fuzzy logic controller

In various industries, the coordinated movements of mobile robots in triangular formations hold promise for enhancing efficiency and safety. This study investigates trajectory tracking and formation control using two distinct methodologies: the PID controller and the Fuzzy Logic Controller (FLC). Under ideal conditions, both controllers exhibit precise navigation and formation maintenance. Notably, the leader robot has a simulated virtual sensor for obstacle avoidance. The followers emulate the leader’s path using the selected controller methodology. However, when exposed to external disturbances, modeled as sinusoidal waves, the FLC, with its superior adaptability and resilience, demonstrates its potential as a robust solution for real-world applications susceptible to disturbances. This research emphasizes the pivotal role of controller selection in practical scenarios and reiterates the FLC’s potential, instilling confidence in its effectiveness.

generation generates power for local loads as well as sharing it to the main grid. The system may get islanded after the occurrence of fault. It is necessary to detect islanding earlier. It is necessary to detect islanding and provide trip signal earlier. Also, the oscillations should be damped out as early as possible to prevent instability. Harmonics are injected due to the introduction of a disturbance signal hence; total harmonic distortion should be as minimum as possible. Hereadaptive network-based fuzzy inference system is used for the CEGRE LV system for the purpose of islanding detection and anti-islanding protection. An active oscillatory disturbance signal is injected in controller. Generally, proportional integral controller and fuzzy logic controller are used for anti-islanding protection. But an adaptive network-based fuzzy inference system can be used for earlier detection of islanding and also it gives better performance than a proportionalintegral controller and fuzzy logic controller. System analysis is discussed by comparing Adaptive network-based fuzzy interference system performance with proportional gain controller and fuzzy logic controller by considering zero power mismatch condition. The simulation results of this proposed method is evaluated by using MATLAB Software.

By combining particle swarm optimization (PSO) and fuzzy logic controller (FLC), the ability of these methods to solve complex and nonlinear problems effectively improves power system stability. Setting the power system stabilizer parameters using the PSO method is presented in this paper. Fuzzy logic controller has been used for simultaneous weighting of the automatic voltage regulator and power system stabilizer output. First, the simulation has been carried out in a single-machine power system, where the optimal PSS parameters have been obtained using the PSO algorithm. Then, by simultaneously adjusting the voltage and damping by the fuzzy logic controller, the effectiveness of the proposed method is verified compared to the PSS based on the linear optimization controller. In the following, the simulation results of a multi-machine system are shown. The efficiency of the method has been shown in response to a variety of disorders

Distribution Static Synchronous Compensator (D-STATCOM) is a shunt compensator in the distribution systems that one of the most important tasks is to improve the imbalance, reduce and eliminate the nonlinear loads harmonics. Distributed generation resources such as photovoltaic (PV) array can be used as the DC input of D-STATCOM. In this paper, PV array and DC/DC boost convertor are used to stabilize the DC link voltage of D-STATCOM. The main advantage of the proposed method is that for all time provides continuous compensation. Another power quality issues are neutral current in four-wire systems that are created due to the harmonics and system imbalance. Zig-Zag transformer is one of the ways for compensating neutral current and providing isolation between the convertor and flow of the fundamental zero sequence component which contains harmonic neutral current. Role and performance of the distribution shunt compensator in the improvement of power quality indices depends on the performance of its control system. In this paper, the control scheme of synchronous reference frame theory based on fuzzy controller is used for D-STATCOM based on PV and Zig-Zag transformer. Performance and behaviour of the proposed system examined using Matlab/Simulink software and the results will be presented.

Electric spring (ES) is a new technology that can be used for fast demand-side management to balance the power between generation and consumption in smart grids. In this paper, the back-to-back structure of electric spring is controlled to operate simultaneously as electric spring and shunt active power filter (shunt-APF). That means the series part of the back-to-back electric spring regulates the critical load voltage and applies the demand-side management and the parallel part operates as a shunt active power filter capable of power factor correction and current harmonic compensation. In the proposed structure, due to harmonic compensation and power factor improvement by the parallel inverter, the output power capacity of the electric spring is increased compared with the first and second generation of electric springs (ES-1 and ES-2), and the performance is improved in critical conditions. Additionally, to improve the robustness of the control system against uncertainties in the grid system, two fuzzy logic controllers are designed to control the voltage of the electric spring and the DC link voltage. The theoretical analysis is validated by simulation results using MATLAB/SIMULINK software.

