PI Fuzzy Logic Controller Research Articles

Fuzzy Based Quick Acting DC Link Voltage Controller for Three Phases of D-Statcom Connected to the Microgrid

The microgrid systems are the combinations of solar photovoltaic, wind energy, fuel cell and battery systems, as well as conventional generators for backup. The micro grid system barriers that are encountered for their integration to the network. In power systems, voltage stability and power quality are major problems. Due to fluctuations in dc link voltage, changes in load may have an effect on the compensation. This work offers a fuzzy logic-based supervisory approach to enhance the performance of the dc link transient. The controllers employ proportional and integral gain changes with fuzzy logic PI controllers integrated with distribution static synchronous compensator (D-STATCOM). These changes occur in the transient response phase right after a load fluctuation. In order to verify the suggested controller, mathematical equations are given to compute the gains of the traditional controller using fuzzy-logic PI fast-acting dc-link voltage controllers for obtaining similar quick transient reaction. Fuzzy logic PI controller enhancements that employ greater sampling during the transient period and expert knowledge of system behavior enhance the controller's performance. Compared to a standard PI controller, a dc link error reduces the capacitor voltage during a load shift. Utilizing the suggested method and the outcomes of MATLAB simulations, it will be demonstrated that efficiency and the voltage's quick settling time.

An Improved Power Quality in a Renewable Energy-based Microgrid System Using Adaptive Hybrid UPQC Control Strategy

Due to its ability to integrate renewable energy, improve energy efficiency, and fortify the power system's resilience, microgrids are widely used as regional energy systems. But these advantages do have certain drawbacks in terms of control and Power Quality (PQ). In order to guarantee the proper operation of equipment that is connected and the system's general health, PQ is crucial in microgrids. For microgrids to operate successfully, governing stratagems in concurrence with front-line power electronics devices bid a firm context to knob PQ challenges like Voltage Sag and Swell, Source/Grid current harmonics, Voltage imbalances, Active and Reactive power compensation etc. Multifunctional systems that can integrate clean energy generation and as well as enhance PQ are necessary to meet the demands of complex loads that have the capability of operating in the situation of an unavailable network grid and power electronics devices, which necessitates the need for clean energy. Hence, this paper provides enactment of an adaptive hybrid control strategy based on an Adaptive Leaky Least Mean Square (AL_LMS) algorithm combined with Fuzzy Logic (FL) to the Unified Power Quality Conditioner (UPQC) in a Solar-PV energy based Microgrid system in improving microgrid power quality. The concert of UPQC is assessed by the conventional PI controller and Fuzzy Logic control with MATLAB/SIMULINK software platform, simulation results are conversed with proportionate studies in improving the PQ by minimizing Total Harmonic Distortion (THD), the Voltage Sag & Swell and the result comparison shows the effectiveness of the Fuzzy Logic in coordination with the AL_LMS algorithm resulting improved power quality within the IEEE Power Quality-519 Standards.

Development of Powered Semi-Active Ankle-Foot Prosthetic with Fuzzy Logic-PI Controller

Development of Powered Semi-Active Ankle-Foot Prosthetic with Fuzzy Logic-PI Controller

Fuzzy Logic PI controller based Direct Torque control of a Self-Excited Induction Generator through a three-level Rectifier

The main goal of this work is to control the terminal voltage of a Self-excitation induction generator (SEIG) that supplies autonomous load and is driven by a variable speed wind turbine. More advanced strategies of control have been suggested and applied these through a two-level converter. However, in this paper, we propose to study a modified DTC approach which based on the use of three-level converter (NPC structure) and instead of the traditional PI controller, we use a PI fuzzy controller to reduce torque and flux ripples, the induction generator's stator flux and electromagnetic torque are controlled using voltage space vector selection. The proposed control strategy has to maintain constant DC bus voltage regardless of load or wind speed variations. Finally, it should be noted that this control accounts for the induction generator's magnetic saturation phenomenon.

