本文针对一类相坐标表示的线性不确定系统，根据滑模控制原理，提出一种基于模糊逻辑的滑模控制方法。
A method of sliding mode control based on fuzzy logic, for a class of linear uncertain system shown in phase coordinate, is presented It if derived from the principle of sliding mode control.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
采用T - S模糊动态模型描述非线性系统，并将非线性系统模糊化为局部线性模型。
Nonlinear system is described based on T-S fuzzy dynamical model, and the nonlinear system is translated into local linear model by fuzzy method.
在被调整模糊系统基础上，提出了一种非线性系统在线估计参数的在线辨识算法。
Moreover, based on this modified fuzzy system, the paper presents an on line identifying algorithm with which the on line parameter estimation of nonlinear system is realized.
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.
基于数据融合的思想，提出一种非线性系统的自适应神经网络模糊控制器的设计方法。
Based on data fusion method, an adaptive neuro-fuzzy controller of nonlinear systems is presented.
模糊系统对非线性函数逼近能力的研究。
针对一类非线性系统，把模糊tS模型和自适应模糊逻辑系统两类模糊逻辑方式结合起来，提出了一种基于观测器的控制方案。
Combining both kinds of fuzzy logic forms including fuzzy t s model and adaptive fuzzy logic systems, this paper presents an observer based control scheme for a class of nonlinear systems.
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两种模糊逻辑方式结合起来，提出了一种基于观测器的跟踪控制方案。
Combining both kinds of fuzzy logic forms including fuzzy T-S model and adaptive fuzzy logic systems, this paper presents an observer-based tracking control scheme for a class of nonlinear systems.
针对一类仿射非线性系统，研究其模糊建模与控制问题。
Fuzzy modeling and control for a class of affine nonlinear systems is studied.
此外，还开发了用以形成模糊专家系统框架核心的推理机制，并通过线性模糊矩阵代数运算予以实现。
Moreover, a fuzzy inference mechanism was developed to form the core of fuzzy expert system frame, which could be realized through linear fuzzy matrix algebra.
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.
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.
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.
采用T_S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 T_S model as an approximation for nonlinear system, the nonlinear system has been fuzzy into local linear model.
基于模糊动态模型研究非线性系统的稳定控制问题，将全局模糊系统模型表示成不确定系统形式。
The stable problem of nonlinear systems is studied based on fuzzy dynamical model, and the global fuzzy model is translated into the system with uncertainties.
讨论了利用模糊方法实现非线性系统的建模方法。
Nonlinear system modeling using fuzzy method is discussed in this paper.
本文将对一类非线性t - S模糊系统的非线性逼近能力进行研究，证明这种模糊系统在输入模糊子集为高斯型隶属函数的情况下，具有通用逼近性。
In this paper, we will study the nonlinear approximation of a kind of nonlinear T-S fuzzy system, and prove that when the fuzzy sets are Gaussian membership functions, it has universal approximation.
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.
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.
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