Lithium-Ion Battery Pack Based on Fuzzy Logic Control Research on Multi-Layer Equilibrium Circuits

In order to solve the problem of inconsistent energy in the charging and discharging cycles of lithium-ion battery packs,a new multilayer equilibrium topology is designed in this paper.The structure adopts a hierarchical structure design,which includes intra-group equilibrium,primary inter-group equilibrium and secondary inter-group equilibrium.This structure greatly increases the number of equilibrium paths for lithium-ion batteries,thus shortening the time required for equilibrium,and improving the overall efficiency.In terms of control strategy,fuzzy logic control(FLC)is chosen to control the size of the equilibrium current during the equilibrium process.We performed rigorous modeling and simulation of the proposed system by MATLAB and Simulink software.Experiments show that the multilayer equilibrium circuit structure greatly exceeds the traditional single-layer equilibrium circuit in terms of efficacy,specifically,the Li-ion battery equilibrium speed is improved by 12.71%in static equilibrium,14.48%in charge equilibrium,and 11.19%in discharge equilibrium.In addition,compared with the maximum value algorithm,the use of the FLC algorithm reduces the equalization time by about 3.27%and improves the energy transfer efficiency by about 66.49%under the stationary condition,which verifies the feasibility of the equalization scheme.

Enhanced Fuzzy Logic Control Model and Sliding Mode Based on Field Oriented Control of Induction Motor

In the context of induction motor control, there are various control strategies used to separately control torque and flux. One common approach is known as Field-Oriented Control (FOC). This technique involves transforming the three-phase currents and voltages into a rotating reference frame, commonly referred to as the “dq” frame. In this frame, the torque/speed and flux components are decoupled, allowing for independent control, by doing so, the motor’s speed can be regulated accurately and maintain a constant flux which is crucial to ensure optimal motor performance and efficiency. The research focused on studying and simulating a field-oriented control system using fuzzy control techniques for an induction motor. The aim was to address the issue of parameter variations, particularly the change in rotor resistance during motor operation, which causes the control system to deviate from the desired direction. This deviation implies to an increase in the magnetic flux value, specifically the flux component on the q-axis. By employing fuzzy logic techniques to regulate flux vector’s components in the dq frame, this problem was successfully resolved, ensuring that the magnetic flux value remains within the nominal limits. To enhance the control system’s performance, response speed, and efficiency of the motor, sliding mode controllers were implemented to regulate the current in the inner loop. The simulation results demonstrated the proficiency of the proposed methodology.

Nonsingular Terminal Sliding Mode Control With Ultra-Local Model and Single Input Interval Type-2 Fuzzy Logic Control for Pitch Control of Wind Turbines

As wind energy is becoming one of the fastestgrowing renewable energy resources,controlling large-scale wind turbines remains a challenging task due to its system model nonlinearities and high external uncertainties.The main goal of the current work is to propose an intelligent control of the wind turbine system without the need for model identification.For this purpose,a novel model-independent nonsingular terminal slidingmode control(MINTSMC)using the basic principles of the ultralocal model(ULM)and combined with the single input interval type-2 fuzzy logic control(SIT2-FLC)is developed for non-linear wind turbine pitch angle control.In the suggested control framework,the MINTSMC scheme is designed to regulate the wind turbine speed rotor,and a sliding-mode(SM)observer is adopted to estimate the unknown phenomena of the ULM.The auxiliary SIT2-FLC is added in the model-independent control structure to improve the rotor speed regulation and compensate for the SM observation estimation error.Extensive examinations and comparative analyses were made using a real-time softwarein-the-loop(RT-SiL)based on the dSPACE 1202 board to appraise the efficiency and applicability of the suggested modelindependent scheme in a real-time testbed.

ARTIFICIAL NEURAL NETWORK AND FUZZY LOGIC CONTROLLER FOR GTAW MODELING AND CONTROL

An artificial neural network(ANN) and a self-adjusting fuzzy logiccontroller(FLC) for modeling and control of gas tungsten arc welding(GTAW) process are presented.The discussion is mainly focused on the modeling and control of the weld pool depth with ANN and theintelligent control for weld seam tracking with FLC. The proposed neural network can produce highlycomplex nonlinear multi-variable model of the GTAW process that offers the accurate prediction ofwelding penetration depth. A self-adjusting fuzzy controller used for seam tracking adjusts thecontrol parameters on-line automatically according to the tracking errors so that the torch positioncan be controlled accurately.