Fractional fuzzy PI controller using particle swarm optimization to improve power factor by boost converter

The power circuit of AC voltage controller capable of operating at a leading, lagging, and unity power factor is studied by a lot of researchers in the literature. Circuits working with high switching frequency are known as power factor correctors (PFCs). The single-phase boost converter has become the most popular topology for power factor correction (PFC) in general purpose power supplies. Power factor correction circuit provides conventional benefits to electric power systems. The benefits are the reduction of power factor penalty and utility bill and power loss. Therefore, a boost converter power factor correction scheme is presented in this paper. A PI, fuzzy logic PI and fractional order PI (FOPI) controllers are used to fix an active shaping of input current of the circuit and to improve the power factor. The controller parameters (coefficients) are optimized using the Particle Swarm Optimization (PSO) algorithm. Average current mode control (ACMC) method is used in the circuit. The converter circuit consists of a single-phase bridge rectifier, boost converter, transformer and load. A mathematical model of the plant is required to design the PI controller. A model for power factor correction circuit is formed in MATLAB/Simulink toolbox and a filter is designed to reduce THD value. The proposed model is simulated using a combination of PI, fuzzy logic and FOPI controllers. The control scheme is applied to 600 Watt PFC boost converter to get 400 Volt DC output voltage and 0.99 power factor. The input voltage is 230 VRMS with 50 Hz. The combination of FOPI and PI controller has the best solution to control the power factor according to PI and fuzzy controllers.

Hybrid Control and Energy Management of a Residential System Integrating Vehicle-to-Home Technology

Electric vehicles (EV) and photovoltaic (PV) systems are increasingly becoming environmentally friendly and more affordable solutions for consumers. This article discusses the integration of PV and EV in a residential system to meet the requirements of residential loads taking into account the PV supplied power, availability and the state of charge (SOC) of EVs. A hybrid control model has been proposed to control the residential system. The combined PI-Fuzzy logic controller is employed to control the buck-boost bi-directional converter. The DC-AC grid-side converter is controlled by the ADRC controller. The effectiveness of PI-Fuzzy logic controller in reducing voltage and current ripples and ADRC controller in rejecting disturbances is demonstrated in each case. A rule-based energy management strategy has been proposed to control the flow of energy between the components of the residential system. The suggested energy management system (EMS) covers every scenario that might occur. Whether the EV is linked to the home or not, and also takes into account the owner using the EV in an emergency situation. The EV operates in two modes, Home-to-Vehicle (H2V) mode and Vehicle-to-Home (V2H) mode, depending on the power produced by the PV and the conditions related to the EV. All possible scenarios are tested and validated. The simulation results show that the proposed EMS is a reliable solution that can reduce the power grid intervention.

Ensuring energy balance for sudden demand changes in smart grids

With the increasing diversity in the use of electrical energy and the inclusion of renewable electricity power plants in the system, more efficient and more controllable electrical power systems are provided by smart grid technologies. Load balance based on pricing in electrical power systems; It is a strategy that takes into account customer demands, enables customers to use electrical energy at the most attractive price, and provides suppliers with the desired profit, that is, in summary, it coordinates the efficient operation of energy systems. In this study; While load balance is created with smart grid technology, demand-supply-price balance is achieved by using an optimum Fuzzy Logic PI controller within a closed-loop electric power control system model. Within the scope of the study, the simulation results obtained by applying 6 different demand scenarios to the power system model consisting of different types of generation resources were given graphically and analyzed. The different demand scenarios applied include difficult demand conditions such as possible sudden increase or decreases in demand in the electrical power system.

A robust fuzzy logic PI controller for solar system battery charging

This article discusses a design of a photovoltaic (PV) system that allow charging a battery under variable climatic circumstances. The system under study is composed of two DC-DC converters a boost and Buck converter. The first one is used to extract the maximum power from the PV array through a novel variable step size P&O based MPPT offering a high tracking accuracy compared to classical approaches such PO and INC. The second converters aim at regulating the output voltage and current that feeds the battery using a robust optimal PI (O-PI) which has a faster time response and high accuracy compared to classical PI and PID controllers. The overall system and thecontrol strategies are tested and validated in MATLAB/Simulink environment. The simulations results show the effectiveness and the robustness of the system.

