in the Matlab/Simulink environment are applied to show the efficiency and performance of the proposed control strategies in terms of power optimization and energy management. Doi: 10.28991/esj-2021-01262 Full Text: PDF

Adaptive type-2 fuzzy PID controller for LFC in AC microgrid

An AC microgrid (MG) system links the distributed generation (DG) based on renewable energy resources and local electrical loads in modern power systems. Intermittent characteristics of wind and solar resources influence not only the availability of energy but also the stability of the entire AC microgrid. This matter as well makes a challenge on the load frequency control (LFC) problem in an islanded MG system, and consequently, the fixed structure controllers are unable to provide a proper performance over a wide range of operating conditions. Therefore, it is required to design a dedicated controller for LFC to ensure the capability of maintaining a generation–load balance by managing the intermittent resources. In this paper, an adaptive type-2 fuzzy PID (T2FPID) controller is suggested for LFC in an AC MG system to enforce the frequency deviation to zero by supplying the load demands. The designed T2FPID controller is a nonlinear controller that can handle the system nonlinearities and uncertainties in the MG system in a better way. Using a Lyapunov function, the stability of the system is evaluated and parameter tuning laws for the T2FPID controller are derived using this function. It has been illustrated that the adaptive parameters are bounded and the frequency deviation reaches to zero properly. The proposed adaptive T2FPID controller has been applied for LFC of a MG system, and the simulation results have been compared with those obtained by type-1 fuzzy (T1F) PI and nonadaptive fuzzy PID controllers, which is the latest research in the problem in hand. The simulation results indicate the efficiency of the proposed adaptive controllers in dealing with intermittent resources and changing in the power system parameters.

Research on the tracing accurate of force based on fuzzy-pi control for a high-speed landing system

Low-gravity simulation platforms play a crucial role in investigating motion states of the lander when landing on the surface of other planets. During the high-speed landing of landers, platforms demand for constant force in real time. A hybrid Fuzzy-PI strategy is proposed in this paper to improve the tracing accurate of force for the high-speed landing system. To enhance contrasts, conventional PI control scheme is also complemented. In view of the characteristic of large-inertia systems, influence of friction on the experiment cannot be neglected. Therefore, a friction measurement experiment is carried out to ensure the accuracy of the numerical simulation results. First, a theoretical model of the system comprised of motors, retarders, rollers and loads is analyzed. Furthermore, simulations of the theoretical model under different disturbing force are compared between these two control methods (Fuzzy-PI and PI), which verifies great effectiveness and performance of the proposed strategy. Finally, experiments are conducted to evaluate the model, and the results are satisfactory.

Coordinated control of rotor kinetic energy and pitch angle for large‐scale doubly fed induction generators participating in system primary frequency regulation

This paper presents a control strategy of large-scale wind-thermal power joint primary frequency regulation. First, an integrated control strategy is established rotor kinetic energy control and pitch angle control for wind turbine generators participation in frequency regulation within a wide range of wind velocity; Second, a fuzzy PI controller is designed for the recovery control of the wind turbine, which can avoid the occurrence of the frequency secondary drop accident during the wind generator exits the frequency regulation. Third, an optimal allocation power strategy of wind generator frequency modulation based on weighting factors is proposed in different operating conditions to make full use of the frequency modulation capability of wind turbine rotor kinetic energy control, and the strategy of orderly exiting the frequency modulation of the wind generators is established. Finally, the control framework for proposing the strategy is constructed to enhance the primary frequency regulation ability of large-scale wind generators connected to power systems. The feasibility of proposing the strategy is verified by two examples. The results show that the presented strategy is able to heighten the characteristics of the power system frequency response availably and provide a reference for power system scheduling with large-scale wind power.

