Advanced Fuzzy Logic Controller Research Articles

Optimizing full-scale MBR performance: A dual-phase approach for real-time air-scouring and permeate flow modifications

This study reports on an advanced fuzzy logic control system designed to optimize air-scour and permeate flow rates in membrane bioreactors, targeting enhanced energy efficiency and reduced fouling. Developed in two stages, the system integrates real-time monitoring of transmembrane pressure and permeability trends to adjust air-scour rates in response to fouling indicators. The initial simulations indicated potential for a 50 % reduction in air-scour rates, suggesting considerable energy savings. The second stage's refinements, based on empirical validations, yielded a more responsive system, albeit with more conservative operational adjustments for energy savings.Over eight months of full-scale testing, the advanced control system implemented in one of eight filtration lines exhibited lower fouling rates and maintained superior permeability values compared to the other lines. This performance translated into reduced chemical cleaning frequency, thereby affirming the system's efficiency in fouling management. These findings validate the application of fuzzy logic in MBR operations and offer a promising approach for energy-efficient and sustainable wastewater treatment.

Enhancing Energy-Efficient Water Pumping with Intelligent Control: A Comparative Study of Advanced Fuzzy Logic and PID Controllers on Simulink/MATLAB

Water resources are crucial for social and economic development, human needs, and food production. However, with water scarcity on the rise, minimizing waste during pumping is vital. Using DC motors for pumping offers a solution for sustainable and efficient water management. This study explores intelligent control strategies to enhance energy efficiency in water pumping systems, comparing Advanced Fuzzy Logic and PID Controllers through simulation. The research aims to optimize the control approach for water pumping operations, improving energy efficiency and system performance. Simulation results indicate that both controllers effectively regulate water pumping operations. The Advanced Fuzzy Logic Controller offer better response to setpoints, with minimal overshoot 0,7%, fast settling time 0.052 Seconds, Rise Time 0.048 Seconds, Time Peak 0.05 Seconds and no steady-state error, Compared to PID Controller with Overshoot 10%, Settling Time 0.23 Seconds, Rise Time 0.048 Seconds, Time Peak 0.078 Second and no steady-state error Moreover, the Advanced Fuzzy Logic Controller performs overall better performance in terms of energy efficiency and robustness compared to the PID controller. The findings suggest that the energy efficiency of water pumping systems can be significantly increased by utilizing Advanced Fuzzy Logic Controller approaches, specifically the Advanced Fuzzy Logic Controller. This study contributes to developing control methods for sustainable water management systems with potential uses in agriculture, irrigation, and water distribution.

Harmonics suppression in high-speed railway via single-phase traction converter with an LCL filter using fuzzy logic control strategy

Introduction. The railway Traction Power Supply System (TPSS) encounters a common challenge related to high-frequency harmonic resonance, especially when employing AC-DC-AC traction drive systems in high-speed trains. This resonance issue arises when the harmonic elements introduced by the traction AC-DC converter on the grid side of trains align with the innate resonance frequency of the TPSS. The novelty the proposed work focuses on the challenges associated with resonance elevation and high-frequency harmonics in high-speed trains, while simultaneously enhancing energy quality. This is achieved by integrating a pulse-width-modulated converter on the grid side with a single-phase configuration and incorporating an LCL filter. Methodology. In order to optimize the system’s efficiency, a robust control system is employed, taking advantage of the capabilities of a fuzzy logic controller (FLC). The choice of the FLC is justified by its straightforward design and reliability, emphasizing the dedication to precise control, as fuzzy logic excels in handling complex, nonlinear systems. Through the use of linguistic variables and heuristic reasoning, the FLC adjusts to dynamic changes in the system, demonstrating its efficacy in enhancing both transient and steady-state responses. Practical value. A grid-side LCL filter-based converter was meticulously designed and rigorously simulated using the MATLAB/Simulink platform. The inclusion of an advanced FLC in the system introduced a novel approach to control strategies, surpassing the traditional PI controller. Through a comprehensive comparative analysis, the simulation results showcased the remarkable efficacy of the proposed solution in an effectively mitigating high-frequency resonance within the TPSS. This outcome underscores the potential of FLC as a sophisticated control mechanism for enhancing the performance systems in railway applications, showcasing its superiority over conventional control methods. The study contributes in shedding light on innovative approaches for optimizing the control and efficiency of grid-side LCL filter-based converters in high-speed train systems.

