SOFC temperature evaluation based on an adaptive fuzzy controller

The operating temperature of a solid oxide fuel cell (SOFC) stack is a very important parameter to be controlled, which impacts the performance of the SOFC due to thermal cycling. In this paper, an adaptive fuzzy control method based on an affine nonlinear temperature model is developed to control the temperature of the SOFC within a specified range. Fuzzy logic systems are used to approximate nonlinear functions in the SOFC system and an adaptive technique is employed to construct the controller. Compared with the traditional fuzzy and proportion-integral-derivative (PID) control, the simulation results show that the designed adaptive fuzzy control method performed much better. So it is feasible to build an adaptive fuzzy controller for temperature control of the SOFC.

Development of single-chip fuzzy controller based on FFSI in binary

Length and concise structure of fuzzy logic reasoning program and its real-time reasoning characteris-tic have their effect on the performance of a digital single-chip fuzzy controller. The control effect of a digitalfuzzy controller based on looking up fuzzy control responding table is only relative to the table and not relative tothe fuzzy control rules in the practical control process. Aiming at above problem and having combined fuzzy log-ic reasoning with digital operational characteristics of a single-chip microcomputer, functioning-fuzzy-subset in-ference (FFSI) in binary, in which triangle membership functions of error and error-in-change are all represen-ted in binary and singleton membership functions of control variable is binary too, has been introduced. The cir-cuit principle plans of a single-chip fuzzy controller have been introduced for development of its hardware, andthe primary program structure, fuzzy logic reasoning subroutine, serial communication subroutine with PC andreliability design of the fuzzy controller are all discussed in detail. The control of indoor temperature by a fuzzycontroller has been conducted using a testing-room thermodynamic system. Research results show that the FFSIin binary can exercise a concise fuzzy control in a single-chip fuzzy controller, and the fuzzy controller is there-fore reliable and possesses a high performance-price ratio.

Design of Fuzzy Controller for Central Air Conditioner

A structure of central air conditioning system in building and its running pattern are proposed in order to perform optimum energy saving strategy. The design of room temperature controller is taken as an example to discuss the design of fuzzy controller using common microprogrammed control unit (MCU) in detail. Based on fuzzy theory the query control tables fixed in read only memory (ROM) of MCU are established to realize the energy saving in the room temperature controller and the reasoning procedure is analyzed. The diagram of hardware design and the flow chart of software of room temperature controller are presented. The results show that the proposed method is practical and effective to achieve the energy saving goal.

Enhancing the efficiency of cabin heaters in emergency shelters after earthquakes through an optimized fuzzy controller

In just one and half minutes,more than fifty thousand died due to the 7.7 and 7.6 magnitude earthquakes that struck Turkey’s southeast on February 6,2023;thousands of families who barely escaped struggled to survive in the freezing weather.A warm shelter was the most basic requirement of these families.Container buildings are a rapid and easy solution to this issue.However,there is a need for a more effective and safe heating option than a wood fire for these buildings.In this study,cabin heaters,which allow truck drivers to warm up when they park their vehicles to sleep,are specially optimized for emergency shelters after an earthquake.An optimized fuzzy controller was developed to use in such buildings,which allows an air–fuel ratio in the combustion chamber of the cabin heater to be controlled adaptively based on system dynamics to get lower carbon emissions and fuel consumption.The TRNSYS software was used to establish the transient simulation model of a cabin heater with a capacity of 4 kW for a typical 21 m^(2) shelter building in Turkey’s cold regions.The developed fuzzy controller carried out the heating process of this shelter from the 15th of November to the 15th of March.Instead of using expert knowledge,the Gray Wolf Optimization(GWO)method was applied to optimize the fuzzy controller parameters developed for the cabin heater.With the optimized fuzzy controller,the fuel consumption at the end of the heating season was reduced by an average of 0.2 L/h,and the cabin heater’s efficiency increased by more than 13%.Our simulation results show that the intelligent controller we developed could improve diesel fuel combustion efficiency by up to 85%.

