一种基于Matlab的参数自调整模糊控制器的设计方法

本文介绍了一种在MATLAB的模糊控制工具箱中,通过编写S函数实现对量化因子和比例因子的在线自动调整来设计模糊控制器,从而有效地实现参数自调整模糊控制器的设计方法。为了验证参数自调整模糊控制器的优越性,分别进行了空调温度控制系统的PID控制、常规模糊控制和参数自调整模糊控制的仿真研究。结果表明,参数自调整模糊控制器较之常规的模糊控制器,在被控对象特性变化或较大扰动的情况下,控制系统能保持较好的性能,是一种较理想的控制方法,具有广阔的发展前景。     

模糊控制器参数调整的产生式方法

为了改善模糊控制器的性能,采用了产生式方法自动地调整模糊控制器的量化因子和比例因子。该方法克服了参数固定或者参数选择不合适而引起系统超调大或者系统响应慢的缺点。不需要反复试凑就能获得较理想的量化因子和比例因子。仿真结果表明,该方法能通过在线运行,较快地自动整定出一组满足性能要求的量化因子和比例因子。     

模糊控制器参数调整的生产式方法

为了改善模糊控制器的性能,采用了产生式方法自动地调整模糊控制器的量化因子和比例因子。该方法克服了参数固定或者参数选择不合适而引起系统超调大或者系统响应慢的缺点。不需要反复试养伤就能获得较理想的经因子和比例因子。仿真结果表明,该方法能通过在线运行,较快地自动整定出一组满足性能要求的量化因子和比例因子。     

参数自整定模糊控制器在弧焊焊缝跟踪中的应用

本文阐述了焊缝跟踪参数自整定模糊控制器的工作原理，提出了比例因子和量化因子自动调节的方案和实现方法，介绍了模糊控制器的具体设计步骤和单片机参数自整定模糊控制系统的软硬件设计。结果表明，在焊缝跟踪中采用参数自整定模糊控制器可以明显改善系统的性能。     

具有加权因子的PID型模糊控制器分析及设计

为了降低模糊控制器的设计难度, 提高控制性能, 以二维模糊控制器为基础, 设计了一种具有加权因子的PID型模糊控制器, 并提出了基于普通PID控制器参数整定模糊控制器参数的方法。首先, 基于模糊控制器的解析结构推导, 从理论上证明了该类PID型模糊控制器是一个全局二维多值继电器与一个局部具有变结构PID控制器的组合; 然后, 基于平衡点处该类PID型模糊控制器与普通PID控制器之间的等效关系, 建立了模糊控制器系统化的参数设计方法; 最后, 仿真实验验证了本设计的有效性。     

一种变论域模糊控制器伸缩因子选择的新方法

对变论域模糊控制器伸缩因子选取的易实现性和输出的实时性问题进行了讨论,给出了一种选择伸缩因子的新方法。该方法与积分型伸缩因子和指数型伸缩因子选择相比具有计算量小、参数少的特点。通过仿真给出了该伸缩因子参数选择的原则。结合间歇反应釜工程应用,将此伸缩因子设置在变论域模糊控制器模糊推理的前件和后件,验证了此伸缩因子的有效性：在保证高精度的基础上,输出能快速跟踪系统的输入,为变论域模糊控制器实际应用提供了一种有效的解决方案。     

变论域模糊控制器伸缩因子的选择方法

对变论域模糊控制器伸缩因子选取的易实现性和输出的实时性问题进行了讨论,给出了一种选择伸缩因子的新方法.该方法与积分型伸缩因子和指数型伸缩因子选择相比具有计算量小、参数少的特点.通过仿真给出了该伸缩因子参数选择的原则.结合间歇反应釜工程应用,将此伸缩因子设置在变论域模糊控制器模糊推理的前件和后件,验证了此伸缩因子的有效性:在保证高精度的基础上,输出能快速跟踪系统的输入,为变论域模糊控制器实际应用提供了一种有效的解决方案.     

新型模糊PID控制及在HVAC系统的应用

为了推广模糊控制器在非线性系统中的应用,提出一种利用PID控制器的参数优化和调节模糊控制器的新型设计方法.通过模糊控制器的结构分析建立与PID控制之间的精确解析关系之后提出基于PID控制增益因子的模糊控制器设计算法,然后利用改进的变论域思想进一步优化模糊控制器设计参数.将其应用于暖通空调(HVAC)系统的节能控制中并与常规PID控制器相比较,仿真和实验结果表明这种模糊控制器具有超调量小、跟踪迅速、鲁棒性强等优越的控制性能.     

