Showing 15 results for Fuzzy Logic
M. M. Rezaei, M. Mirsalim,
Volume 6, Issue 2 (6-2010)
Abstract
Here, a new fuzzy direct torque control algorithm for induction motors is
proposed. As in the classical direct torque control, the inverter gate control signals directly
come from the optimum switching voltage vector look-up table, the best voltage space
vector selection is a key factor to obtain minimum torque and flux ripples. In the proposed
approach, the best voltage space vector is selected using a new fuzzy method. A simulation
model is built up and the torque and flux ripples of basic direct torque control and the
proposed method are compared. The simulation results show that the torque and flux
ripples are significantly decreased and in addition, the switching frequency can be fixed.
C. Nagarajan, M. Madheswaran,
Volume 8, Issue 3 (9-2012)
Abstract
This paper presents a Closed Loop CLL-T (capacitor inductor inductor) Series Parallel Resonant Converter (SPRC) has been simulated and the performance is analysised. A three element CLL-T SPRC working under load independent operation (voltage type and current type load) is presented in this paper. The Steady state Stability Analysis of CLL-T SPRC has been developed using State Space technique and the regulation of output voltage is done by using Fuzzy controller. The simulation study indicates the superiority of fuzzy control over the conventional control methods. The proposed approach is expected to provide better voltage regulation for dynamic load conditions. A prototype 300 W, 100 kHz converter is designed and built to experimentally demonstrate, dynamic and steady state performance for the CLL-T SPRC are compared from the simulation studies.
L Hassan, H Sadati, J Karimi,
Volume 9, Issue 4 (12-2013)
Abstract
An integrated fuzzy guidance (IFG) law for a surface to air homing missile is introduced. The introduced approach is a modification of the well-known proportional navigation guidance (PNG) law. The IFG law enables the missile to approach a high maneuvering target while trying to minimize control effort as well as miss-distance in a two-stage flight. In the first stage, while the missile is far from the intended target, the IFG tends to have low sensitivity to the target maneuvering seeking to minimize the overall control effort. When the missile gets closer to the target, a second stage is started and IFG law changes tactic by increasing that sensitivity attempting to minimize the miss-distance. A fuzzy-switching point (FSP) controller manages the transition between the two stages. The FSP is optimized based on variety of scenarios some of which are discussed in the paper. The introduced scheme depends on line-of-sight angle rate, closing velocity, and target-missile relative range. The performance of the new IFG law is compared with PNG law and the results show a relative superiority in wide variety of flight conditions.
F. Hunaini, I. Robandi, I. N. Sutantra,
Volume 11, Issue 1 (3-2015)
Abstract
Steer-by-wire is the electrical steering systems on vehicles that are expected with the development of an optimal control system can improve the dynamic performance of the vehicle. This paper aims to optimize the control systems, namely Fuzzy Logic Control (FLC) and the Proportional, Integral and Derivative (PID) control on the vehicle steering system using Imperialist Competitive Algorithm (ICA). The control systems are built in a cascade, FLC to suppress errors in the lateral motion and the PID control to minimize the error in the yaw motion of the vehicle. FLC is built has two inputs (error and delta error) and single output. Each input and output consists of three Membership Function (MF) in the form of a triangular for language term "zero" and two trapezoidal for language term "negative" and "positive". In order to work optimally, each MF optimized using ICA to get the position and width of the most appropriate. Likewise, in the PID control, the constant at each Proportional, Integral and Derivative control also optimized using ICA, so there are six parameters of the control system are simultaneously optimized by ICA. Simulations performed on vehicle models with 10 Degree Of Freedom (DOF), the plant input using the variables of steering that expressed in the desired trajectory, and the plant outputs are lateral and yaw motion. The simulation results showed that the FLC-PID control system optimized by using ICA can maintain the movement of vehicle according to the desired trajectory with lower error and higher speed limits than optimized with Particle Swarm Optimization (PSO).
M. Khoddam, J. Sadeh, P. Pourmohamadiyan,
Volume 13, Issue 1 (3-2017)
Abstract
Circuit Breakers (CBs) are critical components in power system for reliability and protection. To assure their accurate performance, a comprehensive condition assessment is of an imminent importance. Based on dynamic resistance measurement (DRM), this paper discusses a simple yet effective fuzzy approach for evaluating CB’s electrical contacts condition. According to 300 test results obtained from healthy and three defected electrical contacts, the authors describe the special effect of common failures on DRM characteristics and propose seven deterioration indicators. Using these parameters, a fuzzy classifier is suggested to accurately determine contact sets condition. The salient advantage of the proposed model is its capability to recognize the type of contact failure. The feasibility and effectiveness of the proposed scheme has been validated through 40 real life recorded data of some electrical contacts.