Fuzzy Control Optimization of Loading Paths for Hydroforming of Variable Diameter Tubes

The design of the loading path is one of the important research contents of the tube hydroforming process.Optimization of loading paths using optimization algorithms has received attention due to the inefficiency of only finite element optimization.In this paper,the hydroforming process of 5A02 aluminum alloy variable diameter tube was as the research object.Fuzzy control was used to optimize the loading path,and the fuzzy rule base was established based on FEM.The minimum wall thickness and wall thickness reduction rate were determined as input membership functions,and the axial feeds variable value of the next step was used as output membership functions.The results show that the optimized loading path greatly improves the uniformity of wall thickness and the forming effect compared with the linear loading path.The round corner lamination rate of the tube is 91.2%under the fuzzy control optimized loading path,which was increased by 47.1%and 22.6%compared with linear loading Path 1 and Path 2,respectively.Based on the optimized loading path in the experiment,the minimum wall thickness of the variable diameter tube was 1.32 mm and the maximum thinning rate was 12.4%.The experimental results were consistent with the simulation results,which verified the accuracy of fuzzy control.The research results provide a reference for improving the forming quality of thin-walled tubes and plates.

Greenhouse Environmental Control Using Optimized, Modeled and Simulated Fuzzy Logic Controller Technique in MATLAB SIMULINK

The main objective of this study is the control of the agricultural greenhouse in view of the economic interest generated by such an activity. A simulation model is developed, gathering all the external and internal climatic conditions that influence the microclimate of the greenhouse to predict the temporal evolution of the state variables characterizing this microclimate. The fuzzy control is an alternative to the approaches proposed by the automatic for the control of complex systems. The performance objectives of the looped systems and the corresponding actions are summarized in the form of rules of expertise, which are spelled out in plain language. This technique thus makes it possible to dispense with the use of mathematical models which are sometimes difficult to obtain. Our objective is the multivariable strategy synthesis and the fuzzy application to a multivariate system （MIMO ~ such as the agricultural greenhouse.） First, the principles of fuzzy logic and fuzzy control are recalled. The origins of non-Linearitys of the command are explained. One of the practical problems of this technique is the combinatorial explosion of the rule base when the number of variables involved becomes large. A solution to simplify the complexity of the system is presented together with an optimization algorithm to automatically adjust the parameters of the fuzzy controller. The last part is devoted to the synthesis of an optimal control of the greenhouse in order to compare it to the fuzzy control implemented.

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.

Modeling and simulation of temperature control system in plant factory using energy balance

Closed production systems,such as plant factories and vertical farms,have emerged to ensure a sustainable supply of fresh food,to cope with the increasing consumption of natural resource for the growing population.In a plant factory,a microclimate model is one of the direct control components of a whole system.In order to better realize the dynamic regulation for the microclimate model,energy-saving and consumption reduction,it is necessary to optimize the environmental parameters in the plant factory,and thereby to determine the influencing factors of atmosphere control systems.Therefore,this study aims to identify accurate microclimate models,and further to predict temperature change based on the experimental data,using the classification and regression trees(CART)algorithm.A random forest theory was used to represent the temperature control system.A mechanism model of the temperature control system was proposed to improve the performance of the plant factories.In terms of energy efficiency,the main influencing factors on temperature change in the plant factories were obtained,including the temperature and air volume flow of the temperature control device,as well as the internal relative humidity.The generalization error of the prediction model can reach 0.0907.The results demonstrated that the proposed model can present the quantitative relationship and prediction function.This study can provide a reference for the design of high-precision environmental control systems in plant factories.

Temperature Intelligent Control System of Large-Scale Standing Quench Furnace

Considering some characteristics of large-scale standing quench furnace, such as great heat inertia, evident time lag, strong coupling influence, hard to establish exact mathematical models of plant and etc, an artificial intelligent fuzzy control algorithm is put forward in this paper. Through adjusting the on-off ratio of electric heating elements, the temperature in furnace is controlled accurately. This paper describes structure and qualities of the large-scale standing quench furnace briefly, introduces constitution of control system, and expounds principle and implementation of intelligent control algorithm. The applied results prove that the intelligent control system can completely satisfy the technological requirements. Namely, it can realize fast increasing temperature with a little overshoot, exact holding temperature, and well-distributed temperature in quench furnace. It has raised the output and quality of aluminum material, and brought the outstanding economic and social benefits.