一种自调整模糊控制器的设计与仿真研究

提出了一种基于规则，参数自整定的模糊控制器的设计方法，它通过引入误差加权因子和误差变化率加权因子，以系统阶跃响应的上升时间和超调量为性能评价指标，并根据评价结果建立自适应算法，对模糊控制器的模糊推理规则及参数进行自调整。仿真结果进行表明，误差变化率加权因子以明显改善模糊控制器的稳定性，性能评价指标函数，模糊推理规则和参数调整算法简单实用，便于实现，对被控对象的参数变化具有较强的适应能力，控制效果良好。     

一种基于模糊切换的模糊复合控制器及其应用

基于线性控制器与模糊控制器的特点，通过使两者并行结合，提出一种模糊复合控制器的设计方法，谈模糊复合控制器采用模糊推理完成两组控制器的平稳“切换”，而且其中模糊控制器的比例因子的初始整定可由PID控制器的整定参数获得，从而简化了模糊控制器的设计。在某电厂300MW机组的实际应用结果表明，采用谈方法设计的过热蒸汽温度控制系统具有较强的适应能力和良好的控制效果。     

Dynamic switching based fuzzy control strategy for a class of distributed parameter system

In this work, a dynamic switching based fuzzy controller combined with spectral method is proposed to control a class of nonlinear distributed parameter systems (DPSs). Spectral method can transform infinite-dimensional DPS into finite ordinary differential equations (ODEs). A dynamic switching based fuzzy controller is constructed to track reference values for the multi-inputs multi-outputs (MIMO) ODEs. Only a traditional fuzzy logic system (FLS) and a rule base are used in the controller, and membership functions (MFs) for different ODEs are adjusted by scaling factors. Analytical models of the dynamic switching based fuzzy controller are deduced to design the scaling factors and analyze stability of the control system. In order to obtain a good control performance, particle swarm optimization (PSO) is adopted to design the scaling factors. Moreover, stability of fuzzy control system is analyzed by using the analytical models, definition of the stability and Lyapunov stability theory. Finally, a nonlinear rod catalytic reaction process is used as an illustrated example for demonstration. The simulation results show that performance of proposed dynamic switching based fuzzy control strategy is better than a multi-variable fuzzy logic controller.     

A new approach for dynamic fuzzy logic parameter tuning in Ant Colony Optimization and its application in fuzzy control of a mobile robot

Ant Colony Optimization is a population-based meta-heuristic that exploits a form of past performance memory that is inspired by the foraging behavior of real ants. The behavior of the Ant Colony Optimization algorithm is highly dependent on the values defined for its parameters. Adaptation and parameter control are recurring themes in the field of bio-inspired optimization algorithms. The present paper explores a new fuzzy approach for diversity control in Ant Colony Optimization. The main idea is to avoid or slow down full convergence through the dynamic variation of a particular parameter. The performance of different variants of the Ant Colony Optimization algorithm is analyzed to choose one as the basis to the proposed approach. A convergence fuzzy logic controller with the objective of maintaining diversity at some level to avoid premature convergence is created. Encouraging results on several traveling salesman problem instances and its application to the design of fuzzy controllers, in particular the optimization of membership functions for a unicycle mobile robot trajectory control are presented with the proposed method.     

基于模糊控制的进场飞机排序

针对日益增长的空中交通需求所带来的严重航班延误,利用模糊控制理论设计对终端区进场飞机的调度排序算法。把管制员调度航班考虑的主要因素作为输入,制定模糊规则,建立模糊控制器,输出比较合理的飞机排定着陆顺序。     

基于混沌搜索的二级倒立摆模糊控制器设计

利用混沌优化的模糊控制方法对二级倒立摆系统进行闭环控制。用混沌算法优化控制器的参数,首先将混沌变量引入到模糊控制器的参数域,并进行全局范围内直接寻优,当获得全局近似最优解后,再缩小寻优区间,根据性能指标,在次优解附近继续寻优,得到全局最优参数。控制结果说明该方法是有效可行的。     

Comfort-based fuzzy control optimization for energy conservation in HVAC systems

The work presented herein illustrates the use of computational intelligence and optimization approaches for improving the fuzzy controller׳s performance in architectural heating, ventilation, and air conditioning system (HVAC). The primary purpose of the performed research is to find a method to moderate the energy use without compromising the comforts of the inhabitants. The control design used to meet this purpose includes the predicted mean vote (PMV) and predicted percentage dissatisfied (PPD) indices. The software of choice for evaluating PMV and PPD is EnergyPlus. Whereas, for the fuzzy controller and the evolutionary optimization framework, the co-simulation tool with building controls virtual test bed (BCVTB) is used in conjunction with Simulink. The ensuing comparison between EnergyPlus׳s thermal control of HVAC and our fuzzy approach is the outcome of the present research.     

