Fuzzy Logic Control Technique Research Articles

Enhancing photovoltaic system maximum power point tracking with fuzzy logic-based perturb and observe method

Photovoltaic systems have emerged as a promising energy resource that caters to the future needs of society, owing to their renewable, inexhaustible, and cost-free nature. The power output of these systems relies on solar cell radiation and temperature. In order to mitigate the dependence on atmospheric conditions and enhance power tracking, a conventional approach has been improved by integrating various methods. To optimize the generation of electricity from solar systems, the maximum power point tracking (MPPT) technique is employed. To overcome limitations such as steady-state voltage oscillations and improve transient response, two traditional MPPT methods, namely fuzzy logic controller (FLC) and perturb and observe (P&O), have been modified. This research paper aims to simulate and validate the step size of the proposed modified P&O and FLC techniques within the MPPT algorithm using MATLAB/Simulink for efficient power tracking in photovoltaic systems.

An Improved Perturb and Observe MPPT for Photovoltaic Systems using Fuzzy Step Size

Photovoltaic (PV) systems have emerged as a promising energy resource that caters to the future needs of society, owing to their renewable, inexhaustible, and cost-free nature. The output power of these systems relies on solar cell radiation and temperature. To mitigate the dependence on atmospheric conditions and enhance power tracking, a conventional approach has been improved by integrating various methods. The Maximum Power Point Tracking (MPPT) algorithm is employed to optimize power extraction from PV systems. To overcome limitations such as steady-state voltage oscillations and improve transient response, two traditional MPPT methods, namely Perturb and Observe (P&O) and Fuzzy Logic Controller (FLC), have been modified. This research work aims to simulate and validate the fuzzy step size of the proposed modified P&O and FLC techniques within the MPPT algorithm using Matlab/Simulink™ for efficient power tracking in PV systems.

Nonlinear control of two fingers model for movement coordination

This research introduces an innovative methodology for the integrated modeling, simulation, and analysis of two fingers, with particular emphasis on their fundamental roles in everyday tasks. In this study, we provide two nonlinear control strategies, specifically Sliding Mode Control (SMC) and Feedback Linearization Control (FLC), to achieve accurate and stable finger movements. As mentioned earlier, the controllers are utilized in the context of a biomechanical model consisting of two fingers, each possessing two degrees of freedom. These controllers enable the coordination of flexion and extension movements. The research conducted in our study emphasizes the coordinated regulation of finger movements, enabling the achievement of flexion through the utilization of two nonlinear controllers. By implementing these sophisticated control mechanisms, we can effectively showcase our model’s fidelity in adhering to the physiological limitations inherent to human fingers in their natural state. In addition, the proposed controllers demonstrate sound mitigation of non-linearities, such as load variations, different velocities, positional changes, and damping forces. This approach presents several advantages, such as handling non-linearities, guaranteeing robustness, choosing suitable parameters, and conducting comparative analysis. In order to substantiate our findings, we develop the nonlinear model utilizing the MATLAB/Simulink software. The findings of our study demonstrate effective regulation and control of the two-finger model’s position. In our study, we were able to get flexion angles of [Formula: see text] rad and [Formula: see text] rad using the sliding mode control (SMC) technique, and flexion angles of [Formula: see text] rad and [Formula: see text] rad using the fuzzy logic control (FLC) technique, all within a time frame of 5 s. These results serve to illustrate the applicability and significance of our proposed methodology.

Design of PV, Battery, and Supercapacitor-Based Bidirectional DC-DC Converter Using Fuzzy Logic Controller for HESS in DC Microgrid

Renewable energy sources (RES) are becoming more popular globally as a reaction to critical energy concerns. Modern energy management technologies are used to maximize their efficiency while preserving the reliability of the grid. A hybrid energy storage system (HESS) connects to the DC microgrid through the bidirectional converter, allowing energy to be transferred among the battery and supercapacitor (SC). In this paper, a fuzzy logic control (FLC) technique is developed for PV-based DC microgrid systems that use both batteries and SCs. The proposed method uses the unbalanced energy from the battery pack to enhance the overall effectiveness of the HESS. The FLC approach is performed to validate under conditions of variable irradiance using MATLAB Simulink. When sudden changes in irradiance occur, the proposed FLC brings the voltage back to the desired level in terms of transient response like 33 ms settling times and 19% overshoot values. The results exhibit that the proposed method is more efficient in terms of time response, power output, increasing battery life, and ensuring a continuous supply of the PV system.