FUZZY GLOBAL SLIDING MODE CONTROL BASED ON GENETIC ALGORITHM AND ITS APPLICATION FOR FLIGHT SIMULATOR SERVO SYSTEM

To alleviate the chattering problem, a new type of fuzzy global sliding mode controller （FGSMC） is presented. In this controller, the switching gain is estimated by fuzzy logic system based on the reachable conditions of sliding mode controller（SMC）, and genetic algorithm （GA） is used to optimize scaling factor of the switching gain, thus the switch chattering of SMC can be alleviated. Moreover, global sliding mode is realized by designing an exponential dynamic sliding surface. Simulation and real-time application for flight simulator servo system with Lugre friction are given to indicate that the proposed controller can guarantee high robust performance all the time and can alleviate chattering phenomenon effectively.

Fuzzy self-tuning PID control of the operation temperatures in a two-staged membrane separation process

A two-staged membrane separation process for hydrogen recovery from refinery gases is introduced. The principle of the gas membrane separation process and the influence of the operation temperatures are analyzed. As the conventional PID controller is difficult to make the operation temperatures steady, a fuzzy self-tuning PID control algorithm is proposed. The application shows that the algorithm is effective, the operation temperatures of both stages can be controlled steadily, and the operation flexibility and adaptability of the hydrogen recovery unit are enhanced with safety. This study lays a foundation to optimize the control of the membrane separation process and thus ensure the membrane performance.

Optimization of the Plugging Agent Dosage for High Temperature Salt Profile Control in Heavy Oil Reservoirs

After steam discharge in heavy oil reservoirs,the distribution of temperature,pressure,and permeability in different wells becomes irregular.Flow channels can easily be produced,which affect the sweep efficiency of the oil displacement.Previous studies have shown that the salting-out plugging method can effectively block these channels in high-temperature reservoirs,improve the suction profile,and increase oil production.In the present study,the optimal dosage of the plugging agent is determined taking into account connection transmissibility and inter-well volumes.Together with the connectivity model,a water flooding simulation model is introduced.Moreover,a non-gradient stochastic disturbance algorithm is used to obtain the optimal plugging agent dosage,which provides the basis for the high-temperature salting-out plugging agent adjustment in the field.

基于Fuzzy-PID的棉花打顶升降装置设计与试验

为解决棉花打顶机作业过程中由于仿形时与刀盘移动滞后、定位精准度低,导致的棉花漏打、过打及伤苗的问题,基于模糊控制技术对棉花打顶装置高度控制系统进行研究。以3MDZF-6棉花打顶机升降系统为分析对象,确定了刀盘在升降过程中的定位精度要求。以液压阀-液压缸为对象,在AMESim中建立打顶升降装置的控制模型,并将其导入到MatLab中,设计相应的模糊规则和模糊控制器,对其进行仿真分析,从超调量和响应时间两方面验证了PID和模糊PID控制方法的可行性。仿真结果表明:无外界干扰的情况下,PID参数分别为100800、500、30时,输入信号达到稳态的响应时间为0.55s;模糊PID控制下输入信号达到稳态的响应时间为0.31s。经过对比分析固定参数PID控制和模糊PID控制在不同扰动下的控制效果,发现模糊PID控制系统的超调量为0.84%,输入信号达到稳态所需的时间为0.39s,小于固定参数PID的0.64s。该方法实现了打顶升降装置的位移控制,提高了刀盘的定位精度及控制系统的抗干扰性和鲁棒性,可为棉田环境下的棉花打顶升降装置的精确控制问题提供借鉴。

Automobile active suspension system with fuzzy control

A quarter-automobile active suspension model was proposed. High speed on/off solenoid valves were used as control valves and fuzzy control was chosen as control method . Based on force analyses of system parts, a mathematical model of the active suspension system was established and simplified by linearization method. Simulation study was conducted with Matlab and three scale coefficients of fuzzy controller (ke, kec, ku) were acquired. And an experimental device was designed and produced. The results indicate that the active suspension system can achieve better vibration isolation performance than passive suspension system, the displacement amplitude of automobile body can be reduced to 55%. Fuzzy control is an effective control method for active suspension system.