Fuzzy logic controller design with unevenly-distributed membership function for high performance chamber cooling system

Fuzzy logic controller adopting unevenly-distributed membership function was presented with the purpose of enhancing performance of the temperature control precision and robustness for the chamber cooling system.Histogram equalization and noise detection were performed to modify the evenly-distributed membership functions of error and error change rate into unevenly-distributed membership functions.Then,the experimental results with evenly and unevenly distributed membership functions were compared under the same outside environment conditions.The experimental results show that the steady-state error is reduced around 40% and the noise disturbance is rejected successfully even though noise range is 60% of the control precision range.The control precision is improved by reducing the steady-state error and the robustness is enhanced by rejecting noise disturbance through the fuzzy logic controller with unevenly-distributed membership function.Moreover,the system energy efficiency and lifetime of electronic expansion valve(EEV) installed in chamber cooling system are improved by adopting the unevenly-distributed membership function.

Fuzzy logic control strategy for submerged arc automatic welding of digital controlling

A microcomputer control system based on 80C320 and a switching regulation of wire feeder were designed. A correction factor based double model fuzzy logic controller （FLC） was introduced to achieve welding digital and intellectualized control by means of wire feeding speed feedback. The controller has many functions such as keyboard input, light emitting diode （LED） display and real-time intellectualized control of welding process etc. The controlling performance influenced by the coefficient of correction function was discussed. It was concluded by the experiments the relation between the coefficient of correction function and welding quality, when the coefficient of correction function is great, the dynamic character of controller is better, when the coefficient of correction function is small, the sensitivity character of controller is better. Experimental results also show that digital and fuzzy logic control method enable the improvement of appearance of weld and stability of welding process to be achieved in submerged arc automatic welding.

SPECTRUM HANDOFF IN COGNITIVE RADIO WITH FUZZY LOGIC CONTROL

The secondary usage of spectrum has been investigated in Cognitive Radio(CR) network to resolving the spectrum scarcity issue in wireless communication.When Primary Users(PU) who own the spectrum appear,spectrum handoff is needed to maintain the communications of Secondary Users.But the decision making of spectrum handoff is a challenge issue for CR network,because the input of decision making,which obtain through spectrum sensing,is heterogeneous and inexact.In this paper we will use fuzzy logic control theory to solve this issue and make use of new information for handoff operation:the probability of PU's occupancy at a certain channel.Our new algorithm can make more intelligent decision compared to simple traditional spectrum handoff decision making and reduce the probability of spectrum handoff,also the performance of SU's communication can be enhanced.

Fuzzy Logic Control of a Robotic Manipulator for Obstacles Avoidance

This work presents a Fuzzy Logic Controller （FLC） assigned to control a robotic arm motion while avoiding the obstacles that may face the robotic arm in its movement from the initial point to the final point in an optimized manner, in addition to avoid the singularity phenomenon, and without any exceeding of the physical constraints of the robot arm. A real platform （5 DOF ＂Degree Of Freedom＂ Lab Volt 5150 Robotic Arm） is used to carry this work practically, in addition to providing it by a vision sensor, where a new approach is proposed to inspect the robot work environment using a designed integrated MATLAB program having the ability to recognize the changeable locations of each of the robotic arm＇s end-effector, the goal, and the multi existed obstacles through a recorded film taken by a webcam, then these information will be treated using the FLC where its outputs represent the values that must be delivered to the robot to adopt them in its next steps till reaching to the goal in collision-free movements. The experimental results showed that the developed robotic ann travels successfully from Start to Goal where a high percentage of accuracy in arriving to Goal was achieved, and without colliding with any obstacle ensuring the harmonization between the theoretical part and the experimental part in achieving the best results of controlling the robotic arm＇s motion.

Maximum Power Point Tracker Controller Using Fuzzy Logic Control with Battery Load for Photovoltaics Systems

The target of this paper is to model a Maximum Power Point Tracker (MPPT) using a Fuzzy Logic Control (FLC) algorithm and to investigate its behavior with a battery load. The advantage of this study over other studies in this field is that it considers a battery load rather than the commonly used resistive load especially when we deal with the relationship between MPPT and system load. The system is about 60 kW which is simulated under various environmental conditions by Matlab/Simulink program. For this type of non-linear application, FLC naturally offers a superior controller for the real load case. The artificial intelligence approach also benefits from this method for overcoming the complexity of nonlinear system modelling. The results show that FLC provides high performance for MPPT of PV system with battery load due to its low settling time and limited oscillation around the steady state value. These are assistant factors for increasing battery life.