Control Techniques of the Modified Stator and Rotor Pole Shape in a 6/4 Switched Reluctance Motor: Effects on Torque Ripple Minimization

A switched reluctance motor (SRM) provides the advantages of simple and robust motor structure. But in switched reluctance motors (SRMs), as the result of the double ridged structure of motor, the torque vibrations and acoustic noise are relatively higher as against the sinusoidal machines. This study intends to minimize the torque ripple of a SRM. In machine’s design, new control approaches were employed by modifying the stator and rotor pole shapes in order to minimize the torque ripple in SRM. Moreover, by observing the performance of 6/4 SRM under steady-state conditions and at constant dwell angles for fan load, torque ripple (TR) analyses were performed. The driver was simulated for current control (CC), and control of sum of squared phase currents (SPC). Fuzzy Logic Controller (FLC) was also applied on speed loop in order to minimize torque ripple, and to improve the effective torque. In MATLAB/SIMULINK environment, the results are being discussed in detail. The FLC technique provided successful results in improving the effective torque ripple of SRM. The results of simulation were verified by the experimental results.

A new variable step fuzzy logic control technique for minimum emission point tracking of ship microgrid

A new variable step fuzzy logic control technique for minimum emission point tracking of ship microgrid

Fault tolerant control of two tanks system using gain-scheduled type-2 fuzzy sliding mode controller

To save the robustness of type 2 fuzzy logic control technique and to avoid the high energy consumption that represents the sliding mode control (SMC) technique control technique, without failing the performance of the system, we propose a new fault tolerant control method based on gain-scheduled sliding mode control with interval type 2 fuzzy logic (FTCGST2FSMC) applied to the hydraulic system (two tanks system) with an actuator fault. The proposed control scheme avoids a difficult modeling, due to the chatter effect of the SMC, guarantees the stability studied by Lyapunov with the robustness of the system. The gains of the control with the SMC controller are modified and changed by an adaptation with a technique based on type 2 fuzzy logic, used to improve the gains of the controller when the fault is added, the proposed FTCGST2FSMC controller has been compared with the sliding mode controller. The results obtained confirm the robustness and the performance of this method, in the presence of the actuator fault effect.

A single source five-level switched-capacitor based multilevel inverter with reduced device count

Nowadays, multilevel inverters (MLIs) are widely used for integration with renewable energy (RE) resources and in industrial applications. Among different RE sources, photovoltaic (PV) energy is generally used for the generation of power. For accumulating more power from PV systems, the Fuzzy Logic Controller (FLC) technique is used to trace the maximum power (MPP). The FLC computes the reference PV voltage guarantee to ensure optimal power transmission between the PV system and the MLI's connected load. In this paper, a novel 5L (five-level) PV-based switched-capacitor MLI topology (PV-SC-MLI) has been projected with the target of reducing the number of switches and boosting the input voltage without any bulky transformer. A selected harmonic elimination pulse width modulation technique (SHEPWM) based technique is used to remove the harmonic for 5L-PV-SC-MLI. The projected technique is appropriate for all levels of MLIs, including non-equal and equal DC sources. The SHEPWM technique is used to solve the non-linear transcendental equations and obtain the optimal values of switching angles. The obtained switching value is used to reduce the total harmonic distortion (THD) of 5L-PV-SC-MLI. The THD at the output voltage of proposed inverter has been obtained value is 8.72% without filter and with filter 4.20%, which lies within the limits of IEEE 519 standards.