Neuro-fuzzy generalized predictive control of boiler steam temperature

Power plants are nonlinear and uncertain complex systems. Reliable control of superheated steam temperature is necessary to ensure high efficiency and high load-following capability in the operation of modem power plant. A nonlinear generalized predictive controller based on neuro-fuzzy network （NFGPC） is proposed in this paper. The proposed nonlinear controller is applied to control the superheated steam temperature of a 200MW power plant. From the experiments on the plant and the simulation of the plant, much better performance than the traditional controller is obtained,

Application of Fuzzy Control to Improve Flow Balance of Multi-Cavity Hot Runner System

In this study, we propose a new temperature compensation control strategy for a multi-cavity hot runner injection molding system, At first, the melt filling time of each cavity can be measured by installing temperature sensors on the position around end filling area, and filling time difference between the various cavities can be calculated. Then the melt temperature of each hot nozzle can be adjusted automatically by a control strategy established based on the Fuzzy Theory and a program compiled with LABVIEW software. Temperature changes the melt mobility, so the adjustment of temperature can equalize the filling time of the melt in each cavity, which can reduced the mass deviation between each cavity and make product properties of each cavity consistent. The conclusion of the experiment is as follows： For this contact lens box of a four-cavity Hot Runner mold, by applying hot runner temperature compensation control system, time difference can be reduced from 0.05 s to 0.01 s at each cavity, and the mass Standard deviation of the four cavity can be improved from 0.006 to 0.002. The ratio of imbalance can be reduced from 20% to 4%. Hence, the hot runner temperature compensation control system has significant feasibility and high potential in improving melt flow balance of multi-cavity molding application.

Simulation of fuzzy control systems for nonferrous alloy vacuum counter-pressure casting

Through simulation analyses of vacuum counter-pressure casting fuzzy control systems based on MATLAB, fuzzy control systems designed by simulation can track technical route established well. When transmission functions of vacuum counter-pressure casting controlled objects are changed in operation, fuzzy control systems can carry on self-regulation and stabilize quickly, and embody the advantages of fleet response velocity and little adjusting quantity. The design of vacuum counter-pressure casting fuzzy control systems is accelerated and improved greatly by simulation based on MATLAB. Meanwhile, their design is accurate and reliable. Moreover, microstructure and properties of thin-wall aluminum alloy castings are improved effectively by using fuzzy control systems.

Simulating a fuzzy level controller for flotation columns

Level control in flotation columns is an important factor that influences the recovery and the grade of concentrate from the column. A flotation column is a nonlinear, multi-variable problem with changeable parameters that traditional methods have difficulty controlling. We have applied fuzzy control methods to the flotation column and tested the performance of the design by Matlab/Simulink simulation. The simulations show that level control in the flotation column becomes smoother and more rapid with the fuzzy controller. Compared to PID control methods the overshoot in valve position, the adjustment time, and the robustness of the controller are all improved. This indicates that it is suitable to model fuzzy controllers in applications for the study of automatic control of flotation column.

Temperature Control and Simulation of Temperature-Altitude Test System

The temperature-Altitude Test System(TATS) supplies various testing environments.The traditional PID method controls the temperature in TATS Temperature-Pressure Cabin(TPC) over a long adjusting time and with a large overshoot.In order to solve this problem simply,a temperature control strategy with temperature difference corresponding factors is presented through a dynamic analysis and modeling of TPC temperature change.The TPC temperature descending process is simulated,and the results show that this control strategy can allot the proportion of PID heating controller and PID cooling controller in the whole control process and TPC temperature can be controlled at a set point quickly and effectively.

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.