Using radial basis function neural network for PMSM to overcome the changing load

This paper presents a using Radial Basis Function Neural Network (RBFNN) for PMSM to overcome the changing load. Firstly, a mathematic model of the PMSM drive is derived; then, to increase the performance of the PMSM drive system, a Fuzzy PI controller in which an RBFNN adjusts its parameters is applied to the speed controller for coping with the effect of the system dynamic uncertainty and the external load. Secondly, the Very high-speed integrated circuit Hardware Description Language (VHDL) is adopted to describe the behaviour of the speed control IC which includes the circuits of space vector pulse width modulation (SVPWM), coordinate transformation, RBFNN, and Fuzzy PI. Thirdly, the simulation work is performed by MATLAB/Simulink and ModelSim co-simulation mode, provided by Electronic Design Automation (EDA) Simulator Link. The PMSM, inverter, and speed command are performed in Simulink, and the speed controller of the PMSM drive is executed in ModelSim. Finally, the co-simulation results validate the effectiveness of the proposed algorithm based speed control system

10 kW Optimization of grid-connected wind power system and its application in Xiamen

Coastal areas not only have large annual average wind speed, but also have more days of strong winds in a year. Xiamen >8 gale days, 22.4 days a year, so it is very suitable for wind power generation. This design is 10 kW wind grid-connected power generation system, each branch is composed of permanent magnet synchronous motor, rectifier, boost module, inverter and filter, 20 groups are used in parallel to form 10 kW system. Choose a single permanent magnet synchronous wind turbine power of 500 W, need 20. System DC voltage :12 V, when the power is fixed, the proper lifting of DC voltage is helpful to reduce the current, thus preventing the IGBT from causing device damage due to overcurrent. A two-dimensional fuzzy controller is used to select the outer loop error and error differential signal as input variables. In order to verify the correctness of fuzzy adaptive PI control strategy, a system simulation model is built.

WITHDRAWN: A novel methodology to capture the maximum power from variable speed wind turbines using fuzzy proportional integral Controllers, modified PSO-GSA algorithm

This article provides a modified technique for controlling generator torque efficiently in wind turbines (WT). The generator torque is generally used at low wind speeds to obtain extreme power. In this study, we introduce a method for torque of the WT generator is controlled by using a fuzzy proportional integral controller (FPI). To upsurge the PI gain, by using a radial base function neural network (RBF-NN). And another hand we conducted the optimal dataset for training this neural network has been delivered by the techniques of modified procedure of gravity search algorithm and particle swarm optimization (GSA-PSO) algorithm. Thus, the benefits of enhanced technique performance and the reliability of the FPI can be completely utilized in the control course. By showing the simulation of WT experiments with help of Matlab, the performance of a modified GSA-PSO based FPI controller to meet the high accuracy and quick response requirements of permanent magnet direct drive (PMDD) is better than that of a PI controller, Without the use of modified PSO in situations where the wind speed changes abruptly.

Research on PMSM Speed Control System Based on Adaptive Fuzzy Control

PMSM servo system has nonlinear, parameter time-varying, load disturbance and other issues. In the face of these problems, traditional PI control strategies often fail to achieve ideal parameter tracking and load immunity, showing a large degree of limitations. Aiming at this kind of problem, this paper designs a fuzzy PI control method combining PI control and fuzzy control, and uses the vector rotation control method of current speed double closed loop to drive the permanent magnet synchronous motor for control. Finally, the traditional PI control system and fuzzy PI control system simulation model are built in Matlab/Simulink environment. The simulations were carried out in three cases of high speed, medium speed and low speed, and the speed and current waveforms of the two control methods were observed. The simulation results show that the fuzzy PI control system can increase the response rate, reduce the overshoot of the speed and reduce the current fluctuation in the full speed range. The robustness of the system is improved, the adaptability of the system to load changes is enhanced, and the correctness of the theoretical analysis is verified.