Sugeno-Type Fuzzy Ontology PI Controller for Proportional Electrohydraulic System

In this paper, an ontology representation of the Sougeno-type PI Fuzzy Logic Controller (FLC) is presented. The proposed controller is an extension of the Fuzzy Ontology Controller (FOC), where the new fuzzy annotations relevant to Sougeno-type fuzzy control are added to the ontology. The design of the fuzzy ontology is carried out in Protégé and it is hosted on a remote server in the Virtuoso database. Simulation results for the proportional electrohydraulic system are presented and compared to the PI and the SMC controller. The simulation results show that the proposed concept works, and achieves similar results to the PI controller. Experimental results are carried out on a proportional electrohydraulic system. Results show good tracking capabilities despite slow network communication between the server and experimental setup.

Optimizing BLDC motor drive performance using particle swarm algorithm-tuned fuzzy logic controller

A brushless DC (BLDC) motor is synchronous motor with trapezoidal/square wave counter-electromotive force, which is a typical example of highly coupled nonlinear systems. In industrial control, BLDC motor drive usually uses proportional–integral (PI) controller to control the speed, but it is very difficult to adjust the scale factors. In this study, we present a particle swarm algorithm-tuned fuzzy logic-PI (PF-PI) controller applied to the speed control system. The objective of this paper is to optimally tune the PI controller parameters to obtain the best drive response. The scale factors are optimized using particle swarm optimized-PI (P-PI) controller and PF-PI controller. The three performance indicators integral time absolute error (ITAE), integral time square error (ITSE) and integral square error (ISE) are used to measure the effectiveness of PF-PI controller optimization. The results show that the optimal torque ripple and speed response curves are obtained by using ITAE as the performance indicator. The conclusions demonstrate that the proposed method provides superior dynamic performance for BLDC motor.HighlightsIn terms of research content, we propose a new PF-PI controller driven control system based on the traditional BLDC speed control system, and the applicability of three performance indicators on the controller is discussed.In terms of research method, we compare the no-load start, variable speed and sudden addition disturbance load start capabilities of P-PI controller and PF-PI controller, and verify the fast and robustness of PF-PI controller.In the research significance, the PI controller structure is improved and the dynamic performance of BLDC speed control system is enhanced.

Performance Analysis of Buck Boost and Cuk converters for Solar PV Applications using PI controller and Fuzzy Logic Controller

Abstract: In this paper, analysis of DC-DC converters Buck-Boost and Cuk converter by using PI Controller and Fuzzy Logic controller. These converters are mainly used in solar PV applications and it is explained. In this paper mainly MATLAB/ Simulink software is used for the compare the performance of both. the design is mainly compared with the proportional integrated controller versus FLC. The main objective of this work to reduce the overshoot of these types of converters. The buck boost and cuk converter are simulated for different Loads and their output voltage is settle at desired voltage The performance of buck-boost and cuk converter are simulated using Matlab/Simulink and comparison study is performed. The complete control system has been developed analysed and validation by the simulation. Keywords: Buck-Boost Converter, Cuk Converter, MATLAB/ Simulink, Solar PV and Fuzzy Logic Converter

Fuzzy based MPPT Control System in Grid Connected Solar Plant

The increase in demand for the electricity system is increasing. Thus, enviromentally friendly technologies such as new and renewable energy are needed, one of which is a power plant with Photovoltaic as the main component. Solar power plant has enviromentally friendly properties. The design of this solar power plant uses Fuzzy Logic Controller and PI Controller methods, where both methods are used to find the maximum power peak point used for fast charges and MPPT, which is simulted using MATLAB/Simulink. The things presented in developing the generating system using these two methods are solar radiation intensity, temperature and Photovoltaic module. The model developed will make it possible to examine the characteristics of solar power plant and predict the amount of energy generated by solar panels in a particular location and compare the effectiveness of Fuzzy Logic and PI methods. The results shows that Fuzzy method produces a boost converter output voltage in the range of 600 V with result that are still not good and less stable, but the irradiation of 100 W/m2 voltage is stable, while the boost converter output voltage controller by the PI method is very good and stable in all conditions. Radiation and voltage are also in the range of 600 V.