An adaptive fuzzy logic control technique for LVRT enhancement of a grid-integrated DFIG-based wind energy conversion system

The fast improvement of wind energy conversion technology with optimization algorithms has recently received a lot of attention. However, their slow convergence speed, huge computational load, and low efficiency are the main drawbacks and to improve these disadvantages, a new adaptive fuzzy logic controller strategy is proposed to enhance the low voltage ride-through of the grid-connected doubly fed induction generator during severe grid faults. The rotor side converter and the grid side converter are controlled using an adaptive fuzzy logic controller topology under cascaded structure to improve the performance. The novel application of the ‘generalized variable step-size diffusion continuous mixed p-norm’ adaptive filtering algorithm is proposed to modify the calibrating factors of the fuzzy logic controllers at a rapid convergence speed with low normalized misalignment error. The proposed adaptive algorithm-based fuzzy logic controller has a better low voltage ride-through improvement capability than that of using the particle swarm optimization-based proportional-integral controller during severe grid disturbances. The convergence speed of the proposed adaptive filtering algorithm is compared to that of existing algorithms such as least mean fourth, least mean square, and continue mixed p-norm algorithms. In addition, a comparison is also made with different common optimization methods. The field-programmable gate array-based real-time experimental results are presented to validate the proposed adaptive control topology.

Modeling of MPPT-Based Solar Eco-System Using Fuzzy Logic Controller

Due to the depletion of fossil fuel reserves, renewable sources are now one of the most important sources of generating electricity. As far as reachable RE technologies are concerned, wind and photovoltaic sources offer the best potential, since they are omnipresent, free, and environmentally friendly. PV (photovoltaic) energy from the sun is an incredibly valuable renewable energy source on this planet. Because of varying climatic conditions, the energy generated directly from sunlight through PV panels is not steady. Environmental conditions are not every time favourable to generate electricity through solar. One of the solutions to this problem is to utilize optimization methods like P&O (Perturbation and Observation) with Maximum Power Point (MPPT) controllers. In this paper the main objective is to enhance the power capabilities of systems by utilizing maximum environmental conditions with Maximum Power Point Tracker to extract the maximum power from sunrays present in the environment. To improve the efficiency and accuracy of this MPPT tracking, a Fuzzy Logic Control technique has also been used in this paper. Simulations of the suggested method are carried out using MATLAB/Simulink.

Unlocking Energy Efficiency: Harnessing Fuzzy Logic Control for Lighting Systems

Energy efficiency is a critical concern for businesses and homeowners alike. Lighting systems account for a significant portion of energy usage, and optimizing these systems can lead to significant cost savings. One way to improve lighting system efficiency is by implementing fuzzy logic control (FLC) techniques. FLC is a type of control that uses imprecise data to make decisions, making it well-suited to the uncertain and dynamic environment of lighting systems. By using FLC, lighting systems can adjust brightness levels and schedules in response to occupancy and daylight levels, reducing energy consumption while maintaining a comfortable level of illumination. However, implementing FLC in lighting systems can be challenging, and requires careful design and tuning to ensure optimal performance. This article explores the benefits and challenges of using FLC in lighting systems and provides examples of successful implementations. Overall, the article highlights the potential of FLC as a valuable tool in achieving energy efficiency in lighting systems.

Identification and classification of faults using fuzzy logic controller in transmission line

This manuscript discusses the identification and categorization of faults in transmission network system with fuzzy logic controller (FLC) with high-speed digital protective relay, which can be used for real-time data analysis. The FLC uses signals for the extraction of original signals for multi-resolution analysis. The proposed FLC technique detects the fault occurrence based on fault index. The stoutness of technique is demonstrated on transmission line models under different fault situations on MATLAB Simulink platform for the post-fault current of all three phases the end of line. In the projected technique, different rules have been structured for phase and ground faults. Simulation has been carried out on various faults type to test the effectiveness of the method which is used for a power station of 400 kV voltages with a 300 km long line. The extensive simulation effort has been carried out to recognize and categorize the types of faults using projected methodology with higher efficiency. This method is appropriate for high-impedance faults carried out in high-voltage line. The result obtained from Simulation led to the conclusion that the presented work is quite robust for medium and long lines.