Design of an Integral Fuzzy Logic Controller for a Variable-Speed Wind Turbine Model

The demand for electricity is continuously growing around the world and thus the need for renewable and long-lasting sources of energy has become an essential challenge. Wind turbines are considered one of the major sources of renewable electricity generation. Therefore, there is a crucial demand for wind turbine model and control systems that are capable of precisely simulating the actual wind power systems. In this paper, an advanced fuzzy logic controller is proposed to control the speed of a wind turbine system. Initially, aero dynamical, mechanical and electrical models of two mass wind turbines models are derived. Analytical calculation of the power coefficient is adopted through a nonlinear function of six coefficients that mainly depends on pitch angle and tip speed ratio. The ultimate power output from the turbine can reach up to 50 % which is achieved at zero pitch angle with an approximately tip speed ratio of eight. This is then followed by designing a hybrid fuzzy-plus I pitch controller to regulate the speed of the wind turbine shaft. In general, fuzzy logic control strategy have the advantages over traditional control techniques especially when the system is highly non-linear and has to deal with strong disturbances such as wind turbulence. To evaluate the reliability and robustness of the controller, the response of the wind turbine system is tested under several types of disturbances including wind fluctuation, sudden disturbances on high and low speed shafts. Simulation findings reveals that the performance of fuzzy-integral control technique outweighs that of conventional fuzzy approach in terms of multiple performance evaluation indexes such as zero overshoot and steady state error, rise time and a settling time of (32.9 s) (44.7 s) respectively. The reliability and robustness of the controller is tested by applying speed and torque disturbances of 25% of their maximum ranges. Results have revealed that the controller was able to reject all disturbances efficiently with a change in pitch angle up to a maximum of 10 degrees in order to retain a constant rotor speed at 1000 rpm.

Improve and analyze the performance of photovoltaic systems controlled by an advanced fuzzy logic method for fast and stable MPPT

The main problem that often arises in photovoltaic systems is to achieving the maximum output power and maintaining the DC-DC connection voltage at a stable value since the power generated by photovoltaic panels is very powerless in uncertain climatic conditions. Moreover, the sunshine and temperature constantly change during the day. The aim of this work is to adapt and optimize an intelligent control algorithm for photovoltaic systems based on a fuzzy logic method to track the maximum power point (MPPT) at a stable value with a fast settling time and to optimize the efficiency under different influences of weather conditions (lighting and temperature). The system consists of a photovoltaic solar module connected to a DC-DC boost converter and a load. The effectiveness of the proposed system was validated by computer simulations using MATLAB/Simulink software. The results of this work show that the efficiency of the photovoltaic system can be improved up to 99.1% by using the advanced fuzzy logic controller.

Implementation of a High Power Quality BLDC Motor Drive Using Bridgeless DC to DC Converter with Fuzzy Logic Controller

Electric motor drives based on electronic power converters having good power quality parameters are getting huge acceptance. Conventional Diode Bridge Rectifier (DBR) and DC to DC converter-based methods have become obsolete, as they provide low power quality indices which hamper the supply by introducing current harmonics and conduction losses. Although there are many developments in motors and control strategies, the risk and complexity of such drives become bottlenecks in implementation. This study implemented a drive scheme with a brushless DC Motor. The new improved bridgeless topology was modified with an advanced fuzzy logic controller to further improve its power quality and performance. Due to low power, a high-speed application of Brush Less (BLDC) motor was selected for the drive scheme. This combination could achieve almost Unity Power Factor (UPF) and significantly improve control compared to conventional topologies. A circuit-wise analysis was conducted to design the converter's components. The modifications were elaborated through mathematical expressions, and the parameters of power quality were analyzed and validated.