Increase Stability and Efficiency in PV-Battery-Grid Systems Using PSO Algorithm

In this article, the meta-heuristic algorithm PSO with PI fuzzy logic controller is proposed to develop a new control strategy of bidirectional converter (CSBC), in order to improve the stability and increase the efficiency of energy flow exchange in grid-connected photovoltaic generator (PVG) Battery hybrid system. The proposed command aims to satisfy the DC Motor load demand, manages the power flows from different parts, injects surplus energy into the grid as and when need, ensure charge-discharge battery operation even under the fluctuating condition of power generation, and stabilize the DC bus voltage. This new control has been placed in the network topology, which consists of a PVG Photovoltaic Generator, grid-connected DC/AC converter, storage battery and DC motor load. A bidirectional buck-boost converter is used for optimum exploit of power from PVG along with battery charging/discharging control, and for feeding DC motor load. The effectiveness of the proposed control scheme is demonstrated by using MATLAB / Simulink program. The results obtained, show that the proposed control provided the system with the stability of Vdc voltage, and contributed to improving the speed produced by the DC motor load. The results have been compared with the conventional control.

Steering Control in Electric Power Steering Autonomous Vehicle Using Type-2 Fuzzy Logic Control and PI Control

The steering system in autonomous vehicles is an essential issue that must be addressed. Appropriate control will result in a smooth and risk-free steering system. Compared to other types of controls, type-2 fuzzy logic control has the advantage of dealing with uncertain inputs, which are common in autonomous vehicles. This paper proposes a novel method for the steering control of autonomous vehicles based on type-2 fuzzy logic control combined with PI control. The primary control, type-2 fuzzy logic control, has three inputs—distance, navigation, and speed. The fuzzy system’s output is the steering angle value. This was used as input for the secondary control, PI control. This control is in charge of adjusting the motor’s position as a manifestation of the steering angle. The study results applied to the EPS system of autonomous vehicles revealed that type-2 fuzzy logic control and PI control produced better and smoother control than type-1 fuzzy logic control and PI. The slightest disturbance in the type-1 fuzzy logic control showed a significant change in steering, while this did not occur in the type-2 fuzzy logic control. The results indicate that type-2 fuzzy logic control and PI control could be used for autonomous vehicles by maintaining the comfort and safety of the users.

Fuzzy Logic Decoupling Control of Real and Reactive Power in Grid-Connected Photovoltaic Power System based a Seven Levels Inverter Linked to a Three-Stage Boost Circuit

ABSTRACT The paper presents a detailed modelling, simulation, and control of the real and reactive power flows in the Grid-Connected Photovoltaic Power system (GCPV) based on seven-phase voltage source inverter linked to a three-stage boost circuit interfacing a photovoltaic (PV) generation system to the power grid. Synchronisation of the inverter and grid AC waveforms is achieved using a phase-locked-loop (PLL) circuit. An effective decoupling strategy based on fuzzy logic controllers (DFLC) is designed to eliminate the interaction between the two current components. The DC-link voltage is controlled using a closed loop scheme based on a clamping bridge and an adaptive fuzzy logic PI controller (AFLC-PI). The overall model is implemented in Matlab and Simulink/SimPowerSystems toolboxes. Simulations results with the PV system operating with real irradiance data are presented to demonstrate the performance of the proposed decoupling and control strategies under different conditions of the power grid.

