An Intelligent Adaptive Fuzzy PID Controller Based on Multimodel Control Approach

A novel intelligent adaptive fuzzy PHD controller based on multimodel control approach is presented in this paper.It can improve the system performance of the dynamic time- varying system at various operating conditions.The fuzzy PHD controller is implemented by combining a fuzzy PI with a fuzzy PD controller in a parallel structure. The parameters of the fuzzy PHD controller are linked, via analytical derivation, to the gains of the linear PID controller. The sum of error square is used as performance criterion to locate the model that best reresents the process among the multiple models, The desired control output to drive the process along the desired path is generated only by modifying the output scale factots GU_I and GU_D of the fuzzy PID controller, Among the prescribed models, the control signal of the nearestmmodel to the system is applied. The system can be driven to its original trajectory because of the robustness of the fuzzy PID controller, Computer simulation results show that the adaptiv     

Small unmanned helicopters attitude controller by an on line adaptive fuzzy control system

Since small unmanned helicopter flight attitude control process has strong timevarying characteristics and there are random disturbances, the conventional control methods with unchanged parameters are often unworkable. An online adaptive fuzzy control system (AFCS) was designed, in a way that does not depend on a process model of the plant or its approximation in the form of a Jacobian matrix. Neither is it necessary to know the desired response at each instant of time. AFCS implement a simultaneous online tuning of fuzzy rules and output scale of fuzzy control system. The two cascade controller design with an inner (attitude controller) and outer controller (navigation controller) of the small unmanned helicopter was proposed. At last, an attitude controller based on AFCS was implemented. The flight experiment showed that the proposed fuzzy logic controller provides quicker response, smaller overshoot, higher precision, robustness and adaptive ability. It satisfies the needs of autonomous flight.     

Neural—networks—based Modelling and a Fuzzy Neural Networks Controller of MCFC

Molten Carbonate Fuel Cells(MCFC) are produced with a highly efficient and clean power generation technology which will soon be widely utilized.The temperature characters of MCFC stack are briefly analyzed.A radial basis function (RBF) neural networks identification technology is applied to set up the temperature nonlinear model of MCFC stack,and the identification structure,algorithm and modeling training process are given in detail.A fuzzy controllery of MCFC stack is designed.In order to improve its online control ability,a neural network trained by the I/O data of a fuzzy controller is designed.The neural networks can memorize and expand the inference rules of the fuzzy controller and substitute for the fuzzy controller to control MCFC stack online,A detailed design of the controller is given,The validity of MCFC stack modilling based on neural networks and the superior performance of the fuzzy neural networks controller are proved by Simulations.     

An Adaptive Model and Algorithm for an Electrohydraulic Position Servo System in Auto Gauge Control for Aluminum Hot Tandem Mill

The electrohydraulic servo position control system (HPC) is the core of an auto gap control for a modern fourhigh continuous hot strip mill. The actuators are loaded with considerable external disturbances, rolling forces, and the system stiffness and position accuracy will become hypersensitive to the leakage and the compressibility of the oil. Many efforts have being made to increase the position accuracies. The conventional resources are proportion integral differential (PID) controller. But the PID controller is faint for a considerable external disturbance. In this paper, by introducing the adaptive control strategy of model reference the reciprocities of the system structure with the loads were analyzed. With the Lyapunov energy function, an adaptive control algorithm applied to improve the system accuracy was formulated. The system simulations and the selection of parameters of the model were also discussed. The simulations show the static state errors at 0.02%. Finally, the industrial experimental result was given.     

The real time cascade generalized predictive control and application to a boiler circuit system

Boiler-circuit system in a circulating fluidized bed conrbustion boiler is a complex and typical industrial process with a large lag and time-delay. Conventional PID algorithm can not obtain satisfied performance, especially in the presence of disturbance. A cascade generalized predictive control (CGPC) strategy, is which the inner loop can restrain the disturbance while the outer loop can eliminate the offset, is proposed in this paper. We develop cascade GPC algorithm instead of conventional PID algorithm in the boiler-circuit system. Simulation on experimental boiler-circuit models of circulating fluidized bed combustion boiler shows strong robustness.     