Comparison the Performance of the Dynamic Voltage Restorer Based on PI, Fuzzy Logic, and Fuzzy Neural Controller

The Dynamic Voltage Restorer (DVR) is one of the most efficient and effective custom power devices in protecting the sensitive equipment against voltage sag and voltage harmonics due to; lower cost, smaller size and dynamic response. The inverter is the core of the DVR and it directly affects the performance of the DVR, incorrect injection or delay in the process would be dangerous to sensitive loads. The major functions of the DVR controller are, detection of voltage disturbances events in the system, calculation of the compensating voltage and generation the reference signal for the PWM to trigger the voltage source inverter. PI controller and fuzzy logic controller has been compared with the proposed fuzzy neural optimized fuzzy logic controller in correcting the sag problems and mitigating the harmonics distortion with linear and non-linear loads. Fuzzy Neural optimized Fuzzy Logic controller is the most efficient in improving the performance of the Dynamic Voltage Restorer in compensating any kind of voltage variations and reducing the voltage Total Harmonic Distortion (THD) by enhancing an injection capability of the DVR which is highly influenced by a control algorithm employed. The system is simulated in MATLAB and results confirm the validity and feasibility.

PI-like fuzzy based synchronous SEPIC converter control for PV-fed small scale irrigation DC pump

For off-grid, standalone solar-fed water pumping has become a very viable option for small householder farmers. Appropriate configuration and control to suit this specific application are required. Buck, boost, and buck-boost converters are used to ensure impedance adaption between the solar PV generation and the load. However, these converters have switching harmonic problems. This problem is solved by the use of a single-ended primary inductor converter. Thus, a single-ended primary inductor converter is designed to overcome these drawbacks. Therefore, the objective of this paper is to design a single-ended primary inductive converter with a PI-like fuzzy controller. In this paper, synchronous SEPIC converter with PI-like fuzzy controller for PV-fed pumping system is modeled and designed. The system performance at different input conditions is evaluated. PI and PI-like fuzzy controllers have been compared using MATLAB/SIMULINK. PI-type fuzzy controller is less sensitive to input parameters variation than PI due to auto-tuning capability. Less than 2% output variation is recorded between 200 and 1000 W/m2 irradiance. This show that output voltage is less sensitive to the input solar radiation with this SEPIC converter control. The steady-state result obtained in speed and flow rate were 141.4 rpm and 1.56 l/s, respectively, and the voltage error was 1.4 V. Thus, PI-like fuzzy controller was used to reduce the steady-state error. The results obtained with PI-like fuzzy controller in speed and flow rate were 143.6 rpm and 1.624 l/s at 6 m head, respectively. The voltage error is 0.2 V which is less than the PI converter error (1.4 V).

Bi-directional power flow control with improved power quality using intelligent controller for AC-DC coupled hybrid micro-grid system

Grid connected renewable sources are affected by harmonic distortion due to non-linear power electronics interfaces. Depending upon the nature of the load, many conversion stages are incorporated in the micro-grid which leads to increase in the losses. Therefore, in this paper, the AC-DC coupled hybrid micro-grid system is presented in which AC renewable sources and AC loads are connected to AC sub-grid and DC renewable sources and DC loads are connected to DC sub-grid. The shunt active power filter based 3φ 4-leg bi-directional intermediate converter using d-q load current technique is proposed to achieve the power flow between AC and DC sub-grids. The MATLAB simulation is carried out, and the performance of the proposed system is analysed using the d-q load current technique based fuzzy logic and PI controller. The obtained results demonstrate that the overall system performance is improved with the d-q load current technique based fuzzy logic controller.

An intelligent fuzzy PI controller based 33 level switched capacitor multilevel inverter for PMSM drives

This paper presents an intelligent Fuzzy PI controller based switched capacitor 33 level multilevel inverter for PMSM Drives and the advantages of proposed SCMLI is proved. Compared to this suggested topology, the conventional MLI topology is compared with an indifferent viewpoint, such as the number of switches needed, output voltage levels and power supply. In order to further improve torque ripple, anti-interference capability and speed response, a new fuzzy PI vector speed control system with an adaptable proportion factor familiar by the RBF neural network must be created. The proposed design is implemented in MATLAB/ Simulink and the performance is improved for proposed circuit is achieved with experimental findings.