Modeling and Analysis of Active Full Vehicle Suspension Model Optimized Using the Advanced Fuzzy Logic Controller

The suspension system plays a major role in automobiles to improve passenger comfort, passenger safety and road handling. It isolates the body of a vehicle from road disturbances. The full vehicle would be subjected to disturbances from all four wheels or a full suspension model of the vehicle and, thus, a full-suspension model of the vehicle should be added to the idea of an enhanced control preview. The input data for the fuzzy logic controller (FLC) is the velocity and acceleration of the front and rear wheels. Controller outputs are considered to be active forces that improve driver comfort, safety and road handling characteristics. The objective of this work is to model and analyse an active full vehicle suspension. The model is optimized using advanced FLC to improve driver comfort, safety and road handling. The mathematical model for the active full vehicle suspension model has been derived. The necessary background for the Simulink fuzzy logic and FLC has been presented. All the simulations are carried out using MATLAB/SIMULINK, a high-performance numeric computation and visualization software package. The fuzzy logic-controlled active values have been compared with ordinary passive simulated values for road profiles. The result of the simulation show that the designed advanced FLC has improved ride comfort by effectively reducing the vehicle body displacement. There is also an appreciable reduction in velocity and acceleration with no increase in suspension travel.

Energy, economic and environmental analysis of fuzzy logic controllers used in smart buildings

This article is divided into three parts: the first presents a simulation study of the effect of occupancy level on energy usage pattern of Engineering building of Applied Science Private university, Amman, Jordan. The simulation was created on simulation mechanism by means of EnergyPlus software and improved by using the building’s data such as building’s as built plan, occupant’s density level based on data about who utilize the building throughout operational hours, energy usage level, Heating Ventilating and air conditioning (HVAC) system, lighting and its control systems and etc. Data regarding occupancy density level estimation is used to provide the proposed controller with random number of users grounded on report were arranged by the university’s facilities operational team. The other division of this paper shows the estimated saved energy by the means of suggested advanced add-on, FUZZY-PID controlling system. The energy savings were divided into summer savings and winter savings. The third division presents economic and environmental analysis of the proposed advanced fuzzy logic controllers of smart buildings in Subtropical Jordan. The economic parameters that were used to evaluate the system economy performance are life-cycle analysis, present worth factor and system payback period. The system economic analysis was done using MATLAB software

Advanced fuzzy logic controller design for a sustainable energy system

Advanced fuzzy logic controller design for a sustainable energy system

Advanced fuzzy logic controller design for a sustainable energy system

Advanced fuzzy logic controller design for a sustainable energy system

A Comparative Study on Controllers for Improving Transient Stability of DFIG Wind Turbines During Large Disturbances

Under power system short-circuits, the Doubly-Fed Induction Generator (DFIG) Wind Turbines (WT) are required to be equipped with crowbar protections to preserve the lifetime of power electronics devices. When the crowbar is switched on, the rotor windings are short-circuited. In this case, the DFIG behaves like a squirrel-cage induction generator (SCIG) and can adsorb reactive power, which can affect the power system. A DFIG based-fault-ride through (FRT) scheme with crowbar, rotor-side and grid-side converters has recently been proposed for improving the transient stability: in particular, a hybrid cascade Fuzzy-PI-based controlling technique has been demonstrated to be able to control the Insulated Gate Bipolar Transistor (IGBT) based frequency converter in order to enhance the transient stability. The performance of this hybrid control scheme is analyzed here and compared to other techniques, under a three-phase fault condition on a single machine connected to the grid. In particular, the transient operation of the system is investigated by comparing the performance of the hybrid system with conventional proportional-integral and fuzzy logic controller, respectively. The system validation is carried out in Simulink, confirming the effectiveness of the coordinated advanced fuzzy logic control.

Advanced Fuzzy Logic Control system for Thermal Power Plant

Advanced Fuzzy Logic Control system for Thermal Power Plant

OCR- The 3 Layered Approach for Decision Making State and Identification of Telugu Hand Written and Printed Consonants and Conjunct Consonants by Using Advanced Fuzzy Logic Controller