Temperature modeling and control of Direct Methanol Fuel Cell based on adaptive neural fuzzy technology

Aiming at on-line controlling of Direct Methanol Fuel Cell （DMFC） stack, an adaptive neural fuzzy inference technology is adopted in the modeling and control of DMFC temperature system. In the modeling process, an Adaptive Neural Fuzzy Inference System （ANFIS） identification model of DMFC stack temperature is developed based on the input-output sampled data, which can avoid the internal complexity of DMFC stack. In the controlling process, with the network model trained well as the reference model of the DMFC control system, a novel fuzzy genetic algorithm is used to regulate the parameters and fuzzy rules of a neural fuzzy controller. In the simulation, compared with the nonlinear Proportional Integral Derivative （PID） and traditional fuzzy algorithm, the improved neural fuzzy controller designed in this paper gets better performance, as demonstrated by the simulation results.     

Feed-Forward-Like Decoupling Control in Coagulation Bath of Carbon Fiber Precursor

The coagulation bath system of carbon fiber precursor is a complicated and multivariable coupling system. Based on the model of industrial production, the full dynamic decoupling control of the coagulation bath system of carbon fiber precursor is achieved in combination with multivariable feed-forward-like decoupling and proportional-integral-differential （PID） control. Compared with the conventional PID decoupling control, the experiment results show that the proposed method has a better control effect. The use of the controller can achieve complete decoupling of three parameters from coagulation bath system. The method should have great applications.     

Numerical prediction of the incremental melting and solidification process

A mathematical formulation is applied to represent the phenomena in the incremental melting and solidification process (IMSP), and the temperature and electromagnetic fields and the depth of steel liquid phase are calculated by a finite difference technique using the control volume method. The result shows that the predicted values are in good agreement with the observations. In accordance with the calculated values for different kinds of materials and different size of molds, the technological parameter of the IMS process such as the power supply and the descending speed rate can be determined.     

Proportion Integration Differentiation (PID) Control Strategy of Belt Sander Based on Fuzzy Algorithm

Aiming at solving the problems of response lag and lack of precision and stability in constant grinding force control of industrial robot belts, a constant force control strategy combining fuzzy control and proportion integration differentiation(PID) was proposed by analyzing the signal transmission process and the dynamic characteristics of the grinding mechanism. The simulation results showed that compared with the classical PID control strategy, the system adjustment time was shortened by 98....     

Research on the Winding/Unwinding Control System Based on Fuzzy Control Theory

A fuzzy controller of the winding/unwinding control system used in jig-dyeing machine is introduced, which is superior to the one with conventional optimal PID controller in convergence speed and stability. Its mathematical model and transfer function are presented based on mechanism of the winding/unwinding control system. Simulation of the fuzzy controller carried out in the MATLAB （Simulink） environment proves that the control system based on fuzzy controller is superior in quality, precision and operation to a conventional optimal PID controller. The outlined experimental results also show the effectiveness and the robustness of the fuzzy PID controller in good dynamic performance, high robustness to parameter variation and disturbance.     

基于S7-200PLC的食品杀菌温度PID控制系统设计

针对食品杀菌过程中温度较难控制的问题,采用PLC中PID控制器进行解决,介绍了PID算法及S7-200PLC中PID回路指令的使用方法.说明了PID控制器在食品杀菌温度控制系统中的程序设计的全过程,该控制方法能满足实际生产需要.     

温度控制系统的无超调模糊-PID控制器设计

提出一种针对典型温度控制系统的模糊-PID控制策略,使得系统在无超调的情况下获得最短的调节时间,以节省设备投资.对传统模糊控制方法与PID参数整定进行了改进,仿真结果表明控制器设计方法简单实用,并有良好的控制效果.     

