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.

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.

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,

Intelligent Control on Hot Strip Coiling Temperature

A new intelligent control scheme for hot strip coiling temperature is presented. In this scheme, the prediction mode1 of finishing temperature and the presetting model of main cooling zone are establish based on BP neural network, the feed-forward open-loop control model of main cooling zone is constructed based on T-S fuzzy neural network, a new improved structure of T-S fuzzy neural network is developed, and the feedback close-loop control model of precision cooling zone is obtained based on fuzzy control. The effectiveness of the proposed scheme has been demonstrated by computer simulation with a satisfactory result.

Self-adaptive fuzzy controller with formulary rule for servo control of discharge gap in Micro EDM

In micro electrical discharge machining （micro EDM）, it is difficult for servo controlling the narrow discharge gap with the characters of non-linear and quick change. In this paper, aiming at solving the problems above, a self-adaptive fuzzy controller with formulary rule （SAFCFR） is presented based on the dual feedbacks composed by gap electric signal and discharge-ratio statistics. To ensure the properties of self-optimizing and fast stabilization, the formulary rule was designed with a tuning factor. In addition, the fast-convergence algorithms were introduced to adjust control target center and output scale factor. In this way, the normal discharge ratio can tend to the highest value during micro-EDM process. Experimental results show that the proposed algorithms are effective in improving the servo-control performance. According to the drilling-micro-EDM experiments, the machining efficiency is improved by 20% through applying SAFCFR. Moreover, SAFCFR is a prompt way to optimize parameters of discharge-gap servo control.

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.

Active-Disturbance-Rejection-Control for Temperature Control of the HVAC System

Heating, ventilation, and air conditioning (HVAC) system is significant to the energy efficiency in buildings. In this paper, temperature control of HVAC system is studied in winter operation season. The physical model of the zone, the fan, the heating coil and sensor are built. HVAC is a non-linear, strong disturbance and coupling system. Linear active-rejection-disturbance-control is an appreciate control algorithm which can adapt to less information, strong-disturbance influence, and has relative-fixed structure and simple tuning process of the controller parameters. Active-rejection-disturbance-control of the HVAC system is proposed. Simulation in Matlab/Simulink was done. Simulation results show that linear active-rejection-disturbance-control was prior to PID and integral-fuzzy controllers in rising time, overshoot and response time of step disturbance. The study can provide fundamental basis for the control of the air-condition system with strong-disturbance and high-precision needed.

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.

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.

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.

Simulation and analysis of a Truck Model’s ride comfort based on fuzzy adaptive control theory

This paper tried to analyse and verify the fuzzy adaptive control strategy of electronic control air suspension system for heavy truck. Created the seven-freedoms vehicle suspension model, and the road input model; with Matlab/Simulink toolboxes and modules, built dynamical system simulation model for heavy truck with air suspension, fuzzy adaptive control model, height control model for air spring, and intelligent control and analyse on root mean square value of acceleration of gravity center of the vehicle under excitation of road. Results show that the fuzzy control had less help to the body vibration on the better pavement, but had the better benefit on the bad road, and the vehicle’s root mean square value of acceleration of gravity center is less than passive suspension’s obviously.

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.

Thermal Compensation and Fuzzy Control for Developing a High-Precision Optical Lens Mold

Precision plastic lenses often exhibit dimensional deviations due to the thermal expansion of the mold during injection molding.Although this deviation is smaller in micron-sized(1–5μm)lenses,it exceeds the tolerance requirement of such lenses.It is difficult to resolve this dimensional issue by using injection molding parameters(e.g.,melt temperature,injection speed,and hold pressure).In this study,the thermal analysis of a mold was conducted,and it was confirmed that the deviation of lens dimension was caused by the thermal instability and thermal expansion of the mold.Due to the inconsistent heat distribution of the fixed and the movable side of the mold,the position of the location system was displaced approximately 1 to 5μm.In this study,thermal compensation technology for this the mold was investigated.The temperature on both sides of the mold was measured,and mold temperature could be adjusted automatically using a control strategy based on fuzzy theory.During the mold preheating or mass production stage,the temperature on both sides of the mold could be easily adjusted to quickly obtain the required temperature range.The dilatation on both sides of the mold was revised to improve the alignment accuracy of the cavity,and the decenter error of these injection lenses was reduced to 1μm.This technology can markedly improve the production yield and efficiency of plastic products requiring an extremely high dimensional accuracy.

Application of Fuzzy Control into a New Kind of Sea Water Still

A double level multi variable controller, which is designed to regulate the temperature of sea water, is applied into a new kind of sea water still.An algorithm of the controller adopting the theory of fuzzy control is processed computationally via hardware. According to the results of operation and test upon the spot, the advantages for this controlling system, namely, rapid response, high precision, and good reliability, are obtained.

基于LabVIEW的Fuzzy-PID温度控制系统的设计

针对电子束加热是在真空室中进行,能量密度高、工件温度变化快、控制难度大、数学模型难以建立等特点,提出了系统解决方案及控制机理。利用LabVIEW软件中的模糊逻辑模块(Fuzzy Logic)及仿真模块(Simulation Module)建立系统仿真程序,并通过仿真曲线获得优化参数。实验表明,该控制系统具有动态响应快、调整时间短、稳态误差小、超调量小等特点,从而证明了在以高能密度的电子束为加工热源过程中,采用Fuzzy-PID控制技术对被加工件温度进行控制,可以获得理想的控制效果。

陀螺Fuzzy-PID温度控制系统研究

对于具有大时间延迟环节并难以建立精确数学模型的陀螺温度控制系统,提出采用模糊自整定PID控制参数的Fuzzy-PID陀螺温度控制方法。该方法可以集模糊控制与PID控制之所长,有较好的抗干扰能力。温控及高低温实验证明,该系统可以达到所要求的快速启动、输出稳定并能较好适应工作环境变化等精度要求。

基于FUZZY-PID的主汽温控制

基于ＳＴＡＮ－９０火电机组全仿真机系统平台，选用全论域范围内带自调整因子的模糊控制器与ＰＩ控制器相结合的复合控制方案设计过热器减温控制系统：编程建立相关模糊控制算法并组态实现了控制系统功能．动态试验结果表明，与常现ＰＩＤ串级控制系统相比该系统达到了更好的动、静态性能。

基于Fuzzy-PID的MOCVD温度控制方法

针对MOCVD系统反应室温度的特性和对温度控制的要求,提出了一种基于Fuzzy-PID的温度控制方案,即利用模糊控制求得归一化的PID参数变化系数,从而实现PID参数的在线自调整.与Smith预估控制相比,Fuzzy-PID具有更好的控制效果,较好地解决了系统中存在的“非线性”、“大滞后”、“物理模型不精确”等问题,满足MOCVD控制系统温度控制要求.

基于Smith-Fuzzy控制的温度控制系统的设计

介绍了Smith预估器与模糊控制相结合的温度控制系统 ,该方法解决了传统Smith控制系统过分依赖被控对象的精确模型 ,且实现简单 。

基于Fuzzy-PI双模控制的控制系统

叙述了孵化装置中有关温度与湿度的控制方法。为了提高控制精度、改善系统的动态、稳态性能,引入了基于Fuzzy-PI双模控制方法,并利用Matlab进行仿真。通过仿真和实际运行表明,采用了Fuzzy-PI双模控制以后,加快了动态响应,提高了控制精度,有效地降低了超调量,孵化率达到了规定的技术指标。对于实际中存在的非线性、大滞后、大惯性、难以建立数学模型的系统,采用该控制方法,不失为一种好的策略。