PI control based on fuzzy set-point weighting tracking for hydraulic crane boom system

A PI control strategy based on fuzzy set-point weighting following was proposed for the active damping control of a hydraulic crane boom system （HCBS）. Two valve-controlled PI controllers, which include a proportional feedforward controller based on fuzzy set-point weighting following and a limited semi-integrator（LSI）, are designed respectively. LSI is used to limit output signal and to prevent wind up at the low frequency of the spectrum. By using a range camera and an electronic feedback control, the tip damping on the HCBS can be adjusted artificially. A collaborative control simulation technique of HOPSAN and MATLAB/SIMULINK is applied to the controller design. Simulation results show that the proposed PI control system has less overshoot as well as faster response. The tip damping on the HCBS during operation is improved.

Consensus intuitionistic fuzzy group decision-making method for aircraft cockpit display and control system evaluation

A novel group decision-making （GDM） method based on intuitionistic fuzzy sets （IFSs） is developed to evaluate the ergonomics of aircraft cockpit display and control system （ACDCS）. The GDM process with four steps is discussed. Firstly, approaches are proposed to transform four types of common judgement representations into a unified expression by the form of the IFS, and the features of unifications are analyzed. Then, the aggregation operator called the IFSs weighted averaging （IFSWA） operator is taken to synthesize decision-makers’ （DMs’） preferences by the form of the IFS. In this operator, the DM’s reliability weights factors are determined based on the distance measure between their preferences. Finally, an improved score function is used to rank alternatives and to get the best one. An illustrative example proves the proposed method is effective to valuate the ergonomics of the ACDCS.

Nonlinear combined forecasting model based on fuzzy adaptive variable weight and its application

In order to enhance forecasting precision of problems about nonlinear time series in a complex industry system,a new nonlinear fuzzy adaptive variable weight combined forecasting model was established by using conceptions of the relative error,the change tendency of the forecasted object,gray basic weight and adaptive control coefficient on the basis of the method of fuzzy variable weight.Based on Visual Basic 6.0 platform,a fuzzy adaptive variable weight combined forecasting and management system was developed.The application results reveal that the forecasting precisions from the new nonlinear combined forecasting model are higher than those of other single combined forecasting models and the combined forecasting and management system is very powerful tool for the required decision in complex industry system.

Adaptive fuzzy compensation based composite nonlinear feedback controller design for robot manipulators

In order to suppress the influence of uncertain factors on robot system and enable an uncertain robot system to track the reference input accurately,a strategy of combining composite nonlinear feedback(CNF)control and adaptive fuzzy control is studied,and a robot CNF controller based on adaptive fuzzy compensation is proposed.The key of this strategy is to use adaptive fuzzy control to approach the uncertainty of the system online,as the compensation term of the CNF controller,and make full use of the advantages of the two control methods to reduce the influence of uncertain factors on the performance of the system.The convergence of the closed-loop system is proved by feedback linearization and Lyapunov theory.The final simulation results confirm the effectiveness of this plan.

Model Predictive Yaw Control Using Fuzzy-Deduced Weighting Factor for Large-Scale Wind Turbines

Yaw control system plays an important role in helping large-scale horizontal wind turbines capture the wind energy.To track the stochastic and fast-changing wind direction,the nacelle is rotated by the yaw control system.Therein,a difficulty consists in the variation speed of the wind direction much faster than the rotation speed of the nacelle.To deal with this difficulty,model predictive control has been recently proposed in the literature,in which the previewed wind direction is employed into the predictive model,and the estimated captured energy and yaw actuator usage are two contradictive objectives.Since the performance of the model predictive control strat-egy relies largely on the weighting factor that is designed to balance the two objectives,the weighting factor should be carefully selected.In this study,a fuzzy-deduced scheme is proposed to derive the weighting factor of the mod-el predictive yaw control.For the proposed fuzzy-deduced strategy,the variation degree and the increment of the wind direction during the predictive horizon are used as the inputs,and the weighting factor is the output,which is dynamically adjusted.The proposed model predictive yaw control is demonstrated by some simulations using real wind data and its performance is compared with the conventional model predictive control with thefixed weighting factor.Comparison results confirm the outweighing performance of the proposed control strategy over the conventional one.