基于嵌入式微控制器的冻干试验机温度模糊控制系统设计

将模糊控制理论引入冻干试验机温度控制系统中,设计了基于嵌入式微控制器的模糊PID控制器,解决了常规PID控制温度超调大的问题;给出了模糊PID控制器的设计方法及冻干试验机控制电路的框图;将该系统以蕨菜为冻干物料进行了实验,获得了良好的温度响应曲线．     

带Smith预估器的模糊PID组织温度控制系统

针对激光热疗法中组织温度模型的纯滞后和大惯性,提出一种新颖的带Smith预估器的模糊PID控制系统.模糊PID控制器是由一个简单的模糊PI控制器和一个简单的模糊PD控制器并行结合而成.模糊PID控制器的增益通过解析推导与线性PID控制器的增益相联系.设计好的线性PID控制器的增益可用于在线设计模糊PID控制器.计算机仿真结果表明模糊控制系统在组织温度控制中比对应的线性PID控制系统鲁棒.     

热处理电阻炉炉温的自适应模糊PID控制

热处理电阻炉温度控制具有大的滞后性、非线性、难以获得准确数学模型的特点。目前热处理炉温度控制系统中常采用的PID控制器难以进一步提高温度控制系统的控制精度,无法与PC机进行通信,难以实现对热处理数据的管理。基于模糊控制无需精确数学模型和PID控制的良好稳态控制特性,本文选用单片机结合模糊PID控制策略对热处理加热炉进行了控制,减小了系统的调节时间,提高了温度控制精度。     

碳纤维激光石墨化炉温度控制系统的优化设计

碳纤维激光石墨化加热具有热源集中、升温迅速的特点,石墨化炉的温度控制系统主要采用传统PID控制器,存在惯性大、超调严重等缺点,并且PID控制器的3个参数(比例系数k_p、积分系数k_i和微分系数k_d)固定且主要依据经验获取。对于没有精确数学模型的PID控制系统,可以采用模糊控制对控制策略进行优化,但是模糊算法中模糊规则表的制定依旧主要源于经验所得,无法保证当前规则为最佳规则组合。针对上述问题,提出一种基于遗传算法的优化策略,对模糊规则表寻找全局最优解;借助MATLAB和Simulink环境进行编程仿真,结果表明,基于遗传算法的模糊PID控制效果在整体上优于传统PID控制和模糊PID控制,其响应时间短,控制精度高,无超调量,可用于碳纤维激光石墨化炉的温度控制系统设计。     

微机程序温度控制仪的研制

研制成功的微机程序温度控制仪,能按照微机存贮器中所给定的温度模式自动地控制炉温。这个温度模式可以模拟任何曲线或函数,可调出执行,也可根据需要进行改写。仪器上装有16位数码显示管,能够实时地显示编程过程和运行过程。此外,采用了非线性校正和PID调节规律。本仪器在炉温控制方面,为科研和生产提供了有力的手段。     

基于模糊PID的通用中档单片机温度控制系统设计

温度的控制有着十分广泛的应用,尝试设计一个具有普遍适用意义的中档单片机温度控制系统。该系统采用模糊PID方法进行温度控制,采用C8051F020单片机作为控制核心。该系统能克服普通的单片机PID温度控制系统的一些不足之处,达到较为理想的控制效果。阐述了该系统的模糊PID控制原理,介绍了该系统的硬件结构,给出了该系统的程序框图。     

一种采用时间最优控制的PID恒温控制器

本控制器由 80 31单片机、MC1 4 4 33A/ D转换器、双向晶闸管以及热敏电阻等组成 .采用了时间最优控制与 PID控制相结合的控制方案 ,很好地实现了对恒温箱的温度控制 .     

药剂温度控制系统的智能PID控制方法与实现

针对药剂温度控制系统，提出了一种基于模糊系统的自整定PID控制器，用于解决系统中出现的纯时滞，大惯性，时变不确定性等问题，实际运行结果表明，这种方法达到了良好的控制效果，降低了被控量超调，且增强了系统的鲁棒性。