Efficient MPPT Controller for Solar PV System Using GWO-CS Optimized Fuzzy Logic Control and Conventional Incremental Conductance Technique

Efficient MPPT Controller for Solar PV System Using GWO-CS Optimized Fuzzy Logic Control and Conventional Incremental Conductance Technique

Modeling and Performance of a Buck Converter Based on ‘Fuzzy Logic Soft Computing Technique’ for Low Voltage Operations

This present paper details a ‘fuzzy logic soft computing technique’ of designing a controller for a buck converter operating at low voltages. The dc – dc buck converters find applications in solar energy technologies where they are used in solar control charging systems, battery charging systems, drones, in the automotive industry where there is integration of the engine and dc-dc motor drives resulting in hybrid electric drives or vehicle’s. Conventional controllers that is the proportional derivative control (pid) have dominated the control engineering field from the time of invention, however, these controllers present increased overshoot and a long time to achieve steady-state conditions. In this regard since fuzzy logic has intelligent capabilities, then a fuzzy logic soft computing-based controller is proposed in this paper. A mathematical analysis of the dc-dc buck design is also given and the modeling of the fuzzy logic control algorithms that avoids mathematical analysis is also discussed. Fuzzy control is one of the soft computing tools that consists of the observation made by people and their decision based on non-numerical information is also discussed. The performance analysis of the fuzzy controller is determined under constant load and variable decreasing voltage conditions. The analysis and simulation of the dynamic response in closed-loop frequency response are conducted in the Simulink platform in Matlab. The proposition of control is executed on a dc-dc step down converter for an input of 12V. This proposed fuzzy logic control technique provides a dc – dc buck converter system with increased overall operating efficiency and a very stable output.

Circulating Current Control of Phase-Shifted Carrier-Based Modular Multilevel Converter Fed by Fuel Cell Employing Fuzzy Logic Control Technique

The contribution of the modular multilevel converter (MMC) in integrating non-conventional energy sources into the grid is significant; the integration of fuel cells with distributed energy sources is especially prominent as they provide a constant voltage and current for constant load applications. Still, there is a high demand for a high-quality power conditioning unit since there is an occurrence of frequent power spikes. Further, the circulating current (CC) in phase legs is an inherent phenomenon of MMC that must be mitigated. Hence, this article proposed an MMC incorporating a fuzzy logic controller (FLC)-based technique to control the circulating currents. The fuzzy controller effectively reduced the harmonics of the CC in the dc-link system. In addition, phase-shifted carrier (PSC) modulation was employed for the MMC to improve the capacitor voltage balancing to maintain the constant input voltage. Moreover, a mathematical analysis of PSC modulation for MMC was performed to identify the PWM harmonic characteristics of the output voltage and the CC. The performance analysis of the proposed system was tested using the hardware in loop (HIL) simulation with the help of the real-time simulator OP-5700 to verify the feasibility.

Mathematical Modelling and Torque Ripple Waning in BLDC Motor Using Outgoing-Phase Current Discharge Hysteresis Controlled ANFIS Controller

This study focused on approaches for reducing torque ripples in Permanent Magnet Brushless Direct current motors (PMBLDC) to provide sophisticated performance and reliable machine drives for both industrial and consumer applications. Torque ripples are caused by current ripple, nonsinusoidal Back Electromotive Force (EMF), and cogging torque at the Brushless Direct Current Motor (BLDCM) output. Acoustic emissions are produced when the torque ripple creates vibrations in the mechanical system, which interacts with the motor housing and reduces the life span of the motor. The BLDC’s uses are limited due to these acoustic emissions. Proportional-Integral (PI), Fuzzy Logic Control (FLC), and Adaptive Neuro-Fuzzy Inference System (ANFIS) speed controller approaches were used to construct and analyze the mathematical model of the BLDC motor in the MATLAB environment. The Adaptive Neurofuzzy Inference System (ANFIS) speed control system has solved the shortcomings of the PI and Fuzzy Logic Control (FLC) techniques. Because of FLC interpolation and flexibility, ANFIS is one of the finest trade-offs between neural and fuzzy systems, allowing for smooth control. Model compactness, a smaller training set, and faster convergence are all benefits of the ANFIS approach over traditional feedforward NN. In this research proposal, a simple control approach based on outgoing phase current discharge hysteresis control (OGCDHC) with minimal torque ripple is presented.

