An Adaptive Neuro-Fuzzy Inference System to Improve Fractional Order Controller Performance

The design and analysis of a fractional order proportional integral deri-vate(FOPID)controller integrated with an adaptive neuro-fuzzy inference system(ANFIS)is proposed in this study.Afirst order plus delay time plant model has been used to validate the ANFIS combined FOPID control scheme.In the pro-posed adaptive control structure,the intelligent ANFIS was designed such that it will dynamically adjust the fractional order factors(λandµ)of the FOPID(also known as PIλDµ)controller to achieve better control performance.When the plant experiences uncertainties like external load disturbances or sudden changes in the input parameters,the stability and robustness of the system can be achieved effec-tively with the proposed control scheme.Also,a modified structure of the FOPID controller has been used in the present system to enhance the dynamic perfor-mance of the controller.An extensive MATLAB software simulation study was made to verify the usefulness of the proposed control scheme.The study has been carried out under different operating conditions such as external disturbances and sudden changes in input parameters.The results obtained using the ANFIS-FOPID control scheme are also compared to the classical fractional order PIλDµand conventional PID control schemes to validate the advantages of the control-lers.The simulation results confirm the effectiveness of the ANFIS combined FOPID controller for the chosen plant model.Also,the proposed control scheme outperformed traditional control methods in various performance metrics such as rise time,settling time and error criteria.

Study on Fuzzy Self-Adaptive PID Control System of Biomass Boiler Drum Water

The paper discusses the features of the Biomass Boiler drum water level. Conventional PID Control System can not reach a satisfaction result in nonlinearity and time different from Biomass Boiler Drum Water Control System. In this study, a kind of fuzzy self-adaptive PID controller is described and this controller is used in biomass boiler’s drum water level control system. Using the simulink tool of MATLAB simulation software to simulate the fuzzy adaptive PID and conventional PID control system, the result of the comparison shows that the fuzzy self-adaptive PID has the strong anti-jamming, flexibility and adaptability as well as the higher control precision in Biomass Boiler Drum Water.

Fuzzy adaptive PID control on hydraulic servo system of quadruped robot

Quadruped robot driven by high power density hydraulic device works in unstructured en- vironment. With variable load and various external disturbance, the hydraulic servo system has fea- tures such as nonlinear, time-varying parameters. Traditional control method has some limitation. In order to help the hydraulic servo system of the quadruped robot to adapt to harsh environments, and to obtain high control quality and control precision, an incremental fuzzy adaptive PID controller based on position feedback is designed to solve the related technical problems. Matlab/Simulink sim- ulation and experimental results show that the incremental fuzzy adaptive PID controller improves the dynamic performance of the system, enhances the respond speed and precision of the hydraulic ser- vo system, and has some theory significance and practical value.

Application of Single Neuron Adaptive PID Regulators with Auto-tuning Gain in Industrial Parameter(Pressure)Closed-loop Process Control Systems

A type of single neuron adaptive PID regulator with auto-tuning gain is proposed and applied to the work control of fans, waterpumps and air-pressers etc. in Handan Iron & Steel Compel China. The robusthess of induStrial parameter closed-loop process controlsystems is improved, and the work quality of the systems bettered.

The control of welding wire feed self-adaptive mechanism based on fuzzy PID

The welding wire feed mechanism is an important component of welding equipment, both reliability and stabilization are the premise that the welding quality can be ensured. The PID is currently adapted to control the welding wire feed mechanism, although the fuzzy PID has advantage of fast response and adaptation, the precision of fuzzy PID is lower. Accordingly, the fuzzy self-adaptive PID controller was proposed through changing fuzzy input variables and output variables based on variable universe, simple furwtion is adopted as scaling factor, the fuzzy PID controller parameters are adjusted to improve the precision and adjustment range. Simulation results show that control effects of fuzzy self-adaptive PID adopted by the welding wire feed mechanism have good adaptive ability and robustness based on variable universe, the welding experiments indicate that the welding quality met the requirements actually.

Design of Adaptive Fuzzy PID Altitude Control System for Unmanned Aerial Vehicle

Based on Matlab/Simulink and Fuzzy Logic toolboxes, the altitude control system is designed and simulated. The validity of conventional PID control method and adaptive fuzzy PID control method is compared. It can be drawn out that the adaptive fuzzy PID control method is superior to the conventional PID in rising time and overshoot etc. The effectiveness of a fuzzy PID controller shows potential application in the future, especially in the presence of model uncertainty or changing dynamics and time-varying parameters.

The Application and Simulation of Fuzzy Adaptive PID in Household Heating Metering System

After heat is metered in each house unit,the heating system is regulated by variable flow.The temperature of the return w ater is controlled to regulate the flow to realize the temperature regulation.According to the characteristics of the temperature control w ith big inertia,pure time-delay and degeneration,a fuzzy adaptive PID controller is designed w ith the advantages of the fuzzy control and PID algorithm,and the simulation model is established according to the characteristics of heating metering system.Simulation results show that the fuzzy adaptive PID controller proposed has small overshoot,short oscillation cycle,high precision and strong anti-jamming capability in comparison w ith conventional PID controller,w hich could meet the requirement of the dynamic and steady-state performance of the heating process.

