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多变量模糊控制的现状与发展(Ⅱ)—关于解耦,神经网,变结构等问题 总被引:10,自引:0,他引:10
回顾了多变量模糊控制近年来的发展过程,着重介绍近年来出现的一些新研究方向,并对当前文盲华而不实领域的热点课题:模糊模型的辨识,多变量模糊自校正控制,模糊解耦,模糊分层控制,模糊神经网络的研究现状及其发展趋势作了进一步讨论。 相似文献
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多变量模糊预测控制及其应用研究 总被引:5,自引:0,他引:5
将文献「3」的单变量模糊预测控制方法加以推广,提出一种多变量模糊预测控制算法,并将其应用无机组负荷控制系统。仿真结果表明,所提出的多变量模糊预测控制方法是有效的。 相似文献
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针对在污水处理过程中存在的多变量相互影响,单变量控制显然不能满足其要求的情况下,本文提出了2种分级多变量模糊控制方法,分别为基于模糊PID-Smith和模糊理论的2级控制和基于双模糊PID-Smith理论的2级控制。这2种控制方法均采用1个双输入、单输出的控制器,它在结构上分为2级,其中基于模糊PID-Smith和模糊理论的2级控制器的第1级结构为模糊PID-Smith控制,第2级结构为模糊控制;而基于双模糊PID-Smith理论的2级控制的2级结构均为模糊PID-Smith控制。这2种控制器的设计方法不但解决了多变量模糊控制规则难以制定的问题,又充分的考虑了其他因素对控制量DO的影响,从而实现了污水处理过程中的多变量模糊控制。本文利用MATLAB软件实现了这2种控制方法的设计与仿真,并和单变量模糊控制进行了比较,总结了多变量模糊控制的特点和优势,指明了把多变量模糊控制应用于污水处理系统是切实可行的。 相似文献
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模糊规则控制一种绝对不稳定系统 总被引:4,自引:0,他引:4
本文设计了一个高精度、高分辨率的模糊控制器,并用以控制二阶倒立摆获得成功。提出了一种处理多变量系统的新观点,给出了模糊控制二阶倒立摆的控制规则;和一种强有力的清晰化方法,从而使模糊控制器的输出更加细腻,应用上述理论设计的高精度、高分辨率的模糊控制器,对二阶倒立摆进行实时控制获得成功。 相似文献
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多变量非线性系统参数自调整的模糊加权控制 总被引:1,自引:0,他引:1
本文针对多变量非线性系统,提出了一种参数自调整的模糊加权信息融合方法.利用
模糊组合变量降低模糊控制系统的维数,根据不同的模糊组合变量对最后决策的作用大小,
赋予不同的权重来实现对多变量非线性系统的控制,在利用反向传播算法对量化系数和加权
系数进行自学习后,在线进行基于模糊规则的参数自调整,有效地解决了多变量模糊控制系
统中难于设计多维规则库和在线实现自适应模糊控制的问题.本文还对所提出的方法进行了
仿真实验和实际系统的实验,实验结果证明了该方法的有效性. 相似文献
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基于模糊神经网络的混凝沉淀投药控制 总被引:1,自引:0,他引:1
根据已有的资料分析了自来水混凝沉淀过程多变量影响因素和特点,找出了影响混凝沉淀过程的主要变量是进水流量、进水浊度、原水pH值、进水温度.根据高木-关野模糊系统和神经网络非线性逼近的特点,提出了建立混凝沉淀加药控制模型的模糊适用度加神经网络的集成模糊神经网络控制方法.还结合某自来水厂的具体现场数据进行了仿真模型研究和现场的实验,实验表明控制精度满足要求,运行正常. 相似文献
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Multi-joint manipulator systems are subject to nonlinear influences such as frictional characteristics, random disturbances and load variations. To account for uncertain disturbances in the operation of manipulators, we propose an adaptive manipulator control method based on a multi-joint fuzzy system, in which the upper bound information of the fuzzy system is constant and the state variables of the manipulator control system are measurable. The control algorithm of the system is a MIMO (multi-input-multi-output) fuzzy system that can approximate system error by using a robust adaptive control law to eliminate the shadow caused by approximation error. It can ensure the stability of complex manipulator control systems and reduce the number of fuzzy rules required. Comparison of experimental and simulation data shows that the controller designed using this algorithm has highly-precise trajectory-tracking control and can control robotic systems with complex characteristics of non-linearity, coupling and uncertainty. Therefore, the proposed algorithm has good practical application prospects and promotes the development of complex control systems. 相似文献