Performance optimization of doubly-fed induction generator (DFIG) equipped variable-speed wind energy turbines by using three-level converter with adaptive fuzzy PI control system

The present paper aims at optimizing the performance of a Doubly Fed Induction Generator (DFIG) equipped variable-speed wind energy turbine in utility grid-connected mode. Since maximum power extraction and output power quality improvement are considered the main challenges for enormous scale variable-speed wind turbines to meet the worldwide demand for clean energy, this work has two contributions; the first concerns the use of the three-level converters to upgrade the output power quality of the wind energy turbine through reducing the total harmonic distortion (THD) of the currents delivered to the power grid, whereas the second contribution intends to design an adaptive proportional-integral (PI) control system for the rotor side converter (RSC) control. The proposed adaptive PI control system is designed by combining the intelligent and adaptive nature of fuzzy logic control (FLC) and the simpleness of the PI controller framework to effectively optimize the DFIG wind energy turbine performance. In the proposed control system, the PI controller's gains are adjusted in real-time by a supervisory system based on FLC according to the wind turbine running conditions. The adopted control scheme to controlling the RSC comprises two cascaded regulation loops for reaching the maximum power point tracking (MPPT), that intends to extract obtainable maximum power of the wind energy turbine. The internal regulation loop is applied to control the rotor current while the external regulation loop is employed to regulate the generator speed. To prove the efficiency of the three-level converter and performance of the proposed control system, simulation studies were performed utilizing MATLAB/Simulink software. The obtained results through simulation clearly show that research paper purposes are achieved and the performance optimization of the wind turbine is well done.

Multi-verse optimizer based Fuzzy-PI controller for robust frequency regulation in thermal-hydro power system

This study presents a frequency regulation scheme using a fuzzy-based proportional-integral (FUZZY-PI) controller for two areas non-reheat thermal-hydro power system. Optimal tuning of controller parameters is achieved through a newly established metaheuristic algorithm called Multi-Verse Optimizer (MVO) algorithm. The superiority of the proposed controller has been proven by comparing it with recently published control approaches. The different figure of merits is used to evaluate the performance of the offered controller. The attained results confirm the effectiveness of the designed controller for studied power systems.

Voltage regulation of soft switched interleaved boost converter using fuzzy proportional integral controller

This paper discusses about a fuzzy PI controlled three-stage soft switched interleaved boost converter with improved switching method. The proposed fuzzy PI controller has been evaluated against with proportional integral controller. The proposed fuzzy PI controlled soft switched interleaved boost converter model has been developed and tested in MATLAB/SIMULINK environment. Performance of the designed controller is tested with different loading constraints and step change in reference voltage conditions. For effective comparisons, four performance parameters are taken for analysis such as integral of time multiplied absolute error, integral of squared error, integral of absolute error, and settling time. From these simulation results, fuzzy PI controlled soft switched interleaved boost controller has better performance than PI controlled soft switched interleaved boost converter. Experimental verification also conducted to check effectiveness of the proposed fuzzy PI controlled soft switched interleaved boost converter.

Three-level (NPC) shunt active power filter based on fuzzy logic and fractional-order PI controller

In this paper, a three-level neutral point clamped (NPC) shunt active power filter is proposed which injects into the network a current equal to that absorbed by the polluting load, but opposed to the phase. Thus, it is designed to prevent current disrupters of pollutants to flow through the impedance of the network making the sinusoidal network side current. The three-level neutral-point-clamped (NPC) inverter hysteresis-based control shunt active power filter offers enormous advantages compared to the two-level inverters. The regulation and the stability of the DC voltage across capacitor of the power supply filter during transient states and under various operating conditions is ensured by fuzzy logic controller and then by a fractional order proportional integral (PI) controller. A comparative study was carried out and the comparison criteria are the total harmonic distortion (THD) in the current line and the stability of the voltage during the load variation. The obtained results showed the efficiency of the proposed shunt active filter based on a three-level inverter (NPC) using a fractional order controller.