基于PLC的换热站Fuzzy-adaptive-PID控制策略简析

在换热站供热控制系统中引用Fuzzy-adaptive-PID控制策略,实时调整二次网热水的温度。换热站采用工业控制领域应用最广泛的PLC座位控制核心,采集换热站各项参数,实时监测外接环境温度变化,控制一次网调节阀,自动调节二次网的温度,使其保持在用户需要的范围内。实测结果表明,利用西门子PID控制模块,结合Fuzzy-adaptive-PID控制策略,应用数据分析和计算,实现供热相关指标的预测,并且消除了系统迟滞性的缺点,运行指令直接下发到每一台换热机组,形成了完整的闭环控制,从而提高换热站的运行效率。

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

基于模糊自适应PID的汽车硅油风扇离合器性能测试系统研究

以汽车硅油风扇离合器为研究对象,结合单片机和传感器技术,开发出性能测试系统.提出模糊自适应PID动态控制算法,设计控制器控制温度,利用速度传感器检测风扇转速,对测试系统进行整体设计,给出了硬件总体设计框图,设计模拟量输入输出电路,并设计对应的软件系统.实验结果表明:测试系统升降温速率最高不超过8.5℃/min,耦合区加温速率约为2.3℃/min,分离区降温速率约为6.6℃/min,系统性能稳定,符合标准.

基于模糊PID控制的粉碎机转速和位置自适应控制研究

为提高粉碎机的控制性能,提出一种基于模糊PID控制的粉碎机转速和位置自适应控制算法。方法以粉碎机STM86步进电机控制为研究对象,构建粉碎机驱动电机数学模型,并结合PID控制和模糊控制设计基于模糊PID控制算法,以实现粉碎机的自适应控制。结果表明,模糊PID控制算法对粉碎机速度和位置控制的超调量分别为4.20%和0.13%,调节时间分别为0.21 s和0.02 s、平均跟随误差分别为0.02 mm和0.01 r/min;相较于PID控制、模糊滑模控制、模糊自抗干扰控制算法,模糊PID控制算法具有更低的超调量,更短的调节时间和更小的平均跟随误差。由此得出,模糊PID控制方法可实现更优异的粉碎机自适应控制,且具有一定的实际应用价值。

基于模糊自适应PID控制器的夹具自适应控制研究

为提高夹具自适应控制的稳定性和响应速度,以电磁无心夹具为研究对象,提出一种基于模糊自适应比例-积分-微分(proportion integration differentiation, PID)控制器的控制方法。首先构建夹具数学模型,然后结合模糊控制和PID控制的优势,构建模糊自适应PID控制器对夹具进行自适应控制,最后通过在MATLAB软件上进行仿真。结果表明,该方法实现了阶跃信号、突加负载、正弦信号输入等不同条件下的夹具控制,且具有优异的控制性能。整个控制过程中,该方法超调量为2.11%,响应时间0.08 s。相较于PID控制器、模糊控制器、自抗扰控制器、模糊滑模控制器,该方法提高了夹具自适应控制的精度和响应速度,且可用于实际夹具自适应控制中,具有一定的实际应用价值。

基于多传感器融合的模糊PID采煤机截割路径自适应控制方法

截割路径自适应控制是提高采煤机生产效率和质量的重要手段,但现行方法控制精度较低,在实际中,截割路径RMSE、MAE均比较高。针对现行方法存在的不足和缺陷,提出基于多传感器融合的模糊PID采煤机截割路径自适应控制方法。采用多传感器融合技术感知采煤机截割运动学模型中位置及状态信息,并对多传感器数据融合处理,根据采煤机截割运动学规律得到采煤机截割路径,模糊化截割路径偏差,利用PID控制器调控比例、积分、微分3个参数,修正采煤机截割路径偏差,实现基于多传感器融合的模糊PID采煤机截割路径自适应控制。实验证明,设计方法应用下的采煤机截割路径RMSE和MAE得到了明显降低,为采煤机截割路径自适应控制提供了一定参考。

基于自适应模糊PID算法的锂电池组双层均衡控制

为提高电池重组时的均衡效率,在传统Buck-Boost均衡拓扑电路的基础上,设计了一种锂电池组双层均衡拓扑电路。组内采用Buck-Boost电路均衡,组间利用双向反激变压器进行均衡。均衡控制策略采用自适应模糊PID算法,以电池荷电状态(state of charge, SOC)为均衡变量,利用模糊控制算法对PID参数进行调节,缩短了均衡时间,提高了均衡效率。在Matlab/Simulink中搭建了锂电池组双层均衡拓扑电路和自适应模糊PID控制算法模型。实验结果表明:在不同工作状态下,所提出的电池组均衡拓扑及其控制策略将均衡时间效率平均提高了58.36%,验证了该方案的有效性。