The principal aim of this paper is to show an independent vector control of two five-phase Linear Induction Motors (LIMs) that are supplied from a single VSI. The LIMs are running at the same speed but with different load conditions. This concept can be especially beneficial in long trains with distributed power. To achieve excellent control characteristics and to reduce the undesirable tension forces between the train mechanical couplers, Fuzzy Logic Controllers (FLCs) have been utilized. As a result, the fault occurrence of the train control systems decreases, and the system reliability increases. The results prove the electrical independence in control of a five-phase two-LIM drive supplied with a single VSI. Furthermore, in the presence of the train mechanical couplers and connections, the application of FLC offers excellent control characteristics and reduces the undesirable tension forces. Furthermore, to obtain a more worthwhile validation of the theoretical results, an experimental set up has been constructed and results have also been presented. According to the results, the undesirable tension forces imposed on train couplers are reduced. Consequently, it leads to higher system efficiency, lower deterioration of the train couplers and connections, greater system reliability, and higher passenger safety and comfort.

Despite superior privileges that multiphase motors offer in comparison with their three-phase counterparts, in the field of multiphase linear induction motors (LIMs) few studies have been reported until now. To combine the advantages of both multiphase motors and linear induction motors, this paper concentrates on multiphase LIM drives considering the end effects.

The main contributions of this paper can be divided into two major categories. First, a comparative study has been conducted about the dynamic performance of Fuzzy Logic Controller (FLC) and Genetic-PI controller for a seven-phase LIM drive; and second, because of the superior performance of the FLC method revealed from the results, the harmonic pollution of the FLC based LIM drive has been studied in the case of supplying through a five-level Cascaded H-bridge (CHB) VSI and then compared with the traditional two-level VSI fed one.

The five-level CHB-VSI has utilized a multiband hysteresis modulation scheme and the two-level VSI has used the traditional three-level hysteresis modulation strategy. Note that for harmonic distortion assessment both harmonic and interharmonic components are considered in THD calculations.

The results validate the effectiveness of the proposed FLC for seven-phase LIM drive supplied with five-level CHB-VSI and guarantee for perfect control characteristics, lower maximum starting current, and significant harmonic and interharmonic reduction The author(s). This is an open access article distributed under the terms of the Creative Commons Attribution (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, as long as the original authors and source are cited. No permission is required from the authors or the publishers.

The objective of this workis to meet the variations of the electrical energy needs by modifying the conventional topology of the conversion chain, at the same time to improve the operation of the photovoltaic system. This article focuses on improving the performance and efficiencyof photovoltaic systems connected to the AC grid, through the use of advanced control algorithms(Sliding Mode control SMC and Fuzzy Logic Control FLC) for the control of DC/DC and DC/AC power conditioners. The control of the DC/DC converter allows the pursuit of the maximum power point MPPT of the photovoltaic generator with a view to a better utilization of the photovoltaic generator.The inverter control system is used to inject synchronized sinusoidal output current to the power grid and to improve thequality of energy injected into the grid. The original idea of this workisbasedon the insertion of a DC/DC BOOST voltage regulator in the conversion chain (between the battery and the inverter) to adjust the voltage transfer of the DC bus. This technique allows the provision of AC voltage for the sufficiency of the energy required by the control according to the need of the load.

Electro-mechanical oscillations are produced in the machines of an interconnected power network, followed by a disturbance or due to high power transfer through weak tie lines. These  oscillations  should  be  damped  as  quickly  as  possible  to  ensure the reliable and stable operation of the network. To damp these  oscillations  different  controllers,  based  on  local  or  wide  area  signals,  have  been  the  subject  of  many  papers.  This  paper  presents  the  analysis  of  the  PID  of  Conventional  Power  System  Stabilizer  (PSS)  and  Fuzzy  Logic  Controller.

Voltage Source Converter based High Voltage Direct Current (VSC-HVDC) has been an area of growing interest during the recent years. Indeed, VSC-HVDC has the capability of controlling the active power and the reactive power; rapidly, independently, and simultaneously. The main focus of this research is on VSC-HVDC system modeling; in which, two different controllers, such as the PI controller and the fuzzy logic controller, have been implanted in the system. Furthermore, these two controllers have been analyzed and compared to each other. Whereas, the main objective of the work presented in this paper is finding the more suitable controller which could allow improving the robustness of the whole control system and its impact on the dynamic performance of the VSC-HVDC during parameter uncertainties, such as load change, parametric variation, and faults occurrence. The obtained results have shown that using the fuzzy controller could lead to a better performance of the studied system, compared to the other controller.

