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本文提出一种基于高斯函数网络的模糊温度控制器,给出了模糊神经网络控制模型和学习算法。通过自学习不断修正模糊控制器规则,使模糊控制器具有自学习和自适应能力。计算机仿真及温控结果表明,这种智能控制器具有良好的控制性能。 相似文献
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利用神经网络进行推理的模糊控制器 总被引:22,自引:3,他引:19
本文介绍了一种利用神经网络进行推理的模糊控制器。网络的输入和输出均为模糊集。训练后的网络能完成合成关系,即模糊推时。为了减少BP网络的高线训练时间,对模糊集进行了“编码”。最后给出了该控制器应用于曲线环节的实时控制结果。 相似文献
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用B样条神经网络设计自适应模糊控制器* 总被引:6,自引:1,他引:5
本文提出一种可用于设计自适应模糊控制器的模化B样条神经网络,并给出了合适的训练算法。由于这种网络在每次训练时仅需对少量权重进行调整,因此构成的模糊控制器学习速率快,可应用于过程控制中。本文最后以电厂中过热汽温的控制为例,说明本文的设计方法是有效的。 相似文献
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常规模糊控制器引入矩形域上的插值算法,基本上消除了普通模糊控制器的调节死区,改善了模糊控制器的稳态性能,最后给出的仿真结果证明这种方法是有效的。, 相似文献
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一种基于模糊CMAC神经网络的自学习控制器 总被引:6,自引:0,他引:6
通过分析模糊控制和基于广义基函数的CMAC神经网络,提出一种模糊CMAC(FCMAC)神经网络。通过FCMAC权系数的在线学习,实现修正模糊逻辑。给出一种基于FCMAC的自学习控制器的结构及合适的学习算法,这种网络每次学习少量参数,算法简单。仿真结果表明所提出的控制器优于传统的PID控制器。 相似文献
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交通信号自适应模糊控制器的设计及稳定性分析 总被引:8,自引:1,他引:7
针对城市交通路口的信号控制,提出一种自适应模糊控制器,并对其稳定性进行分析.通过控制器给出路口实时信号配时,根据红灯相位的等候车辆平均损失和绿灯相位释放车辆的平均增益,给出了模糊控制器的自适应算法,以实时修正其模糊规则.在自适应模糊控制器的稳定性分析中,采用模糊控制系统闭环模型的模糊关系矩阵,证明在路口车辆随机产生的情况下,模糊控制系统是稳定的.仿真结果表明,自适应模糊控制器比全感应控制器、简单模糊控制器更能适应路口交通流的变化,极大地改善了系统性能. 相似文献
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提出了一种分布式神经模糊网络和自学习模糊控制器的构成方法。它是CMAC模型的一种扩展,使其能进行模糊推理和构成自学习的模糊控制器。该方法除具有CMAC优点外,还具有以下特点:输入数据通过模糊划分和隶属函数后自动编码,对精度没有限制;从现场数据直接获取控制规则,即使对未训练的数据,也能结合插值和泛化两种能力,推理给出合适的输出。学习实例证明了方法的有效性。 相似文献
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给出参数自调整模糊控制器的原理.利用MATLAB,分析了一种参数自调整模糊控制器的控制效果.分析了各种模糊控制器的实现方案.同时给出目前FPGA的发展状况,并且分析了相应工业控制应用情况.最后,给出了基于FPGA的参数自调整模糊控制器的实现结构. 相似文献
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π型隶属函数的典型模糊控制器的解析结构 总被引:1,自引:0,他引:1
研究了一种新型的典型模糊控制器,它的输入隶属函数采用π型样条函数,具有二阶逼近特性,而一般典型模糊控制器采用的三角形隶属函数只具有一阶逼近特性,因此研究这种新型的模糊控制器具有重要的意义.文章首先给出了该类典型模糊控制器的定义,推导了它的解析表达式,证明了该类典型模糊控制器可以等效为一个全局的二维继电器和一个局部的非线性PD控制器之和.在此基础上,给出了其极限特性和非线性特性. 相似文献
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Y. Ding H. Ying S. Shao 《Soft Computing - A Fusion of Foundations, Methodologies and Applications》1999,2(4):183-190
In this paper, we first reveal the analytical structure of a simple Takagi–Sugeno (TS) fuzzy PI controller relative to the
linear PI controller. The fuzzy controller consists of two linear input fuzzy sets, four TS fuzzy rules with linear consequent,
Zadeh fuzzy logic AND and the centroid defuzzifier. We prove that the fuzzy controller is actually a nonlinear PI controller
with the gains changing with process output. Utilizing the well-known small Gain Theorem in control theory, we then derive
sufficient conditions for global stability of the fuzzy control systems involving the TS fuzzy PI controller. Finally, as
an application demonstration, we apply the fuzzy PI controller to control issue temperature, in computer simulation, during
hyperthermia therapy. The relationship between heat energy and tissue temperature is represented by a linear time-varying
model with a time delay. The sufficient conditions for global stability are used to design a stable fuzzy control system.