基于模糊PID算法的食用菌大棚温度控制系统研究

食用菌大棚温度控制系统是一个具有时滞性的复杂系统,传统的开关量或常规PID控制很难满足设计要求。该研究设计一种基于STM32F103CRT6单片机为控制核心,加入模糊自适应PID控制算法,利用DHT11温湿度传感器进行温度实时采集,单片机运算处理,光耦固态继电器驱动电路对热风机进行控制,从而达到温度调节的目的。并在MATLAB/simulink环境下建立常规PID控制和模糊自适应PID控制的仿真模型,通过仿真结果,对比验证了该方法比常规PID控制方法具有低超调量和调节时间短等较好的控制效果。

红外干燥箱变论域模糊PID复合温控设计

烘干失重法粮食水分测定过程中,干燥箱温度的精准控制是检测结果准确性的重要保障。针对干燥箱温度变化过程非线性、时滞性和温控精度高的特点,提出一种基于粒子群模型参数辨识的变论域模糊PID复合温度控制策略。基于红外辐射干燥机理及能量守恒方程建立温控系统非线性模型,并利用粒子群优化算法完成参数辨识,通过设定二级偏差阈值,将变论域模糊PID算法结合Bang-Bang控制方法构成自适应分级复合控制策略。系统仿真实验表明:相较于常规PID控制和传统模糊PID控制方法,改进后的复合控制策略在超调量、调节时间和控制进度方面明显改善,在不同工作点温度下,控制误差均小于0.4℃,且具有较好的抗干扰能力。

可靠性驱动下的机械元动作单元变论域自适应模糊PID振动控制系统研究

机械元动作装配单元可靠性是整机功能可靠性的重要构成,元动作单元工作过程中振动异常是导致其故障频发的重要因素。因此,采取有效的振动控制策略对降低元动作单元运行故障、提高单元可靠性和整机性能具有良好的工程意义。结合主动控制思想采用简易、精准的作动装置建立了一种智能的振动控制系统。为了提升控制系统中智能位移作动器的进给精度,设计了变论域自适应模糊PID控制器,并通过仿真分析了控制系统的可行性。仿真结果表明,变论域自适应模糊PID控制器下的系统响应具有极低的超调量、较少调整时间和趋于零的稳态误差。此项研究为提高机械产品使用可靠性提供了一种新的振动控制技术手段。

基于自适应模糊PID算法的绷带压力补偿

医用绷带往往依靠医生经验施加,难以实现精准治疗。为了实现精准监测绷带下的压力,在医用绷带下加入薄膜压力传感器构建了绷带压力监测系统,以STM32微处理器为核心,结合薄膜压力传感器、电路采集模块、电源模块、蓝牙模块,分别实现了压力信号的采集、电路供电及数据传输功能。测量过程中,压力信号峰值较小且变化频率快。为得到有效稳定的压力信号,将传统PID与模糊算法结合对传感器输出电压进行处理,模糊算法对电压偏差与电压偏差变化率进行模糊化、模糊推理、解模糊化处理,实现对传统PID参数的调整,从而实现传感器输出电压的调控。利用压力与传感器输出电压的数学模型关系实现对系统压力误差的控制要求。实验结果表明,自适应模糊PID算法稳定性更高,系统测试最大误差仅为4.5%,实现了系统压力信号的误差控制。

模糊自适应PID对保险粉合成pH值的控制研究

保险粉合成过程pH值控制存在非线性、时滞性、不确定性问题,采用常规PID控制结合人工控制的方式无法实现参数自调整,对pH值的控制很难达到预期效果,为此,提出了模糊自适应PID控制方法。介绍了保险粉合成原理及反应方程式,分析酸碱中和pH值控制并确定系统的传递函数,设计了模糊自适应PID控制器,通过Matlab/Simulink进行仿真分析,并进行了实验验证,结果表明:模糊自适应PID控制与常规PID控制相比,具有超调量小、调节时间短、抗干扰能力强等优点,实现了对pH值的有效控制。

太阳能—地源热泵式空调自适应模糊PID复合控制方法

为了优化太阳能-地源热泵空调系统的能耗和效率,减少环境因素对稳定运行的影响,提出自适应模糊PID复合控制方法。通过监控管理层上位机采集现场数据信号,并下发开关量信号至PLC控制器,再通过PLC控制器对太阳能集热器、循环水泵和温度进行控制。同时,将模糊PID控制器作为子程序控制循环水泵的频率,温度误差和误差变化率作为复合控制器的输入,通过模糊化处理输入信号,调节PID控制的相关参数,输出控制变频器频率的信号,以调节水泵电机的运转速度,精准控制室内温度。实验结果表明,该方法能提高太阳能的利用率,具有较好的抗干扰性能和较高的制冷、供暖性能系数,可实现高效的节能效果。