研究了非线性模糊脉冲系统的静态输出反馈鲁棒模糊控制问题。
The problem of robust output feedback fuzzy control of nonlinear fuzzy impulsive systems is considered in this paper.
对具有非线性模糊输入集的模糊控制器进行了输入输出结构的研究。
In this paper, we give a study of the input-output structures of fuzzy controllers with nonlinear input fuzzy sets.
本文针对新奥法隧道施工期采用非线性模糊综合评判方法进行了风险评估。
The author carries out the study on nonlinear fuzzy judgment method for Risk assessment of the tunnel construction in NAT.
提出了一种基于非线性模糊模型的开关磁阻电机(SRM)转子位置检测的方法。
Based on the nonlinear fuzzy model, an improved method of detecting rotor position for sensorless control of SRMs has been developed.
提出了一种基于非线性模糊模型并经在线调整的开关磁阻电机(SRM)转子位置检测的方法。
Based on the nonlinear fuzzy model which will be online modified, an improved method of detecting rotor position for sensorless control of SRMs has been developed.
运用非线性模糊滑模变结构控制理论，提出了对并联型电能质量调节器来进行模糊滑模变结构控制的设计方法。
By applying nonlinear fuzzy Variable Structure control (FVSC) theory, a design method of Unified Power Quality Conditioner (UPQC) associated FVSC control is proposed.
摘要：针对高速公路交通系统的非线性、时变特性，设计了一种模糊自适应控制器，并将其应用于高速公路匝道控制系统。
Abstract: Aiming at the nonlinear and time-varying characteristics of freeway traffic system, a fuzzy self-adaptive PID controller is designed and applied to freeway ramp metering in this paper.
提出利用直接自适应模糊神经网络控制一类不确定非线性混沌系统新方法。
A novel direct adaptive fuzzy neural networks (FNNs) controller for a class of uncertain nonlinear chaotic system is presented.
针对其存在非线性、参数时变和大延迟等难以控制的特性，提出基于T - S模糊模型的预测函数控制新方法。
As the nonlinearity, time-varying parameters and large lag make the control difficult, a predictive functional control method based on T-S (Takagi-Sugeno) fuzzy model is presented.
该文提出一种用于复杂的非线性未知系统辨识的混合神经网络模型—自适应模糊神经网络(AFNN)。
This paper presents a compound neural network model, i. e., adaptive fuzzy neural network (AFNN), which can be used for identifying the complicated nonlinear system.
基于该模型，并结合非线性反馈理论，一个模糊的控制器，控制器，然后设计。
Based on the model and in conjunction with nonlinear feedback theory, a fuzzy-PID ramp controller is then designed.
针对工业过程中普遍存在的时滞、非线性、对象参数时变等特性，提出了一种基于最优预测的神经元模糊自整定PID控制算法。
To the widely existed characteristics of time-delay, non-linear and timevarying of parameters in the industry process, an adaptive neuron-fuzzy PID controller based on optimal prediction is presented.
第四章：研究了一类非线性系统的间接自适应模糊滑模控制方法。
In chapter four, indirect fuzzy sliding mode control for a class of nonlinear systems is discussed.
针对一类非线性系统，把模糊t - S模型和自适应模糊逻辑系统这两种模糊逻辑方式结合起来，提出了一种自适应控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an adaptive control scheme for a class of nonlinear systems.
研究非线性系统的稳定控制问题，采用模糊动态模型方法，并将全局模糊系统模型表示成不确定系统形式。
The stable problem of nonlinear system was studied. Fuzzy dynamical models were used, and the global fuzzy models were translated into the system with uncertainties.
采用模糊动态模型逼近混沌非线性系统，将混沌非线性系统模糊化为局部线性模型。
Using T-S fuzzy model as an approximation, the nonlinear chaotic system is fuzzy and translated into local linear model.
针对具有严重非线性的受控对象，提出了一种模糊-神经元控制方法。
In accordance with the seriously nonlinear controlled objects, a fuzzy-neuron control scheme is proposed.
该控制策略充分利用了模糊逻辑对非线性的逼近性和神经控制自适应的特点。
The strategy made full use of the nonlinear approximation of fuzzy logic and the self-adaptability of neural control.
采用模糊动态模型逼近非线性混沌系统，将非线性混沌系统模糊化为局部线性模型。
By approximating the nonlinear chaotic system with a t s fuzzy model, the nonlinear chaotic system is fuzzed into a local linear model.
论述了综合运用非线性动态逆、自适应模糊系统和滑模控制的优点进行飞行控制律设计的方法。
The design of the flight controller that exploits the advantages of the nonlinear dynamic inversion, adaptive fuzzy system and slide model control is discussed.
采用模糊动态模型逼近非线性系统，将非线性系统模糊化为局部线性模型。
Using model as an approximation for nonlinear system, the nonlinear system has been fuzzified into local linear model.
将非线性混沌系统模糊化为局部线性模型。
The nonlinear chaotic system has been fuzzy into local linear model.
在非线性动态过程的建模中，融入了模糊逻辑和局部线性模型。
Fuzzy logic and local linear models are employed for modeling a non-linear dynamic process.
针对多输入-多输出(MIMO)非线性系统基于模糊基函数向量提出了一种新的自适应控制方法。
In this paper, a novel adaptive control approach based on fuzzy basis function vector is presented for Multi input and Multi output (MIMO) nonlinear systems.
将非线性系统用t - S模糊动态模型描述，并将全局模糊系统模型表示成不确定系统形式。
The nonlinear systems have been described into T-S fuzzy dynamical models, and the global fuzzy models have been translated into the system with uncertainties.
基于模糊神经网络算法研究了非线性系统的噪声消除问题，设计了一类非线性自适应逆噪声消除控制器。
Based on Fuzzy Neural Network, the noise canceling problem of the nonlinear system was studied. A type of nonlinear adaptive noise controller was proposed.
该文提出了一种基于最差子空间分解聚类的非线性系统模糊辨识方法。
This paper proposed a fuzzy identification method for nonlinear systems which were based on decomposing clustering of the worst subspace.
采用局部线性化方法，用T-S模糊线性模型逼近非线性系统。
The nonlinear plant is approximated by a Takagi-Sugeno fuzzy linear model using local linearization method.
采用局部线性化方法，用T-S模糊线性模型逼近非线性系统。
The nonlinear plant is approximated by a Takagi-Sugeno fuzzy linear model using local linearization method.
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