Hybrid renewable energy sources (HRES) similar to PV, wind and diesel generator are the most charming configurations worn for various applications and most probably for the self-contained systems to generate power. While considering different sources Energy management control will be essential. An energy conservation control system is a computer assisted tool commonly used to monitor, measure and control the generation and transmission system performance. In this article surveillance of photovoltaic, diesel and wind with battery storage is introduced. The energy stability of favoured scheme is done by the Artificial Neural Network (ANN). In this approach Multi-level FFN (Feed Forward Network) which is the form of artificial neural network is used for governing process of the hybrid renewable energy source. The Levenberg Marquardt algorithm is an interconnection of perceptron’s in which the data and calculation will flow in an accurate direction from input to output. It is quite simple and easy to resolve the different operating procedures of the hybrid system on the basis of the time varying conditions. The process is implemented under MATLAB R2016a then the attained results are displayed and the comparison results are carried out with fuzzy logic controller and displays the feasibility of the suggested method.

Based on the problems caused by today conventional vehicles, much attention has been put on the fuel cell vehicles researches. However, using a fuel cell system is not adequate alone in transportation applications, because the load power profile includes transient that is not compatible with the fuel cell dynamic. To resolve this problem, hybridization of the fuel cell and energy storage devices such as batteries and ultra-capacitors are usually applied. This article has studied a hybrid electric vehicle comprising a fuel cell system and battery pack. Energy management strategy is one of the essential issues in hybrid electric vehicles designing, for power optimal distribution as well as, improving both the fuel economy and the performance of vehicle's components. In this paper, an optimal hierarchical strategy has been proposed based on the load power prediction and intelligent controlling to achieve an optimal distribution of energy between the vehicle's power sources; and, to ensure reasonable performance of the vehicle's components. For load power prediction, a new method is presented that is based on Takagi – Sugeno fuzzy model trained by an improved differential evolutionary algorithm with an objective function formulated by support vector machine. A combination of empirical mode decomposition (EMD) algorithm capabilities, fuzzy logic controller, supervisory switching technique and improved differential evolution algorithm is used to design the proposed energy management strategy. The proposed strategy is assessed in the UDDS Standard drive cycle. Simulation results show that the proposed control strategy can fulfill all the requirements of an optimal energy management.

In recent year's renewable energy sources have become a useful alternative for the power generation. The power of photovoltaic is nonlinear function of its voltage and current. It is necessary to maintain the operation point of photovoltaic in order to get the maximum power point (MPP) in various solar intensity. Fuzzy logic controller has advantage in handling non-linear system. Maximum power point trackers are so important in photovoltaic systems to increase their efficiency. Many methods have been proposed to achieve the maximum power that the PV modules. This paper proposed an intelligent method for MPPT based on fuzzy logic controller. The system consists of a photovoltaic solar module connected to a DC-DC Boost converter and the fuzzy logic controller for controlling on/off time of MOSFET switch of a boost converter. The proposed MPPT controller for grid-connected photovoltaic system is tested using model designed by Matlab/Simulink program. Comparison of different performance parameters such as: tracking efficiency and response time of the system shows that the proposed method gives higher efficiency and better performance than the conventional perturbation and observation method.

Defuzzifier circuit is one of the most important parts of fuzzy logic controllers that determine the output accuracy. The Center Of Gravity method (COG) is one of the most accurate methods that so far been presented for defuzzification. In this paper, a simple algorithm is presented to generate triangular output membership functions in the Mamdani method using the multiplier/divider circuit and mirror current CMOS technology. As well as the method simplicity, the method is highly accuracy and controllable in the height, slope of output membership functions, number of rules and number of input/output membership functions cause to use mixed voltages. This method covers each type of the input fuzzifier. The proposed Circuits in this paper are implemented by a standard 0.35um CMOS technology in Hspice software

Vehicle ride comfort is a function of the frequency content of transmitted vibrations to passengers from road irregularities. However, this frequency content varies with vehicle speed fluctuations, which occur under real traffic conditions. The design of an adaptive active suspension system, in order to simultaneously improve ride comfort and travel suspension under various traffic conditions, is addressed in this paper. For this purpose, using a full-vehicle model, with eight degrees of freedom, two separate fuzzy controllers are designed for front and rear suspensions. The parameters of the fuzzy controllers are then tuned for various traffic conditions of a driving pattern, using a multi-objective Pareto-optimal solution. The optimization objectives are: the ride comfort index, evaluated according to the ISO 2631-1 standard, and the maximum suspension travel. Simulation results prove that the multi-objective fuzzy controller conventionally tuned, based on the constant speed driving pattern, results in simultaneous improvement of ride comfort, travel suspension and energy consumption. However, this controller does not work optimally under all traffic conditions. On the other hand, the proposed adaptive multi-objective controller not only results in optimal ride comfort and travel suspension under various traffic conditions, but also leads to a considerable drop in active suspension energy consumption.