A Fuzzy Adaptative Backstepping Control Strategy for Marine Current Turbine under Disturbances and Uncertainties

Marine current energy is attracting more and more attention in the world as a reliable and highly predictable energy resource. However, conventional proportional integral (PI) control will be sensitive to the numerous challenges that exist in a marine current turbine system (MCTs) such as marine current disturbance, torque disturbance and other uncertain parameters. This paper proposes a fuzzy adaptive backstepping control (F-A-BC) approach for a marine current turbine system. The proposed F-A-BC strategy consisted of two parts. First, an adaptive backstepping control approach with the compensation of disturbance and uncertainty was designed to improve anti-interference of the MCT so that the maximum power point tracking (MPPT) was realized. Then, a fuzzy logic control approach was combined to adjust parameters of an adaptive backstepping control approach in real time. The effectiveness of the proposed controller was verified by the simulation of a direct-drive marine current turbine system. The simulation results showed that the F-A-BC has better anti-interference ability and faster convergence compared to the adaptive backstepping control, sliding mode control and fuzzy PI control strategies under disturbances. The error percentage of rotor speed could be reduced by 3.5% under swell effect compared to the conventional controller. Moreover, the robustness of the F-A-BC method under uncertainties was tested and analyzed. The simulation results also indicated that the proposed approach could slightly improve the power extraction capability of the MCTs under variable marine current speed.

Generation control of isolated small hydro power plant by using DECSA optimized FPI controller

PurposeIn this work, generation control of an isolated small hydro plant (SHP) is demonstrated by applying optimal controllers in speed governor and hydraulic turbine system. A comparative analysis of application of fuzzy PI (FPI) and PID controller is conferred for generation control (both power and terminal voltage) of an SHP. The controllers are designed optimally by using crow search algorithm (CSA) and novel hybrid differential evolution crow search algorithm (DECSA). The purpose of this paper is to settle the voltage and real power to improve the quality of the power.Design/methodology/approachIn this work, the controllers (PID and FPI) are implemented in speed governor and excitation system of SHP to regulate power and terminal voltage. Differential evolution and CSA are hybridized to enhance the performance of controller to refurbish the power and terminal voltage of SHP.FindingsThe proposed DECSA algorithm is applied to solve ten benchmark functions, and the effectiveness of DECSA algorithm over CSA and DE is demonstrated in terms of best value, mean and standard deviation. CSA and DECSA algorithms optimized controllers (PID and FPI) are used to design SHP with the capability to contribute power and voltage of better quality. The comparative analysis to substantiate the competence of DECSA algorithm and FPI controller is demonstrated in terms of statistical measures of power and voltage of SHP. Robustness analysis is performed by varying all system parameters to prove the effectiveness of the proposed controller.Originality/valueThe proposed algorithm and FPI controller are applied individually to improve the quality of the power of SHP. DE, CSA and DECSA algorithms are implemented to solve benchmark equations. The solutions of all benchmark equations contributed by DECSA algorithm is converged rapidly and having minimum statistical measures as compared to DE and CSA algorithms. The DECSA algorithm and FPI controller are proposed with superior competence to enhance the generator performances by conceding undershoot, overshoot and settling time of power and terminal voltage. DECSA-based FPI controller contributes a noticeable improvement of the performances over other approaches.

Advanced wavelet transform based shunt hybrid active filter in PV integrated power distribution system for power quality enhancement

Power quality (PQ) issues are significant in inverter-fed distributed generation system with non-linear loads which degrades the performance of the consumer equipments and the power system itself. Therefore, this work presents an improved photovoltaic (PV) coupled hybrid filter for the improvement in PQ in an active distribution system. A shunt hybrid active filter (SHAF) integrated with PV is designed with the help of an advanced signal processing approach called dual tree-complex wavelet transform (DT-CWT) for extracting the frequency information in the voltage and current due to the PQ disturbances. For calculating the reference current and switching signals, zero attracting least mean square (ZA-LMS) is considered in the hybrid filter and adaptive perturb and observe-fuzzy algorithm is proposed for maximum power point tracking in PV system to improve the performance under different operating conditions. The system model using the proposed technique is developed in MATLAB/Simulink and real-time experimental set up using two different controllers, i.e. the conventional proportional-integral (PI) and fuzzy-PI controllers. The results on comparison illustrates better performance of the proposed ZA-LMS and DT-CWT with fuzzy-PI based SHAF technique for PQ improvements with respect to that of LMS/normalised LMS with PI/fuzzy-PI based SHAF under different operating scenarios.