Analogous Research of Classical PI Controller and Fuzzy Logic Controller to Control the Speed of D.C. Servo Motor

Servo motors are widely used in several fields such as industrial, electronics and robotics etc. The precise positioning & speed control of servo motor is compulsory for desired result and output. In this study, the speed control of dc servo motor is compared utilizing two different controllers. First is a classical PI controller while the second one is a fuzzy logic controller (FLC). PI controller and FLC both can be utilized for controlling the speed of servo motor. Both techniques provide good results but the fast response for the proposed calculation is achieved by the fuzzy logic controller. MATLAB/SIMULINK provide the conventional tool to analyze the model precisely so that the performance of servo motor is satisfactory. The performance of both controllers is compared and analyzed on different parameters such as speed, current for DC Servo Motor.

Comparison of T-Type Converter and NPC for the Wind Turbine Based on Doubly-Fed Induction Generator

A three-phase T-type converter topology proposes for wind turbine based on doubly fed induction generator (DFIG). The proposed converter consists of only twelve power switches without flying capacitors or any clamping diodes. The proposed system is implemented to grid side converter of wind turbine. Fuzzy logic controllers are more widely used in wind turbines compared to traditional control systems. Fuzzy logic PI controller has been applied to T-type and the conventional neutral-point clamped (NPC) converters control circuits. Total harmonic distortion (THD) value of current of presented system is measured as 1.76%. Also, DC-link voltage utilization can be maintained. Comparisons are conducted with T- type converter and a 3L-NPC) method under same operation conditions. The proposed scheme has been carried out to verify in simulation results.

Indirect Effective Controlled Split Source Inverter-Based Parallel Active Power Filter for Enhancing Power Quality

The existing solutions for reducing total harmonic distortion (THD) using different control algorithms in shunt active power filters (SAPFs) are complex. This work proposes a split source inverter (SSI)-based SAPF for improving the power quality in a nonlinear load system. The advantage of the SSI topology is that it is of a single stage boost inverter with an inductor and capacitor where the conventional two stages with an intermediate DC-DC conversion stage is discarded. This research proposes inventive control schemes for SAPF having two control loops; the outer control loop regulates the DC link voltage whereas the inner current loop shapes the source current profile. The control mechanism implemented here is an effective, less complex, indirect scheme compared to the existing time domain control algorithms. Here, an intelligent fuzzy logic control regulates the DC link voltage which facilitates reference current generation for the current control scheme. The simulation of the said system was carried out in a MATLAB/Simulink environment. The simulations were carried out for different load conditions (RL and RC) using a fuzzy logic controller (FLC) and PI controllers in the outer loop (voltage control) and hysteresis current controller (HCC) and sinusoidal pulse width modulation (SPWM) in the inner loop (current control). The simulation results were extracted for dynamic load conditions and the results demonstrated that the THD can be reduced to 0.76% using a combination of SPWM and FLC. Therefore, the proposed system proved to be effective and viable for reducing THD. This system would be highly applicable for renewable energy power generation such as Photovoltaic (PV) and Fuel cell (FC).

PI Fuzzy Controller of Synchronous Boost Converter for Drug Storage Thermoelectric Cooler

Medicines should be stored in a room at a suitable temperature if the inappropriate affect the quality of the drug. Therefore we need a control that can control the temperature in the room so that it is constant in accordance with the rules for room temperature in drug storage, which is 25 degrees Celsius. The following paperwork presents a simulation controller between PI controller and PI-Fuzzy logic controller in adjusting the voltage to match the set of point. Where the fuzzy logic controller automatically searches for the Kp value so that the voltage output of the converter match the desired set of point. Then the converter used is synchronoust boost converter as voltage regulator and peltier as a DC load which functions as a cooler. in this research, the system using PI controller was able to adjust the voltage to match the set point with Kp is 0.14089 and Ki is 124.6738 then settling time is 0.016 s. While the system using PI-Fuzzy logic controller,it was able to adjust the voltage to match the set point with Kp is 0.08112 and Ki is 125.6738 then settling time is 0.014 s.

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.