R. Pour Ebrahim, S. Tohidi, A. Younesi,
Volume 14, Issue 1 (3-2018)
Abstract
In this paper, a new sensorless model reference adaptive method is used for direct control of active and reactive power of the doubly fed induction generator (DFIG). In order to estimate the rotor speed, a high frequency signal injection scheme is implemented. In this study, to improve the accuracy of speed estimation, two methods are suggested. First, the coefficients of proportional-integral (PI) blocks are optimized by using Krill Herd algorithm. In the second method, the fuzzy logic control method is applied in the estimator structure instead of PI controllers. The simulation results for the proposed methods illustrate that the estimated speed perfectly matches the actual speed of the DFIG. In addition, the desired slip value is achieved due to the accurate response. On the other hand, the active and reactive power responses have fast dynamics and relatively low oscillations. Moreover, the fuzzy controller shows more robustness against the variations of machine parameters.
M. Naderan, E. Namjoo, S. Mohammadi,
Volume 15, Issue 3 (9-2019)
Abstract
Social networks have become the main infrastructure of today’s daily activities of people during the last decade. In these networks, users interact with each other, share their interests on resources and present their opinions about these resources or spread their information. Since each user has a limited knowledge of other users and most of them are anonymous, the trust factor plays an important role on recognizing a suitable product or specific user. The inference mechanism of trust in social media refers to utilizing available information of a specific user who intends to contact an unknown user. This mostly occurs when purchasing a product, deciding to have friendship or other applications which require predicting the reliability of the second party. In this paper, first the raw data of the real world dataset, Epinions, is examined, and the feature vector is calculated for each pair of social network users. Next, fuzzy logic is incorporated to rank the membership of trust to a specific class, according to two-, three- and five-classes classification. Finally, to classify the trust values of users, three machine learning techniques, namely Support Vector Machine (SVM), Decision Tree (DT), and k-Nearest Neighbors (kNN), are used instead of traditional weighted sum methods, to express the trust between any two users in the presence of a special pattern. The results of simulation show that the accuracy of the proposed method reaches to 91%, and unlike other methods, does not decrease by increasing the number of samples.
B. Yassine, Z. Fatiha, L. Chrifi-Alaoui,
Volume 16, Issue 1 (3-2020)
Abstract
This paper suggests novel sensorless speed estimation for an induction motor (IM) based on a stator current model reference adaptive system (IS-MRAS) scheme. The IS-MRAS scheme uses the error between the reference and estimated stator current vectors and the rotor speed. Observing rotor flux and the speed estimating using the conventional MRAS technique is confronted with certain problems related to the presence of the pure integrator and the rotor resistance causing offsets at low speeds, as proved by the most recent publications. These offsets are disastrous in sensorless control since these signals are no longer suitable to calculate of park angle (θs). This paper discusses the new MRAS approach (IS-MRAS) for on-line identification of the rotor resistance suitable for compensating offsets and solving problems of ordinary MRAS at low speed. This new MRAS approach used to estimate the components of the rotor flux and rotor speed without using the voltage model with on-line Setting parameters (Kp, K1) based on Type-2 fuzzy Logic. The results of the simulation and the experimental results are presented and show the effectiveness of the proposed technique.
H. Shayeghi, A. Younesi,
Volume 16, Issue 4 (12-2020)
Abstract
The main objective of this paper is to model and optimize the parallel and relatively complex FuzzyP+FuzzyI+FuzzyD (FP+FI+FD) controller for simultaneous control of the voltage and frequency of a micro-grid in the islanded mode. The FP+FI+FD controller has three parallel branches, each of which has a specific task. Finally, as its name suggests, the final output of the controller is derived from the algebraic summation of the outputs of these three branches. Combining the basic features of a simple PID controller with fuzzy logic that leads to an adaptive control mechanism, is an inherent characteristic of the FP+FI+FD controller. This paper attempts to determine the optimal control gains and Fuzzy membership functions of the FP+FI+FD controller using an improved Salp swarm algorithm (ISSA) to achieve its optimal dynamic response. The time-domain simulations are carried out in order to prove the superb dynamic response of the proposed FP+FI+FD controller compared to the PID control methods. In addition, a multi-input-multi-output (MIMO) stability analysis is performed to ensure the robust control characteristic of the proposed parallel fuzzy controller.