Our simulation results show that the fuzzy PI control system achieves satisfactory temperature control performance. The control
system is robust and stable even when the model parameters are changed suddenly and significantly. 相似文献
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This paper presents a robust adaptive fuzzy control algorithm for controlling unknown chaotic systems. The control approach encompasses a fuzzy system and a robust controller. The fuzzy system is designed to mimic an ideal controller, based on sliding-mode control. The robust controller is designed to compensate for the difference between the fuzzy controller and the ideal controller. The parameters of the fuzzy system, as well as uncertainty bound of the robust controller, are tuned adaptively. The adaptive laws are derived in the Lyapunov sense to guarantee the stability of the controlled system. Numerical simulations show the effectiveness of the proposed approach. 相似文献
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Abstract: A fuzzy sliding-mode control with rule adaptation design approach with decoupling method is proposed. It provides a simple way to achieve asymptotic stability by a decoupling method for a class of uncertain nonlinear systems. The adaptive fuzzy sliding-mode control system is composed of a fuzzy controller and a compensation controller. The fuzzy controller is the main rule regulation controller, which is used to approximate an ideal computational controller. The compensation controller is designed to compensate for the difference between the ideal computational controller and the adaptive fuzzy controller. Fuzzy regulation is used as an approximator to identify the uncertainty. The simulation results for two cart–pole systems and a ball–beam system are presented to demonstrate the effectiveness and robustness of the method. In addition, the experimental results for a tunnelling robot manipulator are given to demonstrate the effectiveness of the system. 相似文献
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This paper presents a systematic design procedure of a multivariable fuzzy controller for a general Multi-Input Multi-Output (MIMO) nonlinear system with an input-output monotonic relationship or a piecewise monotonic relationship for each input-output pair. Firstly, the system is modeled as a Fuzzy Basis Function Network (FBFN) and its Relative Gain Array (RGA) is calculated based on the obtained fuzzy model. The proposed multivariable fuzzy controller is constructed with two orthogonal fuzzy control engines. The horizontal fuzzy control engine for each system input-output pair has a hierarchical structure to update the control parameters online and compensate for unknown system variations. The perpendicular fuzzy control engine is designed based on the system RGA to eliminate the multivariable interaction effect. The resultant closed-loop fuzzy control system is proved to be passive stable as long as the augmented open-loop system is input-output passive. Two sets of simulation examples demonstrate that the proposed fuzzy control strategy can be a promising way in controlling multivariable nonlinear systems with unknown system uncertainties and time-varying parameters. 相似文献
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Automatic generation of ladder diagram with control Petri Net 总被引:9,自引:0,他引:9
This paper presents a design method to generate a ladder diagram (LD) automatically with the control Petri Net (CPN) for control of discrete event system. This method describes the specification of a practical system with the CPN that associates operations with places and conditions with transitions. Based on the firing regulation of transition, the relationship of places, conditions, and events are formulated with Boolean functions. These functions can be easily converted into LD and implemented on a programmable logic controller (PLC). An application example in a liquid mixture system shows that the proposed method is effective and has the advantages of ease of understanding, modification, and maintenance. 相似文献
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P. Prem Kumar Indrani Kar Laxmidhar Behera 《IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics》2006,36(6):1442-1449
This correspondence proposes two novel control schemes with variable state-feedback gain to stabilize a Takagi-Sugeno (T-S) fuzzy system. The T-S fuzzy model is expressed as a linear plant with nonlinear disturbance terms in both schemes. In controller I, the T-S fuzzy model is expressed as a linear plant around a nominal plant arbitrarily selected from the set of linear subsystems that the T-S fuzzy model consists of. The variable gain then becomes a function of a gain parameter that is computed to neutralize the effect of disturbance term, which is, in essence, the deviation of the actual system dynamics from the nominal plant as the system traverses a specific trajectory. This controller is shown to stabilize the T-S fuzzy model. In controller II, individual linear subsystems are locally stabilized. Fuzzy blending of individual control actions is shown to make the T-S fuzzy system Lyapunov stable. Although applicability of both control schemes depends on the norm bound of unmatched state disturbance, this constraint is relaxed further in controller II. The efficacy of controllers I and II has been tested on two nonlinear systems 相似文献