Controlling Torque Distribution for Parallel Hybrid Vehicle Based on Hierarchical Structure Fuzzy Logic

The Hierarchical Structure Fuzzy Logic Control (HSFLC) strategies of torque distribute for Parallel Hybrid Electric Vehicle (PHEV) in the mode of operation of the vehicle i. e. , acceleration, cruise, deceleration etc. have been studied. Using secondly developed the hybrid vehicle simulation tool ADVISOR, the dynamic model of PHEV has been set up by MATLAB/SIMULINK. The engine, motor as well as the battery characteristics have been studied. Simulation results show that the proposed hierarchical structured fuzzy logic control strategy is effective over the entire operating range of the vehicle in terms of fuel economy. Based on the analyses of the simulation results and driver’s experiences, a fuzzy controller is designed and developed to control the torque distribution. The controller is evaluated via hardware-in-the-loop simulator (HILS). The results show that controller verify its value.

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.

A 16-bit 18-MSPS flash-assisted SAR ADC with hybrid synchronous and asynchronous control logic

This paper presents a 16-bit,18-MSPS(million samples per second)flash-assisted successive-approximation-register(SAR)analog-to-digital converter(ADC)utilizing hybrid synchronous and asynchronous(HYSAS)timing control logic based on an on-chip delay-locked loop(DLL).The HYSAS scheme can provide a longer settling time for the capacitive digital-to-analog converter(CDAC)than the synchronous and asynchronous SAR ADC.Therefore,the issue of incomplete settling or ringing in the DAC voltage for cases of either on-chip or off-chip reference voltage can be solved to a large extent.In addition,the fore-ground calibration of the CDAC’s mismatch is performed with a finite-impulse-response bandpass filter(FIR-BPF)based least-mean-square(LMS)algorithm in an off-chip FPGA(field programmable gate array).Fabricated in 40-nm CMOS process,the proto-type ADC achieves 94.02-dB spurious-free dynamic range(SFDR),and 75.98-dB signal-to-noise-and-distortion ratio(SNDR)for a 2.88-MHz input under 18-MSPS sampling rate.

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.

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.

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.

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.

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.

Logical and Timing Control for Diagnostic Neutral Beam Injection on HT-7

The timing and master control logic （MCL） units are the most important function units of the diagnostic neutral beam （DNB） power supply control system. The units control the operation of nine power supply subsystems of the DNB system, and provide protection for the DNB system from faults such as beam source arc down. Based on the characteristics of the DNB power supply system, the timing and MCL units have been designed, fabricated and tested. Experiments prove that the timing unit is convenient, flexible and reliable, and the MCL is functional.

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.

Adaptive Sliding Mode Control for MIMO Nonlinear Systems Based on Fuzzy Logic Scheme

In this study an indirect adaptive sliding mode control (SMC) based on a fuzzy logic scheme is proposed to strengthen the tracking control performance of a general class of multi-input multi-output (MIMO) nonlinear uncertain systems. Combining reaching law approach and fuzzy universal approximation theorem, the proposed design procedure combines the advantages of fuzzy logic control, adaptive control and sliding mode control. The stability of the control systems is proved in the sense of the Lyapunov second stability theorem. Two simulation studies are presented to demonstrate the effectiveness of our new hybrid control algorithm.

Design of a Fuzzy Logic Based Controller for Fluid Level Application

In industrial process control, fluid level control is one of the most basic aspects. Many control methods such as on-off, linear and PID (Proportional Integral Derivative) were developed time by time and used for precise controlling of fluid level. Due to flaws of PID controller in non-linear type processes such as inertial lag, time delay and time varying etc., there is a need of alternative design methodology that can be applied in both linear and non-linear systems and it can be execute with fuzzy concept. By using fuzzy logic, designer can realize lower development cost, superior feature and better end product. In this paper, level of fluid in tank is control by using fuzzy logic concept. For this purpose, a simulation system of fuzzy logic controller for fluid level control is designed using simulation packages of MATLAB software such as Fuzzy Logic Toolbox and Simulink. The designed fuzzy logic controller first takes information about inflow and outflow of fluid in tank than maintain the level of fluid in tank by controlling its output valve. In this paper, a controller is designed on five rules using two-input and one-output parameters. At the end, simulation results of fuzzy logic based controller are compared with classical PID controller and it shows that fuzzy logic controller has better stability, fast response and small overshoot.

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.

Systematic Logic Controller Design as Sequential Function Chart Starting from Informal Specifications

Today＇s automation industry is driven by the need for an increased productivity, higher flexibility, and higher individuality, and characterized by tailor-made and more complex control solutions. In the processing industry, logic controller design is often a manual, experience-based, and thus an error-prone procedure. Typically, the specifications are given by a set of informal requirements and a technical flowchart and both are used to be directly translated into the control code. This paper proposes a method in which the control program is constructed as a sequential function chart （SFC） by transforming the requirements via clearly defined intermediate formats. For the purpose of analysis, the resulting SFC can be translated algorithmically into timed automata. A rigorous verification can be used to determine whether all specifications are satisfied if a formal model of the plant is available which is then composed with the automata model of the logic controller （LC）.

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 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.

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.