Optical Character recognition is the method of digitalization of hand and type written or printed text into machine-encoded form and is superfluity of the various applications of envision of human’s life. In present human life OCR has been successfully using in finance, legal, banking, health care and home need appliances. India is a multi cultural, literature and traditional scripted country. Telugu is the southern Indian language, it is a syllabic language, symbol script represents a complete syllable and formed with the conjunct mixed consonants in their representation. Recognition of mixed conjunct consonants is critical than the normal consonants, because of their variation in written strokes, conjunct maxing with pre and post level of consonants. This paper proposes the layered approach methodology to recognize the characters, conjunct consonants, mixed- conjunct consonants and expressed the efficient classification of the hand written and printed conjunct consonants. This paper implements the Advanced Fuzzy Logic system controller to take the text in the form of written or printed, collected the text images from the scanned file, digital camera, Processing the Image with Examine the high intensity of images based on the quality ration, Extract the image characters depends on the quality then check the character orientation and alignment then to check the character thickness, base and print ration. The input image characters can classify into the two ways, first way represents the normal consonants and the second way represents conjunct consonants. Digitalized image text divided into three layers, the middle layer represents normal consonants and the top and bottom layer represents mixed conjunct consonants. Here recognition process starts from middle layer, and then it continues to check the top and bottom layers. The recognition process treat as conjunct consonants when it can detect any symbolic characters in top and bottom layers of present base character otherwise treats as normal consonants. The post processing technique applied to all three layered characters. Post processing of the image: concentrated on the image text readability and compatibility, if the readability is not process then repeat the process again. In this recognition process includes slant correction, thinning, normalization, segmentation, feature extraction and classification. In the process of development of the algorithm the pre-processing, segmentation, character recognition and post-processing modules were discussed. The main objectives to the development of this paper are: To develop the classification, identification of deference prototyping for written and printed consonants, conjunct consonants and symbols based on 3 layered approaches with different measurable area by using fuzzy logic and to determine suitable features for handwritten character recognition.

Optical Character Recognition (OCR)-Decision Making State and Identification of Telugu Hand Written Touching Conjuct Consonants and Mixed Consonants by Using Advanced Fuzzy Logic Controller With Layered Approach

Optical Character recognition is superfluity of the various applications of envision of human's life. In present life OCR has been successfully using in finance, legal, banking, health care and home need appliances. OCR is the method of digitalization of hand and type written or printed text into machine-encoded form. India is a multi cultural, literature and traditional scripted country. 18 official scripted languages are formed and have many local regional languages in India. Telugu is official language of the southern Indian states of Telangana and Andhra Pradesh and many people spoken in all over in Malaysia, Bahrain, Oman, Singapore, Fiji, UAE and Mauritius. Telugu is a syllabic language, symbol script represents a complete syllable and formed with the conjunct mixed consonants in their representation. Recognition of mixed conjunct consonants is critical than the normal consonants, because of their variation in written strokes, conjunct maxing with pre and post level of consonants. This paper proposes the layered approach methodology to recognize the characters, conjunct consonants, mixed-conjunct consonants and expressed the efficient classification of the hand written and printed conjunct consonants. This paper implements the Advanced Fuzzy Logic system controller to take the text in the form of written or printed, collected the text images from the scanned file, digital camera, Processing the Image with Examine the high intensity of images based on the quality ration, Extract the image characters depends on the quality then check the character orientation and alignment then to check the character thickness, base and print ration. The input image characters can classify into the two ways, first way represents the normal consonants and the second way represents conjunct consonants. Digitalized image text divided into three layers, the middle layer represents normal consonants and the top and bottom layer represents mixed conjunct consonants. Here recognition process starts from middle layer, and then it continues to check the top and bottom layers. The recognition process treat as conjunct consonants when it can detect any symbolic characters in top and bottom layers of present base character otherwise treats as normal consonants. The post processing technique applied to all three layered characters. Post processing of the image: concentrated on the image text readability and compatibility, if the readability is not process then repeat the process again. In this recognition process includes slant correction, thinning, normalization, segmentation, feature extraction and classification. In the process of development of the algorithm the pre-processing, segmentation, character recognition and post-processing modules were discussed. The main objectives to the development of this paper are: To develop the classification, identification of deference prototyping for written and printed consonants, conjunct consonants and symbols based on 3 layered approaches with different measurable area by using fuzzy logic and to determine suitable features for handwritten character recognition.

Interval Type-2 Fuzzy Logic Control of Maglev Test Stand

The paper contains a description of a research into applying classic algorithm of PID controller as well as advanced Type-2 Fuzzy logic controller to ensure stability of the levitating object in magnetic field. The implemented algorithm can handle uncertainties without increasing drastically the computational complexity, which is crucial in case of PLCs. The issues concerning the construction of the unit, where the experiments were carried out, are presented, as well as the characteristics of the object for different controllers.