P. O. Oluseyi, J. A. Adeagbo, D. D. Dinakin, O. M. Babatunde,
Volume 17, Issue 1 (3-2021)
Abstract
The philosophy of efficient energy consumption is vitally crucial to profitable production cost in manufacturing industries. This is because the unit production cost is largely determined by the cost of unit energy supply; which is quite higher than the cost of raw materials in Nigeria. It has been established that the Nigerian industrial sector is responsible for 8.7% of the total energy consumption in the nation. Out of this chunk, the food and beverage industry appropriates approximately 2%. Meanwhile, it is observed that the energy consumption trend in most industrial electric motors is always high due to continuous operation even during the idle time/period in production. In this study, data gathered has a coefficient of determination of 99.7%. This is, thus, subjected to regression analysis which assists in predicting the energy consumption trend for a period of one year. Further to this, the capacity of control principles in efficient energy consumption is demonstrated by practical real time implementation of a smart energy saving in the food industries using PLClogicx software. In this sense, the developed programmable logic control (PLC) ladder diagram was further designed and implemented using fuzzy logic control (FLC). This is simulated using MATLAB/Simulink toolbox. By this arrangement; it is observed that there was a significant reduction in energy consumption. This is obviously revealed in the obtained results. In this case, there was an average electrical energy savings of 65.59% in the plant’s case sealing section while an energy saving of approximately 0.13% was achieved in reference to the overall energy consumption of the industrial plant’s processes. Finally, based on the mathematical calculations obtained from observations of typical production processes in the multinational food and beverage company, the FLC is discovered to provide 99.83% efficiency in optimizing energy consumption.
Azzedine Khati,
Volume 20, Issue 3 (9-2024)
Abstract
In this research paper, a multivariable prediction control method based on direct vector control is applied to command the active power and reactive power of a doubly-fed induction generator used into a wind turbine system. To obtain high energy performance, the space vector modulation inverter based on fuzzy logic technique (fuzzy space vector modulation) is used to reduce stator currents harmonics and active power and reactive power ripples. Also the direct vector control model of the doubly-fed induction generator is required to ensure a decoupled control. Then its classic proportional integral regulators are replaced by the multivariable prediction controller in order to adjust the active and reactive power. So, in this work, we implement a new method of control for the doubly-fed induction generator energy. This method is carried out for the first time by combining the MPC strategy with artificial intelligence represented by Fuzzy SVM-based converter in order to overcome the drawbacks of other controllers used in renewable energies. The given simulation results using Matlab software show a good performance of the used strategy, particularly with regard to the quality of the energy supplied.
Raheel Jawad, Rawaa Jawad,
Volume 20, Issue 3 (9-2024)
Abstract
Fire accidents are a disaster that can cause loss of life, property damage and permanent disability to the affected victim. Firefighting is a very important and dangerous job. Firefighters must extinguish the fire quickly and safely to prevent further damage and destruction. Detecting and extinguishing fires is a dangerous task that always puts the lives of firefighters at risk. One of the most effective tools for early fire extinguishing is the firefighting robot. Fire sensing in most industries is absolutely essential to prevent catastrophic losses. Robots with this type of embedded system can save the lives of engineers in industrial sites with hazardous conditions. This project aims to design and implement a solar-powered with artificial intelligent of mobile fire detection robot to detect fires in disaster-prone areas and thus reduce human work effort and level of destruction. Design a robot capable of moving using a rotary motor, finding a flame using a flame sensor, and extinguishing a fire using a water spray using a pump, all of which is controlled by an Arduino Uno microcontroller and programmed using an artificial intelligence (fuzzy) logic technology) using MATLAB, the inputs It has two variations:: flame and gas with three organic functions, each of which has a gas variable (low, medium, high), flame sensor (small, normal, large), and the output is a pump, (pump off , pump on ) with 9 rules. In addition to the experimental setup of the proposed system which demonstrates the performance of sensors (gas, flame) using fuzzy and implemented logic tools. The performance of the solar panels was first tested using MATLAB software as well as experimentally under different weather conditions. The pump's performance is being tested experimentally, and the robot is also being tested to detect and extinguish fires. The process of designing and implementing robotics involves creating mechanical and electrical systems. The results showed the effect of temperature change on the solar panel, as when it increases, the panel’s production capacity decreases, as well as the effect of decreased solar radiation resulting from clouds and other things, and the extent of its effect. Impact on the performance efficiency of solar panels, and observing the pump performance in terms of flow rate and height. Hence, it can be noted that the robot designed in the project is capable of discovering fire sources and extinguishing them using fire-fighting systems equipped with a water tank and a controllable pump to spray the water necessary for the process. From this study, can be concluded that the designed model is able to work according to its initial design with artificial intelligence with the least amount of errors, and therefore it can be applied in industrial applications, avoiding fire damage and extinguishing it when it occurs for the first time.