永磁同步直线电机SFLA-FUZZY的PID控制

针对永磁同步直线电机,提出了一种混合蛙跳结合模糊控制器的PID控制方法。设计了模糊控制器,编写混合蛙跳算法,搭建了永磁同步直线电机模型和SFLA-FUZZY(混合蛙跳与模糊控制器)结合控制的Matlab仿真模型。通过仿真对比了电机分别在传统PID、模糊控制器、SFLA-FUZZY控制条件下的运行状况。仿真分析表明,SFLA-FUZZY控制的响应速度更快,超调量更小,具有较好的动静态性能。

Composite Control of Precalciner Exit Temperature in Cement Rotary Kiln

A composite control strategy for the precalciner exit temperature in cement kiln is introduced based on a mathematical model. In this model, the raw meal flow, coal powder flow and wind flow are taken as three input variables, the clinker fow and exit teperature of cement kiln are output variables, and other influencing factors are considered as disturbance. A composite control system is synthesied by integrating self learning PID, fuzzy and feedforward function into a combined controller, and the arithmetics for the self learning PID controller, fuzzy controller and feedforward controller are elaborated respectively. The control strategy has been realized by software in real practice at cement factory. Application results show that the composite control technology is superior to the general PID control in control effect, and is suitable to the industrial process control with slow parameter variation, nonlinearity and uncertainty.

电动汽车复合ABS控制策略仿真及参数分析

为了提高电动汽车在制动过程中的稳定性和安全性,提出了一种电动汽车复合防抱死制动系统(ABS)的控制策略,首先利用AMESim软件建立了电动汽车的仿真模型,并在Simulink中采用模糊逻辑控制的方法设计了具有四个独立通道的ABS控制方法,最后在低路面摩擦系数条件下进行仿真。仿真结果表明,所建立的联合仿真模型及其控制方法能够较好地模拟ABS制动的实际过程,保证车轮转速与车速保持较好的同步,可以提高电动汽车的转向性和稳定性。模型参数可调,因此可对不同参数对ABS效果的影响进行研究,该仿真模型可作为电动汽车ABS研究的良好平台。

基于AHP模型的冷水江市铎山镇岩溶塌陷易发性评价

冷水江市铎山镇岩溶地面塌陷严重威胁居民生产和生活安全。为提出科学合理的防治措施,选取地貌与构造、地层岩性、地下水、人类工程活动、岩溶塌陷现状等5个影响因素的13个评价指标构建研究区岩溶塌陷易发性评价指标体系,分别采用AHP(层次分析法)-模糊综合评价模型和AHP-加权平均综合指数模型进行岩溶塌陷易发性评价。结果表明,两个模型确定的不、低、中、高易发区的频率比(塌陷占比与面积占比的比值)逐渐增大,AUC值分别为0.877和0.813,说明它们都能客观有效地评价铎山镇岩溶塌陷的易发性,而且AHP-模糊综合评价模型评价效果更好;研究区高、中、低、不易发区地面积分别为1.120、2.890、1.763、0.767 km^(2),占比分别为17.1%、44.2%、27.0%、11.7%。建议在高、中易发区采取以搬迁避让和工程治理为主的防治措施,在低、不易发区选择相对稳定区域作为新建居民安置区,同时全域均进行工程监测和群测群防。

汽车ABS模糊控制方法的分析与仿真

运用模糊控制方法对汽车防抱制动系统进行了仿真研究 采用基于模糊规则的模糊控制方法,设计了基于模糊规则的普通模糊控制器,针对其缺陷采用基于智能权函数的模糊控制方法,设计了基于智能权函数的模糊控制器 对两种控制器进行仿真并比较仿真结果,表明基于智能权函数的模糊控制方法的控制效果优于基于模糊规则的模糊控制方法,且能有效克服后者的缺陷。

基于ADVISOR的纯电动汽车复合电源建模与仿真

在分析复合电源结构的基础上,建立复合电源DC/DC仿真子模块,制定基于功率需求分配的模糊控制策略,建立模糊控制复合电源仿真模型,并在汽车仿真软件ADVISOR平台上对其进行二次开发,搭建模糊控制复合电源系统的纯电动汽车仿真模型。以UDDS工况为例进行仿真分析,结果表明,该模糊控制复合电源系统能合理分配蓄电池和超级电容的功率输出,超级电容能在汽车加速时提供瞬时峰值功率,延长了蓄电池的使用寿命,提高了车载电源的整体性能。

Fuzzy-PID复合控制在水泥冷却过程中的应用

针对PID在水泥生产线冷却过程中实际应用所发现的问题,提出了将Fuzzy-PID复合控制算法应用于现场的控制思路,该算法将Fuzzy和PID两种控制方式的控制优点有机结合,根据多次现场实验得到的模糊切换隶属度函数在两种控制方式下自动切换,该控制既能在动态过程中快速调节,又能在稳态过程中准确调节。冷却过程控制软件采用VC++编写,通过在某水泥厂的实际应用表明了该方案的正确性和实用性。