Fuzzy logic controller implementation on a microbial electrolysis cell for biohydrogen production and storage

This work presents the implementation of fuzzy logic control(FLC) on a microbial electrolysis cell(MEC).Hydrogen has been touted as a potential alternative source of energy to the depleting fossil fuels. MEC is one of the most extensively studied method of hydrogen production. The utilization of biowaste as its substrate by MEC promotes the waste to energy initiative. The hydrogen production within the MEC system, which involves microbial interaction contributes to the system's nonlinearity. Taking into account of the high complexity of MEC system, a precise process control system is required to ensure a wellcontrolled biohydrogen production flow rate and storage application inside a tank. Proportionalderivative-integral(PID) controller has been one of the pioneer control loop mechanism. However, it lacks the capability to adapt properly in the presence of disturbance. An advanced process control mechanism such as the FLC has proven to be a better solution to be implemented on a nonlinear system due to its similarity in human-natured thinking. The performance of the FLC has been evaluated based on its implementation on the MEC system through various control schemes progressively. Similar evaluations include the performance of Proportional-Integral(PI) and PID controller for comparison purposes. The tracking capability of FLC is also accessed against another advanced controller that is the model predictive controller(MPC). One of the key findings in this work is that the FLC resulted in a desirable hydrogen output via MEC over the PI and PID controller in terms of shorter settling time and lesser overshoot.

Analyses and Simulation of Fuzzy Logic Control for Suspension System of a Track Vehicle

The vibration caused by terrible road excitation affects the ride quality and safety of track vehicles. The vibration control of suspension systems is a very important factor for modern track vehicles. A fuzzy logic control for suspension system of a track vehicle is presented. A mechanical model and a system of difft, rential equations of motion taking account of the mass of loading wheel are established. Then the fuzzy logic control is applied to control the vibration of suspension system of track vehicles for sine signal and random road surfaces. Numerical simulation shows that the maximum acceleration of suspension system can be reduced to 44 % of the original value for sine signal road surface, and the mean square root of acceleration of suspension system can be reduced to 21% for random road surface. Therefore, the proposed fuzzy logic control is an efficient method for the suspension systems of track vehicles.

Fuzzy Logic Control for Suspension Systems of Tracked Vehicles

A scheme of fuzzy logic control for the suspension system of a tracked vehicle is presented. A mechanical model for the whole body of a tracked vehicle, which is totally a fifteen-degree-of-freedom system, is established. The model includes the vertical motion, the pitch motion as well as the roll motion of the tracked vehicle. In contrast to most previous studies, the coupling effect among the vertical, the pitch and the roll motions of the suspension system of a tracked vehicle is considered simultaneously. The simulation of fuzzy logic control under road surface with random excitation shows that the acceleration, pitch angle and roll angle of suspension system can be efficiently controlled.

A tunable fuzzy logic controller for the vehicle semi-active suspension system

On the basis of analyzing the system constitution of vehicle semi-active suspension, a 4-DOF (degree of freedom) dynamic model is established. A tunable fuzzy logic controller is designed by using without quantification method and taking into account the uncertainty, nonlinearity and complexity of parameters for a vehicle suspension system. Simulation to test the performance of this controller is performed under random excitations and definite disturbances of a C grade road, and the effects of time delay and changes of system parameters on the vehicle suspension system are researched. The numerical simulation shows that the performance of the designed tunable fuzzy logic controller is effective, stable and reliable.

Fuzzy Logic Control for Semi-Active Suspension System of Tracked Vehicle

The model of half a tracked vehicle semi-active suspension is established. The fuzzy logic controller of the semi-active suspension system is constructed. The acceleration of driver's seat and its time derivative are used as the inputs of the fuzzy logic controller, and the fuzzy logic controller output determines the semi-active suspension controllable damping force. The fuzzy logic controller is to minimize the mean square root of acceleration of the driver's seat. The control forces of controllable dampers behind the first road wheel are obtained by time delay, and the delay times are determined by the vehicle speed and axles distances. The simulation results show that this control method can decrease the acceleration of driver's seat and the suspension travel of the first road wheel, the ride quality is improved obviously.