Comparative Analysis of Torque Ripple for Direct Torque Control based Induction Motor Drive with different strategies

ABSTRACT Direct Torque Control (DTC) method is one of the most outstanding and proficient control techniques of the induction motor. The foremost drawback of DTC induction motor drive is high torque pulsation, variable frequency of inverter switching. The main reason of torque pulsation is torque and flux hysteresis band utilised in DTC. DTC method is utilising hysteresis comparators which produce high torque pulsation and unpredictable switching frequency. In this paper, torque ripple analysis of fuzzy logic controller (FLC) based Direct Torque Control (DTC) of three-phase induction motor drive has been discussed. The space vector pulse width modulation (SVPWM) based DTC technique, which operates with the regular switching frequency, helps to solve the fundamental issues of torque pulsation. In addition to this, literature proposes different solutions like a prediction scheme, fuzzy logic controller technique, global minimum torque ripple strategy, constant frequency torque controller (CFTC) Technique, optimal switching instant scheme, duty cycle control scheme, SVPWM DTC for torque ripple reduction. The fuzzy logic controller capabilities for DTC technique are applied with the induction motor (IM) drive for high-performance applications. The simulation results of Conventional DTC, SVPWM DTC, Carrier SVPWM DTC and FLC-DTC method for the induction motor are illustrated. Fuzzy-based DTC technique compared with CSVPWM DTC method and conventional DTC method are presented. The torque ripple of 7.4% for 5 HP induction motor is achieved by FLC-based DTC method. Hardware results for DTC induction motor drive are also demonstrated and discussed. This paper presents improvement in torque ripple reduction with the help of carrier space vector pulse width modulation (CSVPWM) and FLC-based DTC.

Application of fuzzy logic technique to track maximum power point in photovoltaic systems

The use of photovoltaic (PV) systems for generating electric power is increasing in our everyday lives but since the generated voltage and current vary non linearly it has been very difficult to trace the maximum power point (MPP) of the PV systems so to overcome with this problem many power tracking methods were introduced out of which fuzzy logic technique was found to be one of the easy and efficient maximum power point tracking (MPPT) method. In this paper, various MPPT algorithms are observed how they help in improving the efficiency of PV systems by adjusting the duty ratio of the power interface, and also understand why the fuzzy logic control (FLC) technique is preferred over other algorithms. The system was established using MATLAB/Simulink.

Mitigation of pulsed power load effect on power system using FLC-SMES

Integration of the pulsed power load (PPL) into the power system leads to high fluctuations in the frequency and voltage at the point of common coupling (PCC). This paper presents an effective solution to overcome these issues related to the PPL using the superconducting magnetic energy storage (SMES) system that has the features of high power capability and fast response. The fuzzy logic control technique (FLC) is employed to control the interfaced DC–DC chopper of the SMES to regulate the active power of the PCC and the state-of-charge (SOC) of the SMES coil. Two scenarios have been addressed with/without integrating the SMES conversion system. The on-time of the studied PPL is 0.1s with a total power of 5.7 MW, which is considered a high power demand in a short period. The simulation results based on MATLAB/Simulink show the high performance of the proposed system based on the FLC-SMES to minimize the voltage and frequency fluctuations during the operation of PPL.

Intelligent control of induction motor for photovoltaic water pumping system

This work aims to improve the performance of direct torque control (DTC) technique for induction motor based photovoltaic (PV) water pumping system (PVWPS). The innovative aspect of this work consists in introducing the adaptive fuzzy logic control and the fuzzy logic control techniques as alternative approaches to conventional DTC to control the PVWPS. To ensure a good operation of the PV array, a variable step size incremental conductance (VSS INC) is implemented. Simulation studies of the proposed topology based on intelligent approaches will be investigated using Matlab/Simulink under various operating conditions to validate the suitability of the proposed PVWPS. From the obtained results, the proposed control strategies appear to be very convenient for water pumping applications.Article HighlightsAn intelligent control based on the advanced techniques is proposed for PV water pumping system.An adaptive fuzzy logic PID approach and optimal fuzzy rules are proposed for better operation of PV system.The suggested PV water pumping system achieves better performance, in particular minimization of torque and flux ripples, reduction of torque overshoot and high dynamic response.