Potential of Saving Energy Using Advanced Fuzzy Logic Controllers in Smart Buildings in Subtropical Climates in Australia

Subtropical Regions in Australia are associated with high demand for air conditioning throughout the long Summer which leads to a high energy consumption and consequently high greenhouse gas (GHG) emissions which has a high negative impact on the environment. Using conventional controllers in Building Management Systems (BMS) whose functions are based on ON/OFF, temperature control and in some cases humidity control is not the ultimate solution to save energy. The reason behind the above fact is that, conventional controllers do not take into account real time events such as the number of occupants, indoor air quality (IAQ), natural light illuminations and etc dislike Fuzzy logic based controllers. In the last decade there is a high interest in researching Fuzzy logic based controllers as they have the ability to save energy while maintaining indoor comfort level. In this article a general review on Fuzzy logic based controllers is presented, focusing on the role of technology in saving energy, and its potential in subtropical Central Queensland, Australia. The issues of past and present techniquesare highlighted and discussed accordingly.

Fuzzy Regulator Design for Wind Turbine Yaw Control

This paper proposes the development of an advanced fuzzy logic controller which aims to perform intelligent automatic control of the yaw movement of wind turbines. The specific fuzzy controller takes into account both the wind velocity and the acceptable yaw error correlation in order to achieve maximum performance efficacy. In this way, the proposed yaw control system is remarkably adaptive to the existing conditions. In this way, the wind turbine is enabled to retain its power output close to its nominal value and at the same time preserve its yaw system from pointless movement. Thorough simulation tests evaluate the proposed system effectiveness.

Recent Developments of Advanced Fuzzy Logic Controllers Used in Smart Buildings in Subtropical Climate

Building management system (BMS) has the ability to monitor and control buildings’ mechanical and electrical equipment including namely heating, ventilating and air conditioning (HVAC), lighting, power, fire and security systems. BMS can also provide indoor thermal comfort within commercial buildings including industrial and institutional buildings and able to reduce energy consumption. However most of HVAC systems are controlled by using conventional controller whose functions are based on ON/OFF controller and Proportional-Integral-Derivative (PID) controllers. These controllers are not the ultimate solution to save energy because the operations of HVAC systems are nonlinear. Thus, the implementation of fuzzy logic controllers within smart buildings will be more efficient which consequently will save more energy and money. This paper reviews, investigates and evaluates the use of fuzzy logic controller in HVAC systems and light controllers for smart buildings in subtropical Australia. Additionally, it highlights the recent developments in BMS controllers including its conceptual basis, capabilities and limitations.

Design of an advanced incremental fuzzy logic controller for laser surface heat treatments

This work presents an innovative incremental PI fuzzy logic controller developed specifically to laser surface heat treatments, analyzing the specific issues related to the monitoring and control of the process. This real time control system improves considerably the treatment uniformity, reducing the rejection rate and increasing the productivity and final quality of the obtained products. An interesting contribution of this work is the characterization of the developed control strategy in terms of several quantitative criteria not usually analyzed, specially the design time and the experience and knowledge needed to develop and tune the control algorithm, without forgetting the classical validation criteria, such as the rise and settling time, the overshoot, and the steady state error, etc.

Advanced fuzzy logic controllers design and evaluation for buildings’ occupants thermal–visual comfort and indoor air quality satisfaction

The aim of this paper is to present and evaluate control strategies for adjustment and preservation of air quality, thermal and visual comfort for buildings’ occupants while, simultaneously, energy consumption reduction is achieved. Fuzzy PID, fuzzy PD and adaptive fuzzy PD control methods are applied. The inputs to any controller are: the PMV index affecting thermal comfort, the CO 2 concentration affecting indoor air quality and the illuminance level affecting visual comfort. The adaptive fuzzy PD controller adapts the inputs and outputs scaling factors and is based on a second order reference model. More specifically, the scaling factors are modified according to a sigmoid type function, in such a way that the measured variable to be as closer as possible to the reference model. The adaptive fuzzy PD controller is compared to a non-adaptive fuzzy PD and to an ON–OFF one. The comparison criteria are the energy required and the controlled variables response. Both, energy consumption and variables responses are improved if the adaptive fuzzy PD type controller is used. The buildings’ response to the control signals has been simulated using MATLAB/SIMULINK.