Ying Foo Leong, Nizaruddin M. Nasir, Suliana Ab-Ghani, Norazila Jaalam, Nur Huda Ramlan,
Volume 21, Issue 2 (6-2025)
Abstract
This paper focuses on the application of a cascaded multilevel inverter, specifically the 5-level multilevel inverter, utilizing a proposed controller known as the FLC-PSO-PI controller. The primary challenge addressed in this research is the precise regulation of output voltage in the multilevel inverter during load variations while meeting voltage harmonic and transition requirements as per industry standards, which are the 10 % voltage limit recommended by IEC and 8 % of total harmonic distortion (THD) by IEEE. An innovative solution is proposed by integrating PSO and FLC to dynamically adapt the controller in real-time, ensuring stable and accurate output voltage regulation. The proposed controller is designed and simulated using MATLAB/Simulink, and its performance is compared with PSO-PI and no controller under various load conditions. The results demonstrate that the FLC-PSO-PI controller significantly enhances output voltage regulation were achieving the desired peak voltage and low THD across different load scenarios, including half load to full load (0.8 %) and no load to full load (0.89 %). Furthermore, the FLC-PSO-PI controller exhibits superior transient response characteristics, such as reduced overshooting (2.89 %), faster rise time at 36.946 µs, and satisfactory settling time at 151.014 µs. This research contributes to the advancement of multilevel inverter technology and its potential applications in renewable energy systems, motor drives, and grid-connected devices. The proposed FLC-PSO-PI controller offers a promising solution for precise voltage regulation in multilevel inverters, enhancing their performance and enabling widespread adoption in various industrial sectors.
Nurul Husna Abd Wahab, Mohd Hafizuddin Mat, Norezmi Md Jamal, Nur Hidayah Ramli,
Volume 21, Issue 2 (6-2025)
Abstract
In islanded microgrids, circulating currents among parallel inverters pose significant challenges to system stability and efficient power distribution. Traditional droop control methods often struggle to manage these currents effectively, leading to inefficiencies and potential system damage. This study introduces an advanced fuzzy-robust droop control strategy that integrates fuzzy logic with robust droop control to address these challenges. By incorporating fuzzy logic, the proposed strategy enhances the adaptability of droop control to varying system conditions, improving the management of circulating currents and ensuring more accurate power sharing among inverters. Comprehensive mathematical modeling and extensive simulation analyses validate the performance of this control strategy. The results show that the fuzzy-robust droop control method significantly outperforms conventional approaches, achieving up to a 70% reduction in circulating currents. This improvement leads to a substantial reduction in power losses and enhances the dynamic response under varying load conditions. Additionally, the strategy improves voltage and frequency regulation, contributing to the overall stability and reliability of the microgrid. The findings provide a robust solution to the longstanding issue of circulating currents, optimizing microgrid operations, and paving the way for more efficient and resilient distributed energy systems. The advanced control strategy presented in this study not only addresses critical challenges but also demonstrates the potential for innovative methodologies to meet the growing demands of future energy infrastructures, where reliability and efficiency are essential.
Kumuthawathe Ananda-Rao, Steven Taniselass, Afifah Shuhada Rosmi, Aimi Salihah Abdul Nasir, Nor Hanisah Baharudin, Indra Nisja,
Volume 21, Issue 2 (6-2025)
Abstract
This study presents a Fuzzy Logic Controller (FLC)-based Maximum Power Point Tracking (MPPT) system for solar Photovoltaic (PV) setups, integrating PV panels, a boost converter, and battery storage. While FLC is known for its robustness in PV systems, challenges in battery charging and discharging efficiency can affect performance. The research addresses these challenges by optimizing battery charging, preventing overcharging, and enhancing overall system efficiency. The FLC MPPT system is designed to regulate the battery's State of Charge (SOC) while evaluating system performance under varying solar irradiance and temperature conditions. The system is modeled and simulated using MATLAB/Simulink, incorporating the PV system, MPPT algorithm, and models for the PV module and boost converter. System efficiency is assessed under different scenarios, with results showing 97.92% efficiency under Standard Test Conditions (STC) at 1000 W/m² and 25°C. Additionally, mean efficiencies of 97.13% and 96.13% are observed under varying irradiance and temperature, demonstrating the effectiveness of the FLC MPPT in regulating output. The system also extends battery life by optimizing power transfer between the PV module, boost converter, and battery, ensuring regulated SOC.