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In this paper, an adaptive fuzzy control approach is proposed to stabilize a class of uncertain nonlinear MIMO systems with the unmeasured states and the external disturbances. The fuzzy logic systems are used to approximate the unknown functions. Because it does not required to assume that the system states are measurable, it needs to design an observer to estimate the system unmeasured states. The considered MIMO systems are more general, i.e. they consist of N subsystems and each subsystem is in the non‐affine form. The stability of the closed‐loop system is verified by using Lyapunov analysis method. Two simulation examples are utilized to verify the effectiveness of the proposed approach. Copyright © 2010 John Wiley and Sons Asia Pte Ltd and Chinese Automatic Control Society 相似文献
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Sofiane Doudou 《International journal of systems science》2013,44(6):1029-1038
An adaptive fuzzy control approach is proposed for a class of multiple-input–multiple-output (MIMO) nonlinear systems with completely unknown non-affine functions. The global implicit function theorem is first used to prove the existence of an unknown ideal implicit controller that can achieve the control objectives. Within this scheme, fuzzy systems are employed the approximate the unknown ideal implicit controller, and robustifying control terms are used to compensate the approximation errors and external disturbances. The adjustable parameters of the used fuzzy systems are deduced from the stability analysis of the closed-loop system in the sense of Lyapunov. To show the efficiency of the proposed controllers, two simulation examples are presented. 相似文献
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This paper studies a new solution framework for adaptive control of a class of MIMO time-varying systems with indicator function based parametrization, motivated by a general discrete-time MIMO Takagi–Sugeno (T–S) fuzzy system model in an input–output form with unknown parameters. An indicator (membership) function based parametrization has some favorable capacity to deal with certain large parameter variations. A new discrete-time MIMO system prediction model is derived for approximating a nonlinear dynamic system, and its system properties are clarified. An adaptive control scheme is developed, with desired controller parametrization and stable parameter estimation for control of such uncertain MIMO time-varying systems. A control singularity problem is addressed and the closed-loop stability and output tracking properties are analyzed. This work provides a new method for multivariable T–S fuzzy system modeling and adaptive control. An illustrative example and simulation results are presented to demonstrate the proposed novel concepts and to verify the desired adaptive control system performance. 相似文献
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考虑了一类多输入多输出非线性不确定系统的自适应模糊预测控制律设计问题.根据系统的跟踪误差在线调整间接模糊系统的权值,使其一致逼近系统中的未知非线性函数,并引入一个鲁棒控制器来提高整个系统的控制性能.通过泰勒展开设计出了基于间接自适应模糊系统的预测控制律,避免了在线优化带来的繁重的计算负担.基于李亚普诺夫原理,证明了闭环系统最终一致有界.最后利用本文提出的控制方案设计了高超声速飞行器的姿态控制系统,仿真结果表明了控制方案的有效性. 相似文献
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一类非线性MIMO系统的直接自适应模糊鲁棒控制 总被引:9,自引:2,他引:9
针对一类未知的非线性MIMO系统, 本文提出了一种直接自适应模糊鲁棒控制设计方法. 理论分析和仿真实验都已证明, 该方法确保闭环系统全局稳定, 获得H∞跟踪性能指标, 外部干扰、模糊逻辑逼近误差和输入对输出的交叉耦合可衰减到给定的水平, 系统鲁棒性好. 相似文献
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一类多变量非线性动态系统的鲁棒自适应模糊控制 总被引:5,自引:0,他引:5
对一类非线性多变量未知动态系统,提出了一种自适应模糊控制策略.策略中采用
IF-THEN推理规则来构造模糊逻辑系统,实现对系统中未知函数的估计,在建模误差为零的
条件下设计状态反馈控制器及参数的自适应律.分析了当存在建模误差时,闭环系统的稳定
性和鲁棒性. 相似文献