Simplifying the automatic design of a fuzzy logic controller using evolutionary programming

With the availability of a wide range of Evolutionary Algorithms such as Genetic Algorithms, Evolutionary Programming, Evolutionary Strategies and Differential Evolution, every conceivable aspect of the design of a fuzzy logic controller has been optimized and automated. Although there is no doubt that these automated techniques can produce an optimal fuzzy logic controller, the structure of such a controller is often obscure and in many cases these optimizations are simply not needed. We believe that the automatic design of a fuzzy logic controller can be simplified by using a generic rule base such as the MacVicar-Whelan rule base and using an evolutionary algorithm to optimize only the membership functions of the fuzzy sets. Furthermore, by restricting the overlapping of fuzzy sets, using triangular membership functions and singletons, and reducing the number of parameters to represent the membership functions, the design can be further simplified. This paper describes this method of simplifying the design and some experiments performed to ascertain its validity.     

Robust adaptive fuzzy logic power system stabilizer

This paper introduces a robust adaptive fuzzy controller as a power system stabilizer (RFPSS) used to damp inter-area modes of oscillation following disturbances in power systems. In contrast to the IEEE standard multi-band power system stabilizer (MB-PSS), robust adaptive fuzzy-based stabilizers are more efficient because they cope with oscillations at different operating points. The proposed controller adopts a dynamic inversion approach. Since feedback linearization is practically imperfect, components that ensure robust and adaptive performance are included in the control law to compensate for modelling errors and achieve acceptable tracking errors. Two fuzzy systems are implemented. The first system models the nominal values of the system’s nonlinearities. The second system is an adaptive one that compensates for modelling errors. A feedback linearization-based control law is implemented using the identified model. The gains of the controller are tuned via a particle swarm optimization routine to ensure system stability and minimum sum of the squares of the speed deviations. A bench-mark problem of a 4-machine 2-area power system is used to demonstrate the performance of the proposed controller and to show its superiority over other conventional stabilizers used in the literature.     

基于模糊控制的某教练机飞行姿态控制器设计

提出了一种基于规则的模糊逻辑飞行控制系统的设计方法,用以解决某教练机训练系统中数学模型时变性和不确定性问题.为了避免建模的困难,某教练机飞控系统采用模糊逻辑控制设计其控制律,结合飞行员的操纵经验,对系统进行动态调整.以俯仰角为研究对象,利用MATLAB中的fuzzy工具箱实现了模糊控制器设计,给出了俯仰角模糊控制器的控制曲面视图,并在SIMULINK仿真环境下建立了仿真模型.结果表明,所设计的模糊逻辑控制器满足操作品质的要求,具有较好的鲁棒性,对教练机驾驶训练仿真平台的飞行控制系统设计具有一定的应用价值.     

网络时延的模糊逻辑补偿方法的研究

当网络应用到控制系统中时,网络将引起时延,从而对闭环网络控制系统产生一些不利的影响,比如系统性能下降,系统不稳定等。本文介绍了通过在已有的PI控制器的基础上,再增加一个模糊逻辑补偿器来补偿网络控制系统中网络所引起的时延,其优点是不需要再重新设计已有的PI控制器,而只是简单地将模糊逻辑控制器的输出作为一个参数来调节PI控制器所提供的控制信号。文中采用了MATLAB/SIMULINK仿真,仿真结果表明了该方法的有效性。     

模糊逻辑控制系统分析与设计

本文把模糊逻辑控制当作多维继器，用Ｌｐ稳定性和园周判据分析闭环模糊逻辑控制系统的稳定性，给出闭环非线性系统与模糊逻辑控制器结合系统的稳定判据和设计方法，并用计算机仿真试验，进一步将稳定判据应用到不同系统。