基于ATMEGA48V单片机的电动车驱动系统设计

针对当前电动车驱动系统电路结构复杂、可靠性差且控制效果不佳的问题,提出并设计了一种基于低功耗高性能单片机AT- MEGA48V控制、功率驱动电路采用集成模块IR2103S、引入模糊-PI复合控制的电动车驱动系统;详细论述了系统硬件结构和控制策略的设计;实验结果表明,该系统可靠性高,具有良好的启动特性和加速性能,更能适应需要频繁启动及在各种复杂路况下骑行的电动车驱动控制。

基于模糊理论的抗差Kalman滤波算法

动态导航与定位的质量取决于对动态载体扰动和观测异常扰动的认知和控制质量。在实践中,观测向量及其动态模型信息均可能存在异常,此时若仍利用标准Kalman滤波,则状态滤波解将极不可靠。在标准Kalman滤波原理的基础上,结合模糊控制理论,提出了一种基于模糊理论的抗差Kalman滤波算法。该方法是依据滤波处理后的数据残差,利用模糊理论构造等价权,从而有效控制粗差对导航解的影响,并用算例验证了该方法的可行性和有效性。

基于组合权重-Fuzzy的航空公司安全管理体系有效性评估

为提升航空公司安全管理体系(SMS)建设效果和质量,全面考察了影响SMS成效的各类因素,以提高SMS评估模型的有效性。采用融合主观和客观的组合权重法(G1法和变异系数法)求得各级指标的权重,并基于模糊综合评估法,使用三角模糊隶属度函数,构建SMS模糊综合评价模型。最后,以某航空公司为实证对象,求解模糊评判矩阵,并根据最大隶属度原则和加权平均量化法得到该航司SMS有效性的评估等级及量化分值。结果表明,基于G1-变异系数的组合权重法能得到更科学合理的指标权重,各类指标中管理因素和人的因素占有相对重要的权重。某航司SMS有效性评估整体结果良好,但在安全结果类因素方面仍有待加强。

FUZZY-PI控制器在水温控制系统中的应用

针对水温控制系统存在非线性、时滞的问题,采用FUZZY—PI复合控制器对其进行控制,既利用了模糊控制适应能力强、动态特性好、抗干扰能力强的特点,又利用了PI控制可消除系统静差的特点,从而使控制系统的动态和静态品质都得到了提高,在水温控制实验中取得了较理想的效果．

基于LabVIEW的锅炉燃烧远程监控方法研究

提出了一种基于LabVIEW和Internet的锅炉燃烧远程监控系统方案。利用fuzzy-PI复合控制器的优化控制算法实现现场控制,通过Internet实现远端和现场之间的信息交换,并利用开放式图形化设计语言LabVIEW开发平台构建宜人化虚拟故障诊断和控制中心,可以实现锅炉燃烧系统的远程监控,对于重大或疑难故障请求虚拟诊断中心实现网上专家会诊。

针对非线性外生系统的模糊干扰观测器与抗扰控制设计

针对由外生系统描述的扰动的抗扰控制方法一直是研究热点。本文针对一类含有非线性扰动的非线性系统,利用径向基函数模糊逻辑系统逼近系统及外生系统中的未知非线性函数,设计了一种新型的模糊干扰观测器(FDO)估计非线性扰动。构造了一种新颖的干扰估计误差观测器来逼近自适应更新律中的干扰估计误差。在此基础上,结合线性矩阵不等式(LMI)提出了一种基于FDO的自适应模糊控制方法,并利用李雅普诺夫方法分析了闭环系统的稳定性。最后,采用仿真实验验证了所设计的控制方法。实验结果表明,所提出的方法在控制精度及干扰估计精度上均优于传统的抗扰控制方法。

基于ARM7的表贴元件包装机智能控制系统

根据我国当前表帖元件包装机温度控制精度及封装效率都较低的现状,设计了基于ARM7处理器S3C44B0X的智能控制系统。介绍了该控制系统的硬件电路组成并给出了主程序流程,针对温度控制提出了带有加权因子的模糊控制算法。实际应用表明,该智能系统的控制效果优于常规控制系统。

基于IAHP和信息熵组合赋权的空域运行风险评估

针对传统空域运行安全风险评估方法中存在的点值评估随意性和间断性等问题,该文提出基于区间层次分析法(IAHP)和信息熵法结合的空域运行风险评估方法。通过广泛采集空域内航空器运行产生的告警信息,深入分析并挖掘出对空域运行产生影响的风险因子,构建一套新的基于"人、机、环"分类思路的风险评估多层指标体系。所提方法主要采用IAHP和信息熵方法分别对评估指标赋权,同时给出主客观权重组合模型,既保证了评估数据的连续性,也兼顾到评估要素的客观性,并在风险隶属度矩阵基础上进行模糊综合评价。最后对某飞行情报区一段时间的运行状态进行实例评估,结果表明,该模型在空域运行风险方面具有良好的适用性和有效性,为空中交通安全风险管理提供理论上的决策支持。