Correction factor based double model fuzzy logic control strategy of arc voltage in pulsed MIG welding

According to the feature of arc voltage control in welding steel using pulsed MIG welding, a correction factor based double model fuzzy logic controller (FLC) was developed to realize the arc voltage control by means of arc voltage feedback. When the error of peak arc voltage was great, a coarse adjusting fuzzy logic control rules with correction factor was designed, in the controller, the peak arc voltage was controlled by the wire feeding speed by means of arc voltage feedback. When the error of peak arc voltage was small, a fine adjusting fuzzy logic control rules with correction factor was designed, in this controller, the peak arc voltage was controlled by the background time by means of arc voltage feedback. The FLC was realized in a Look-Up Table (LUT) method. Experiments had been carried out aiming at implementing the control strategy to control the arc length change in welding process. Experimental results show that the controller proposed enables the consistency of arc length and the stability of arc voltage and welding process to be achieved in pulsed MIG welding process.

Application of Fuzzy Logic Controller for Development of Control Strategy in PHEV

In this paper, implantation of fuzzy logic controller for parallel hybrid electric vehicles （PHEV） is presented. In PHEV the required torque is generated by a combination of internal-combustion engine （ICE） and an electric motor. The controller simulated using the SIMULINK/MATLAB package. The controller is designed based on the desired speed for driving and the state of speed error. In the other hand, performance of PHEV and ICE under different road cycle is given. The hardware setup is done for electric propulsion system; the system contains the induction motor, the three phase IGBT inverter with control circuit using microcontroller. The closed loop control system used a DC permanent generator whose output voltage is related to motor speed. Comparison between simulation and experimental results show accurate matching.

Improvement of PV/T Based Reverse Osmosis Desalination Plant Performances Using Fuzzy Logic Controller

Photovoltaic based reverse osmosis desalination systems (PV/RO) present an effective method of water desalination especially in remote areas. The increase of the feed water temperature leads to an amelioration of the plant performances. Photovoltaic Thermal Collector (PV/T) represents an ideal power source as it provides both electric and thermal energies for the reverse osmosis process. Nevertheless, PV/T based RO plants should be controlled in order to solve operation problems related to electrical efficiency, reverse osmosis membrane, produced water and the rejected salts. This paper suggests a fuzzy logic controller for the flow rate of the circulating fluid into the PV/T collectors so as to ameliorate the system performances. The designed controller has improved the PV/T field electrical efficiency and preserved the reverse osmosis membrane which upgrades the system productivity. LABVIEW software is used to simulate the controlled system and validate the effectiveness of the controller.

A Fuzzy Logic Controller for Maximum Power Point Tracking with 8-Bit Microcontroller

This paper presents the implementation of maximum power point tracking （MPPT） with fuzzy logic controller. For cost consideration, an inexpensive 8-bit microcontroller, PIC 16F877A, is selected and programmed with C language and integer variables For evaluation, the implemented fuzzy logic controller （FLC） is compared with the MPPT controller of using perturbation and observation （P＆O）. Both types of MPPT controllers are tested on the same voltage source with a series-connected resistor. Experimental results show that the implemented FLC with appropriate design meets the control requirements of MPPT. The FLC based on linguistic fuzzy rules has more flexibility and intelligence than conventional P＆O controller, but the FLC spends more RAM and ROM spaces than the P＆O tracker does.

Fuzzy Logic Controlled Induction Motor Based Intelligent Controller

The indirect vector controlled IM （induction motor） drive involves decoupling of the stator current into torque and flux producing components. This paper proposes the implementation of a fuzzy logic control scheme applied to a two d-q current components model of an induction motor. An intelligent based on fuzzy logic controller is developed with the help of knowledge rule base for efficient control. The performance of fuzzy logic controller is compared with that of the proportional integral controller in terms of the settling time and dynamic response to sudden load changes. The harmonic pattern of the output current is evaluated for both fixed gain proportional integral controller and the fuzzy logic based controller. The performance of the IM drive has been analyzed under steady state and transient conditions. Simulation results of both the controllers are presented for comparison.

A Sender-Initiated Fuzzy Logic Contrnol Method for Network Load Balancing

In this paper, a sender-initiated protocol is applied which uses fuzzy logic control method to improve computer networks performance by balancing loads among computers. This new model devises sender-initiated protocol for load transfer for load balancing. Groups are formed and every group has a node called a designated representative (DR). During load transferring processes, loads are transferred using the DR in each group to achieve load balancing purposes. The simulation results show that the performance of the protocol proposed is better than the compared conventional method. This protocol is more stable than the method without using the fuzzy logic control.